JP7548603B2 - Rental car management system using connected cars - Google Patents

Description

The present invention relates to a rental car operation system, and more specifically, to a rental car operation system that uses connected cars to provide a variety of information, such as traffic information, vehicle accident and abnormality information, fuel fees, fine collection, tourist route and store information, and network diagnosis with rental cars, by configuring rental cars as connected cars and collecting rental car driving information, and enables efficient rental car operation.

A connected car is a car that combines IT technology with automobiles to connect to the Internet. It can wirelessly connect to other vehicles or transportation and communication infrastructure to provide hazard warnings, real-time navigation, remote vehicle control and management services, and is evolving into a technology that also provides e-mail, multimedia streaming, and social networking services (SNS).

In the future, connected car technology is expected to evolve into autonomous driving, automatic charging of cars, and services that monitor the driver's health condition and blood alcohol concentration to check whether they are fit to drive. As shown in the patent document below, the development of connected car technology is ongoing.

Meanwhile, in tourist areas, rental cars are commonly used for the convenience of tourists, who rent cars for a certain period of time and then return them. Rental cars are essential, especially on islands such as Jeju Island and in tourist areas with poor public transportation.

Therefore, if connected cars are applied to rental cars used in tourist destinations, etc., it will become possible to manage rental cars, which are difficult to manage at present, and by collecting various driving information about the rental car, it will be possible to provide rental car users with a variety of information useful for sightseeing.

Korean Patent Publication No. 10-2018-0105503

The present invention has been made to solve the above-mentioned problems, and its purpose is to provide a rental car operation system that provides a variety of information using rental car driving information and enables efficient rental car operation by configuring rental cars as connected cars and collecting rental car driving information, etc.

The present invention aims to provide a rental car operation system that can provide accurate traffic information by providing traffic information that reflects the actual driving speed of the rental car.

The present invention aims to provide a rental car operating system that can increase the accuracy of traffic information by removing information on vehicles that are turned off or stopped for a certain period of time or that deviate from the travel route when calculating speed when traffic information is provided by a rental car.

The present invention aims to provide a rental car operation system that can improve the accuracy of traffic information from an external system by comparing traffic information from a rental car with traffic information from an external system and diagnosing the error.

The present invention aims to provide a rental car management system that can detect accidents by monitoring the impact of rental cars and enable rapid response to accidents.

The present invention aims to provide a rental car operating system that checks the rental car user's response when an impact exceeds a certain level, even if the impact is not as severe as an accident, and enables a quick response even to minor accidents or vehicle abnormalities.

The present invention aims to provide a rental car management system that can efficiently manage rental cars by responding to abnormal vibrations caused by vehicle abnormalities by recognizing and informing the driver even when a weak impact occurs continuously.

The present invention aims to provide a rental car management system that analyzes the correlation between the operating status and fuel consumption of each rental car, and automatically calculates and bills the rental car user for fuel costs incurred during vehicle operation using the analyzed correlation, thereby reducing disputes and inconveniences regarding rental car fuel costs.

The present invention aims to provide a rental car operating system that allows users to refuel using a card attached to the rental car and gives points to the rental car user according to the price they pay for refueling, thereby providing convenience to the user and enabling them to reduce fuel costs associated with operating the rental car.

The present invention aims to provide a rental car operating system that automatically detects the possibility of enforcement for traffic law violations during the operation of a rental car and secures the fine in advance, thereby allowing fines to be levied quickly and smoothly, and automatically refunds the fine if it is found that the violation has not been enforced, thereby protecting the interests of the user.

The present invention aims to provide a rental car operating system that can improve the convenience of sightseeing using rental cars by analyzing the driving route of a rental car user and making recommendations for sightseeing routes.

The present invention aims to provide a rental car operating system that can increase users' satisfaction with purchasing tourist products and also increase the sales rate of local tourist product sellers by analyzing product purchasing information and preference information for each location in an area where a rental car is used, and selecting locations with a high purchasing index on a route recommended for the rental car and providing them to a mobile store operator.

The present invention aims to provide a rental car management system that allows for smooth collection of information from rental cars by diagnosing network anomalies with rental cars and allowing prompt action to be taken.

To achieve the above objective, the present invention is realized in an embodiment having the following configuration.

According to one embodiment of the present invention, the rental car operating system of the present invention includes a rental car that is rented by a user for a certain period of time, used, and returned, and that measures and transmits operating information related to the vehicle, a user terminal that searches for the rental car, selects the rental car to be used, and receives information about the rental car, and an operating server that communicates with the user terminal and the rental car, allows a usage contract for the rental car to be concluded, and receives operating information measured by the rental car, and the operating server analyzes the operating information measured by the rental car and provides information necessary for operating the rental car.

According to another embodiment of the present invention, in the rental car management system according to the present invention, the management server includes a vehicle information collection unit that collects operating information of rental cars, and a traffic information provision unit that analyzes and provides traffic information using the collected operating information, and the traffic information provision unit includes a movement information collection module that collects rental car movement information for each section of a road, a movement speed calculation module that calculates the movement speed of the rental car moving in each section, a speed information refining module that removes speed information of rental cars having excessively low or high movement speeds, an average speed calculation module that calculates the average speed of the rental car for each section, a congestion degree display module that calculates and displays the congestion degree according to the calculated average speed, and an automatic route reflection module that automatically reflects the congestion degree in the movement route guided through navigation and updates the route.

According to another embodiment of the present invention, in the rental car operating system according to the present invention, the traffic information providing unit includes a filtering module that removes rental car information that becomes noise in the calculation of the travel speed for each section, and the filtering module is characterized by including a start time discrimination module that removes information on rental cars whose engines have been turned off for a certain period of time or more, a stop time discrimination module that removes information on rental cars that have been stopped for a certain period of time or more even with the engines turned on, and a travel route discrimination module that removes information on rental cars whose routes deviate from the route for each section.

According to another embodiment of the present invention, in the rental car operation system of the present invention, the operation server includes a traffic information optimization unit that optimizes traffic information by an external system using traffic information analyzed by the traffic information providing unit, and the traffic information optimization unit includes an external traffic information collection module that collects external traffic information, a traffic information comparison module that compares the external traffic information with the results analyzed by the traffic information providing unit, an image discrimination module that checks whether or not there is an accident using a vehicle image if the external traffic information and the traffic information analyzed by the traffic information providing unit differ by more than a certain degree, an abnormality information generation module that generates abnormality information in the traffic information if an accident cannot be confirmed from the image, an abnormality number calculation module that calculates the number of times abnormality information occurs, and an abnormality information provision module that provides traffic information from a rental car to be reflected in the external traffic information system if the number of times abnormality information occurs for more than a certain period of time exceeds a reference value.

According to another embodiment of the present invention, in the rental car management system of the present invention, the management server includes an impact monitoring unit that monitors impacts on the rental car vehicle, and the impact monitoring unit includes an impact information receiving module that receives vibration information measured by the rental car that is above a certain level as impact information, and an accident determination module that determines that an impact on the rental car exceeds a certain level as an accident and notifies the driver of the impact.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the impact monitoring unit includes a danger recognition module that recognizes and takes measures when an impact occurs to the rental car within a certain range below the impact that is determined to be an accident, and the danger recognition module includes a dangerous impact detection module that detects a dangerous impact within a certain range below the impact that is determined to be an accident, a confirmation signal transmission module that transmits a signal to the rental car to confirm the dangerous impact when it is detected, a response signal confirmation module that recognizes a dangerous situation when a response to the confirmation signal is not received within a certain time, and an emergency dispatch instruction module that instructs an emergency dispatch when a dangerous situation is recognized.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the impact monitoring unit includes an abnormality confirmation module that determines that an abnormality in the rental car occurs when an impact to the rental car is not recognized as a dangerous impact but continues within a certain range below that, and notifies the user of the abnormality confirmation module. The abnormality confirmation module includes an impact information storage module that stores information about a certain range of impacts below the dangerous impact, a repetition frequency calculation module that calculates the frequency at which impacts in the certain range are repeated, a reference value comparison module that compares the calculated frequency with a reference value, a consecutive number calculation module that calculates the number of consecutive impacts with a frequency exceeding the reference value, and an abnormality notification module that notifies the user of an abnormality in the rental car if the consecutive number exceeds a predetermined number.

According to another embodiment of the present invention, in the rental car management system of the present invention, the management server includes an oil cost calculation unit that automatically calculates the oil cost of the rental car and bills the user, and the oil cost calculation unit includes a correlation analysis module that analyzes the correlation between the operating state and fuel consumption of each rental car, an operation information receiving module that receives operation information during the rental period of the rental car for which the oil cost is to be billed, an oil cost calculation module that inputs the operation information into the correlation analyzed by the correlation analysis module to calculate the oil cost, and an automatic oil cost billing module that automatically bills the user for the calculated oil cost when the rental car is returned, and the correlation analysis module includes an operation information loading module that reads the start information, speed information, and acceleration/deceleration information of the rental car, a refueling information loading module that reads the refueling information for the rental car, and a correlation derivation module that derives the correlation between the operation information and fuel consumption for each rental car.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the operating server includes an oil cost discount unit that provides discounts on oil costs according to the unit price of refueling by the rental car user, and the oil cost discount unit includes a refueling unit price loading module that loads refueling unit price information from the refueling information of the user, a unit price information collection module that collects oil unit price information for the area in which the rental car is used at the time the user refuels, a standard unit price setting module that sets the average value of the oil unit prices collected by the unit price information collection module as a standard unit price, a reduction ratio calculation module that calculates an oil cost reduction ratio based on the difference between the user's refueling unit price and the standard unit price, a refueling point calculation module that calculates refueling points by multiplying the reduction ratio by the amount of refueling by the user, and an automatic oil cost deduction module that automatically deducts the calculated refueling points from the oil cost to be paid by the user.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the operating server includes a fine calculation unit that automatically reflects the rental car user's traffic law violation information and charges the fine in advance, and the fine calculation unit includes a location information loading module that reads the rental car's location information, a speed information loading module that reads the speed information, a enforcement position collection module that collects vehicle enforcement position information, a violation determination module that determines whether or not there is a violation of traffic laws such as speeding, parking prohibition, cutting in, and bus-only lane prohibition at the enforcement position, a fine calculation module that calculates the fine during the rental car use period depending on whether or not there is a traffic law violation, an automatic fine claim module that adds the fine to the user's fuel expenses and claims it, and a fine refund module that reflects the actual enforcement situation and automatically refunds the fine that was claimed if the violation is not enforced.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the operating server includes a tourist route providing unit that analyzes the travel route of the rental car user and recommends a tourist route, and the tourist route providing unit includes a user information collecting module that collects information on the age, sex, and nationality of the rental car user, a weather information collecting module that collects weather information at the time of rental car use, a time information collecting module that collects information on the time of rental car use, a stay information collecting module that collects stay position information of the rental car user according to the rental car operating route, a correlation analysis module that analyzes the correlation between the user, weather, time information, and the stay position, and a recommended route providing module that provides a recommended tourist route to the rental car user according to the analyzed correlation.

According to another embodiment of the present invention, in the rental car operation system according to the present invention, the operation server includes a store information providing unit that analyzes product purchase information according to the travel route of the rental car user and recommends the location of a mobile store for tourists, and the store information providing unit includes a purchase analysis module that analyzes product purchase information by region, and a location recommendation module that recommends and provides the location of a mobile store based on the results of the analysis by the purchase analysis module, and the purchase analysis module includes a location information input module that inputs location information of the region where the rental car is used, a purchase information analysis module that analyzes purchase information for a specific product group at each location, and a purchase information analysis module that analyzes purchase information for a specific product group purchased at each location. and a purchasing index calculation module that calculates a purchasing index based on the purchasing degree and the preference degree for a specific product group at each position along the travel route, and the location recommendation module includes a product information input module that inputs information on the product group for which the mobile store is to be installed, a recommended route loading module that loads information on the travel route recommended to the rental car user by the tourist route providing unit, a purchasing index comparison module that compares the purchasing index by position of the recommended route during a unit period, and a recommended location providing module that recommends the location of the mobile store at a position with a high purchasing index, taking into account the number of visits by position along the recommended route.

According to another embodiment of the present invention, in the rental car management system of the present invention, the management server includes a network diagnostic unit that diagnoses communication abnormalities with the rental car by sending a confirmation signal to the rental car at regular intervals, and the network diagnostic unit includes a fault detection unit that determines that a communication fault has occurred if a response to the confirmation signal is not received at a certain frequency or more, and the fault detection unit includes a confirmation signal transmission module that sends a confirmation signal to the rental car at regular intervals, a response signal receiving module that receives a response signal to the confirmation signal, a non-reception frequency calculation module that calculates the frequency at which a response signal is not received at a certain unit time interval, and a fault determination module that determines that a fault has occurred and notifies the user if the non-reception frequency exceeds a reference value.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the network diagnosis unit includes an abnormality diagnosis unit that determines that network performance has deteriorated and notifies the user when the frequency of non-reception of a response signal continues within a certain range even if it is not detected as a failure, and the abnormality diagnosis unit includes a danger range recognition module that recognizes that the frequency of non-reception of a response signal has reached a danger range below the frequency at which a failure is detected, a duration count calculation module that calculates the number of times the danger range continues, a reference value comparison module that compares the duration count with a reference value, and an inspection notification instruction module that determines that performance has deteriorated and notifies the user when the duration count exceeds the reference value.

According to another embodiment of the present invention, in the rental car operating system of the present invention, the network diagnosis unit includes an emergency notification unit that detects and notifies an emergency abnormality in the network even before the failure detection unit or the abnormality diagnosis unit diagnoses a failure or performance degradation, and the emergency notification unit includes a no-response information receiving module that receives no-response information, a consecutive number calculation module that calculates the number of consecutive no-responses when there are consecutive no-responses, and an emergency abnormality transmission module that determines that an emergency abnormality has occurred and notifies when the consecutive number of times exceeds a predetermined value.

The present invention can achieve the following effects through this embodiment and the configuration, combination, and usage relationship described below.

The present invention has the effect of providing a variety of information using rental car driving information and enabling efficient rental car management by configuring rental cars as connected cars and collecting rental car driving information.

The present invention has the effect of providing accurate traffic information by providing traffic information that reflects the actual driving speed of the rental car.

The present invention has the effect of improving the accuracy of traffic information by removing information on vehicles that are turned off or stopped for a certain period of time or that deviate from the travel route when traffic information is provided by a rental car, and calculating the speed.

The present invention has the effect of improving the accuracy of traffic information from external systems by comparing traffic information from rental cars with traffic information from external systems and diagnosing the error.

The present invention has the effect of enabling rapid response to accidents by monitoring the impact of rental cars and detecting accidents.

The present invention has the effect of checking the rental car user's response when the impact is greater than a certain level, even if it is not the level of an accident, and enabling a quick response even to minor accidents or vehicle abnormalities.

The present invention has the effect of enabling efficient management of rental cars by responding to abnormal vibrations caused by vehicle abnormalities, by recognizing and notifying the driver even when a weak impact occurs continuously.

The present invention has the effect of reducing disputes and inconveniences regarding rental car oil fees by analyzing the correlation between the operating status and fuel consumption of each rental car, and automatically calculating and charging the rental car user for the oil fees incurred when operating the vehicle using the analyzed correlation.

The present invention has the effect of providing convenience to users and reducing fuel costs associated with operating a rental car by allowing users to refuel using a card attached to the rental car and giving points to the rental car user based on the price at which they refuel.

The present invention has the effect of automatically detecting the possibility of enforcement for traffic law violations while the rental car is in operation and securing the fine in advance, thereby making it possible to quickly and smoothly impose the fine, and by automatically refunding the fine if it is found that the violation has not been enforced, it also protects the interests of the user.

The present invention has the effect of improving the convenience of sightseeing using rental cars by analyzing the driving route of a rental car user and making recommendations for sightseeing routes.

The present invention has the effect of increasing users' satisfaction with purchasing tourism products and increasing the sales rate of local tourism product sellers by analyzing product purchasing information and preference information for each location in an area where a rental car is used, and selecting locations with a high purchasing index on a route recommended for the rental car and providing them to a mobile store operator.

The present invention has the effect of making it possible to smoothly collect information from rental cars by diagnosing network anomalies with rental cars and taking prompt action.

FIG. 1 is a configuration diagram of a rental car operation system using a connected car according to an embodiment of the present invention. FIG. 2 is a block diagram showing a configuration of the administration server of FIG. 1 . 3 is a block diagram showing a configuration of a vehicle information collection unit in FIG. 2 . 3 is a block diagram showing a configuration of a traffic information providing unit in FIG. 2. 3 is a block diagram showing a configuration of a traffic information optimization unit in FIG. 2. FIG. 2 is a block diagram showing a configuration of an impact monitoring unit. FIG. 7 is a block diagram showing the configuration of the danger perception module of FIG. 6 . FIG. 7 is a block diagram showing the configuration of an abnormality confirmation module in FIG. 6 . 3 is a block diagram showing the configuration of an oil cost calculation unit in FIG. 2. 3 is a block diagram showing the configuration of the oil cost discount unit of FIG. 2. 3 is a block diagram showing the configuration of a penalty fee calculation unit in FIG. 2. 3 is a block diagram showing a configuration of a tourist route providing unit in FIG. 2. 3 is a block diagram showing a configuration of a store information providing unit in FIG. 2. 3 is a block diagram showing a configuration of a network diagnostic unit in FIG. 2. FIG. 13 is a block diagram showing a configuration of an administration server according to another embodiment of the present invention. 16 is a block diagram showing a configuration of a price model determination unit in FIG. 15. FIG. 16 is a block diagram showing a configuration of a price calculation unit in FIG. 15 . 16 is a block diagram showing a configuration of a price adjustment unit in FIG. 15 . FIG. 16 is a block diagram showing a configuration of a provider-specific providing unit in FIG. 15 . FIG. 16 is a block diagram showing the configuration of the cancellation and resale unit of FIG. 15 .

A preferred embodiment of a rental car operating system using a connected car according to the present invention will be described in detail below with reference to the accompanying drawings. In the following description of the present invention, if it is determined that a detailed description of a known function or configuration may make the gist of the present invention unclear, the detailed description will be omitted. Throughout the specification, when a part "includes" a certain component, this does not mean that other components are excluded, but that other components may be further included, unless otherwise specified. In addition, terms such as "... unit" and "... module" described in the specification refer to a unit that processes at least one function or operation, which can be realized by hardware, software, or a combination of hardware and software.

A rental car operating system using a connected car according to one embodiment of the present invention will be described with reference to Figures 1 to 14. The rental car operating system includes a rental car 200 that a user rents, uses, and returns for a certain period of time, and measures and transmits operating information related to the vehicle, a user terminal 300 that searches for the rental cars 200, selects the rental car 200 to be used, and receives information related to the rental car, and an operating server 100 that communicates with the user terminal 300 and the rental car 200, allows a usage contract for the rental car 200 to be concluded, and receives operating information measured by the rental car 200.

The rental car operating system according to the present invention allows a rental car 200 to be used through the operating server 100, and a rental car user searches for and selects a required rental car through a user terminal 300 connected to the operating server 100 through wired or wireless communication, and a usage contract is then concluded. In particular, the present invention allows the rental car 200 to be formed as a connected car, and various information about the rental car 200 to be collected through the operating server 100, and the rental car 200 can be managed using the collected information and various information required for driving can be provided. Therefore, the rental car 200 is formed to collect start information, speed information, acceleration/deceleration information, position information, vibration information, refueling information, video information, etc. through various sensors, and transmits the collected information to the operating server 100. In addition, the user terminal 300 can be various devices such as a smartphone, tablet, and PC capable of wired or wireless communication with the operating server 100, and can receive and display rental car 200 information from the operating server 100, select the rental car 200 to be used, enter into a usage contract, and receive various information about the rental car 200.

The management server 100 communicates with the user terminal 300 and the rental car 200 by wire or wireless, concludes a usage contract for the rental car 200, and manages and provides various information for the rental car 200. In particular, the management server 100 can collect and process various information measured by the rental car 200. The management server 100 can collect and store information measured by the rental car 200 in real time, provide traffic information for each road through the operation information of the rental car 200, and optimize traffic information of an external traffic system through the traffic information from the rental car 200. In addition, the management server 100 can monitor the impact of the rental car 200 to detect accidents and abnormalities, and can accurately calculate and charge oil costs through the operation information of the rental car 200, provide discounts for refueling, and charge fines for violations of traffic laws in advance so that the fines for the rental car can be paid quickly. In addition, the operation server 100 can analyze the travel route of the rental car 200 to recommend tourist routes that are frequently visited by users, or recommend the location of a mobile store to a business selling tourist products, etc., and provide the recommended tourist route. The operation server 100 can monitor the communication between the rental car 200 and the operation server 100 to detect abnormalities and maintain smooth communication. To this end, the operation server 100 can include a vehicle information collection unit 1, a traffic information provision unit 2', a traffic information optimization unit 3, an impact monitoring unit 4, an oil cost calculation unit 5, an oil cost discount unit 6, a penalty calculation unit 7, a tourist route provision unit 8, a store information provision unit 9, and a network diagnosis unit 10.

The vehicle information collection unit 1 is configured to collect information measured by the rental car 200, and can collect and store information measured through various sensors of the rental car 200 in real time. The vehicle information collection unit 1 can include a start information collection module 11 for collecting start information of the rental car 200, a speed information collection module 12 for collecting speed information, an acceleration/deceleration information collection module 13 for collecting information regarding acceleration and deceleration, a location information collection module 14 for collecting location information, a vibration information collection module 15 for collecting information regarding vibration of the rental car 200, a refueling information collection module 16 for collecting refueling information regarding the refueling time, amount of refueling, refueling unit price, etc., and an image information collection module 17 for collecting image information captured through a black box, etc., in the rental car 200.

The traffic information providing unit 2' is configured to provide traffic information on roads using operation information of the rental car 200, and can provide information on the degree of congestion on the roads. The traffic information providing unit 2' can collect movement information of the rental car 200 for each section of the road, calculate the speed, and analyze and provide the degree of congestion for each section accordingly. Preferably, the congestion information analyzed can be automatically reflected and corrected on the navigation route of the rental car 200. In addition, the traffic information providing unit 2' can remove rental car 200 information such as stopping in the middle or leaving to a waypoint during the movement of the rental car 200 for each section, and calculate the speed, thereby providing more accurate traffic information. For this purpose, the traffic information providing unit 2' can include a section-by-section movement information collecting module 21, a filtering module 22, a movement speed calculation module 23, a speed information refining module 24, an average speed calculation module 25, a congestion degree display module 26, and an automatic route reflection module 27.

The section-by-section movement information collection module 21 is configured to collect information on the rental car 200 moving along each section of the road, and collects information such as the position, speed, and start of the rental car 200.

The filtering module 22 is configured to remove information from the information of the rental car 200 moving through each section that reduces the accuracy of the calculation of traffic information for each section, and may include a start time determination module 221, a stop time determination module 222, and a travel route determination module 223.

The start-up time determination module 221 is configured to determine whether the start-up of the rental car 200 is turned off while traveling between each section, and if the start-up is turned off for a certain period of time or longer, the information of the rental car 200 is not reflected in the analysis of traffic information.

The stop time determination module 222 is configured to determine the time that the rental car 200 is stopped while traveling between each section, and if the rental car is stopped for a certain period of time or longer, it is determined that the rental car has stayed at a specific location and the rental car information is excluded from the analysis of traffic information.

The travel route determination module 223 is configured to analyze the travel route of the rental car 200 moving through each section, and removes information about the vehicle that moves through each section but leaves each section midway, thereby preventing inaccurate traffic information from being calculated.

The travel speed calculation module 23 is configured to calculate the travel speed of the rental car 200 for each section, and can calculate the travel speed using the time it takes to pass the start and end points of each section and distance information for each section.

The speed information refining module 24 is configured to remove noise from the speed of the rental car 200 calculated by the moving speed calculation module 23, and removes speeds that deviate from the average speed of the rental car 200 by a certain degree or more, i.e., speed information that is too low or too high. Therefore, the speed information refining module 24 can prevent erroneous information from being used to calculate the moving speed when erroneous information is received due to errors in the network, data, sensor, etc., or when the filtering module 22 does not operate normally, thereby improving the accuracy of traffic information.

The average speed calculation module 25 is configured to calculate the average travel speed of each section, and calculates the average value for the travel speed of the rental car 200. At this time, the average speed calculation module 25 removes inaccurate information using the filtering module 22 and the speed information refining module 24, so that the average speed can be calculated.

The congestion level display module 26 is configured to display the level of congestion for each section of the road, and presets the level of congestion for each section based on the average speed, and displays information based on the set congestion level to the user. The congestion level display module 26 can be displayed via the user terminal 300, but is preferably displayed directly on the screen of the rental car 200.

The automatic route reflection module 27 is configured to automatically reflect the degree of congestion displayed by the congestion level display module 26 in route guidance via vehicle navigation, and updates the route to reflect the degree of congestion in real time, thereby providing optimal route guidance without any additional operations.

The traffic information optimization unit 3 optimizes traffic information of an external traffic information system using traffic information provided through the traffic information providing unit 2', and improves the accuracy of traffic information provided from the external traffic information system by reflecting traffic information analyzed through the operation of an actual rental car 200 to the external traffic information system. In the case of an existing external traffic information system, road congestion information is analyzed through various sensors and images, but it is very difficult to accurately analyze congestion information for all sections of a road in real time. Therefore, the traffic information optimization unit 3 grasps the degree of congestion through operation information of a large number of rental cars 200 operated in real time, and reflects such information to the external traffic system, thereby improving the accuracy of traffic information of the external traffic system. To this end, the traffic information optimization unit 3 may include an external traffic information collection module 31, a traffic information comparison module 32, an image discrimination module 33, an anomaly information generation module 34, an anomaly count calculation module 35, and an anomaly information provision module 36.

The external traffic information collection module 31 is configured to collect traffic information from an external system, and receives traffic information in real time from an external server that analyzes traffic information, such as an existing police agency.

The traffic information comparison module 32 is configured to compare the traffic information analyzed by the traffic information providing unit 2' with the traffic information collected by the external traffic information collecting module 31, and compares information regarding the degree of congestion for each section.

The image discrimination module 33 is configured to check the image of the section where the error occurred if an error of a certain level or more occurs as a result of the comparison by the traffic information comparison module 32, and can check and discriminate the image captured and collected from the rental car 200. The image discrimination module 33 can check whether an accident has occurred, and preferably can automatically read the image to determine whether an accident has occurred, and in some cases can check the image and manually input accident information.

The anomaly information generation module 34 is configured to generate anomaly information when the confirmation result by the image discrimination module 33 indicates that no accident has occurred, and generates information indicating that there is an anomaly in the traffic information from the external traffic information system.

The abnormality count calculation module 35 is configured to calculate the number of times abnormality information occurs, and stores the number of times abnormality information is generated by the abnormality information generation module 34 together with time information.

The anomaly information providing module 36 is configured to transmit information to the external traffic information system that there is an error in the analysis of traffic information by the external traffic information system when the number of occurrences of anomaly information calculated by the anomaly count calculation module 35 exceeds a reference number within a certain period of time, so that the external traffic information system can inspect the system and correct the analysis method.

The impact monitoring unit 4 is configured to monitor impacts occurring on the rental car 200, and detects impacts using vibration information collected from the rental car 200, thereby enabling quick recognition of accidents or abnormalities occurring in the rental car 200. In particular, the impact monitoring unit 4 can not only recognize accidents through impacts above a certain level, but also, when an impact that is not above a certain level but is in a dangerous range occurs, it can check the situation of the rental car 200 and take appropriate measures, and when impacts below the dangerous range occur continuously, it can determine that an abnormality in the vehicle exists and take appropriate measures. For this purpose, the impact monitoring unit 4 can include an impact information receiving module 41, an accident determination module 42, a danger recognition module 43, and an abnormality confirmation module 44.

The shock information receiving module 41 is configured to receive shock information of the rental car 200, and recognizes vibrations occurring to the rental car 200 above a certain level as a shock and receives information related thereto. Therefore, the shock information receiving module 41 recognizes only vibrations above a certain level caused by accidents or vehicle abnormalities, excluding general vibrations, as shocks and transmits them to the operation server 100, thereby reducing the amount of data transmitted.

The accident determination module 42 is configured to determine that an accident has occurred in the rental car 200 if the impact on the rental car 200 exceeds a certain level, and enables measures such as emergency dispatch and reporting due to the accident to be taken automatically and quickly.

The danger recognition module 43 is configured to recognize that the impact of the rental car 200 is not an impact that is recognized as an accident, but an impact occurs within a danger range below that level, and transmits a confirmation signal to the rental car where an impact in the danger range has occurred to check whether it is abnormal, and if there is no response within a certain time, an emergency dispatch is made to confirm the abnormality. Therefore, the danger recognition module 43 can efficiently manage the rental car abnormality by confirming the impact that is not an accident but is within a danger range and then sending out an emergency dispatch. In other words, the accident judgment module 42 can recognize only impacts above a certain level as accidents and send out an emergency dispatch, thereby sensitively recognizing accidents and preventing the problem of excessive emergency dispatches, and the danger recognition module 43 can confirm the rental car even for impacts within a danger range below that level and then send out an emergency dispatch, so that a quick response can be made to situations such as minor accidents and driver health abnormalities. For this purpose, the danger recognition module 43 may include a danger impact detection module 431, a confirmation signal transmission module 432, a response signal confirmation module 433, and an emergency dispatch instruction module 434.

The dangerous impact detection module 431 is configured to detect when an impact to the rental car 200 reaches a dangerous range below a certain level that is deemed to be an accident, and is capable of recognizing and dealing with impacts that are not large enough to be deemed an accident but are in a dangerous range that may cause a minor accident.

The confirmation signal transmission module 432 is configured to transmit a confirmation signal to the rental car 200 when an impact in a dangerous range is detected, and the confirmation signal can be transmitted by installing a separate notification device in the rental car 200 itself, or by transmitting the confirmation signal via the user terminal 300.

The response signal confirmation module 433 is configured to confirm the response signal to the confirmation signal, and can transmit the response signal via a notification device installed in the rental car 200 itself or via the user terminal 300, and confirms whether the response signal is received within a certain period of time.

The emergency dispatch instruction module 434 is configured to determine that an abnormality has occurred in the rental car 200 and instruct an emergency dispatch if a response signal is not received within a certain period of time after sending a confirmation signal, thereby enabling rapid response to accidents that have not involved a major impact or driver abnormalities, etc.

The abnormality confirmation module 44 is configured to detect the continuous occurrence of abnormal impacts due to a vehicle abnormality even if there is no possibility of an accident occurring, and allows notification or inspection of the vehicle abnormality to be performed. To this end, the abnormality confirmation module 44 may include an impact information storage module 441, a repetition frequency calculation module 442, a reference value comparison module 443, a consecutive number calculation module 444, and an abnormality notification module 445.

The impact information storage module 441 is configured to store information about an impact within a certain range below a danger range, together with information about the time of impact.
The repetition frequency calculation module 442 is configured to calculate the occurrence frequency of the impact stored by the impact information storage module 441, so that it is possible to determine how frequently the impact occurs.

The reference value comparison module 443 is configured to compare the frequency of impacts calculated by the repetition frequency calculation module 442 with a reference value, and sets the frequency of impacts that can be determined to be an abnormality in the vehicle as the reference value for comparison.

The consecutive number calculation module 444 is configured to calculate the consecutive number of times that the frequency of repetition of an impact exceeds a reference value, making it possible to detect frequent and consecutive occurrences of impacts.

The abnormality notification module 445 is configured to notify of a vehicle abnormality when the frequency of repeated impacts exceeds a reference value and the number of consecutive impacts exceeds a predetermined number, and detects an abnormality only when impacts occur frequently and continuously, and can detect and notify only impacts caused by vehicle abnormalities, excluding impacts caused by mistake that are more than temporary. The abnormality notification module 445 can notify the rental vehicle of an abnormality so that the vehicle can perform a self-inspection or a warning, and can also dispatch a vehicle to the rental vehicle to perform an inspection.

The oil cost calculation unit 5 is configured to calculate the oil cost for the operation of the rental car 200, and to charge the calculated oil cost to the user when returning the rental car 200. Existing oil costs for rental cars 200 are paid by calculating the oil cost using the vehicle's fuel gauge, or by renting a vehicle filled with fuel and returning it filled with fuel. However, the calculation of oil costs using a fuel gauge is less accurate, and even if the vehicle is returned filled with fuel, it must be refueled only near the return location where the unit price of refueling is high, which causes great inconvenience and dissatisfaction for rental car users. Therefore, in recent vehicle sharing systems, a method has been used in which fuel is refueled through a fuel card provided by the operating entity and the oil cost is automatically charged according to the distance traveled by the vehicle. However, even in such cases, although the convenience of the user has increased, the accuracy of the calculation is reduced by simply charging based on the distance, and a higher oil cost is charged than if the vehicle were refueled directly, resulting in a situation in which the damage to the user is rather high. Therefore, in this system, fuel is supplied via a fuel card provided in the rental car 200, and the fuel cost is automatically calculated according to the vehicle's operating condition, and the calculation of the fuel cost is performed by analyzing the correlation between the operating condition and the fuel consumption amount, thereby allowing for convenient and reasonable calculation of the fuel cost. For this purpose, the oil cost calculation unit 5 can include a correlation analysis module 51, an operating information receiving module 52, an oil cost calculation module 53, and an automatic oil cost billing module 54.

The correlation analysis module 51 is configured to analyze the correlation between the driving status and fuel consumption for each rental car 200, and collects driving status and refueling information of the rental car 200 collected for a certain period of time to form big data, and analyzes the correlation between the driving status and fuel consumption by a mechanical learning method using the big data. To this end, the correlation analysis module 51 may include a driving information loading module 511, a refueling information loading module 512, and a correlation derivation module 513.

The operation information loading module 511 is configured to read operation information of each rental car 200, and reads starting information, speed information, acceleration/deceleration information, position information, etc. that affect the fuel consumption of the rental car 200.

The refueling information loading module 512 is configured to read the refueling information of each rental car 200, and uses the loaded refueling information to calculate the amount of fuel consumed while the rental car 200 is operating.

The correlation derivation module 513 is configured to derive the correlation between operation information and fuel consumption, and uses the rental car's operating time, operating distance, speed, acceleration/deceleration, etc. as input variables to derive the correlation with fuel consumption through mechanical learning.

The operation information receiving module 52 is configured to receive operation information for each rental car 200, and receives start, speed, acceleration/deceleration, and position information collected during the use of the rental car 200 to calculate operation information.

The oil cost calculation module 53 is configured to calculate the oil cost associated with the use of the rental car 200, inputting the operation information received by the operation information receiving module 52 into the correlation derived by the correlation analysis module 51 to calculate the amount of fuel consumed, and calculating the oil cost using the amount of fuel consumed.

The automatic oil fee billing module 54 is configured to automatically bill the rental car user for the oil fee calculated by the oil fee calculation module 53, and preferably, the oil fee can be billed via the user terminal 300, and the return is completed only when the billed oil fee is settled.

The oil cost discount unit 6 is configured to discount the oil cost according to the unit price of refueling of the rental car user through the refueling card installed in the rental car 200, and to discount and charge the oil cost calculated by the oil cost calculation unit 5. In the present invention, the oil cost is automatically calculated and charged according to the operating state of the rental car, and refueling is paid for using the refueling card installed in the rental car 200. In such a case, the rental car user may refuel without checking the unit price of refueling at the gas station, which may increase the oil cost burden on the rental car operator. Therefore, the present invention allows convenient refueling through the operator's refueling card, discounts the oil cost according to the unit price of refueling for the rental car user, and induces the rental car user to find a gas station with a low unit price of refueling and refuel, thereby reducing the oil cost burden. For this purpose, the oil cost discount unit 6 can include a fuel unit price loading module 61, a unit price information collection module 62, a standard unit price setting module 63, a savings rate calculation module 64, a fuel point calculation module 65, and an automatic oil cost deduction module 66.

The refueling unit price loading module 61 is configured to read refueling unit price information for the rental car user's refueling, and can receive and read unit price information for the gas station where the user refueled from an external server.

The unit price information collection module 62 is configured to collect refueling unit price information for gas stations in the area where the rental car is used, and collects unit price information on the day of refueling from an external server that manages refueling unit price information.

The base unit price setting module 63 is configured to set a base unit price that serves as the basis for refueling cost discounts using the refueling unit price information collected by the unit price information collection module 62, and sets the base unit price to the average value for the refueling unit prices in the area on the day of refueling.

The saving ratio calculation module 64 is configured to calculate the ratio by which the rental car user has saved on refueling costs, and calculates the saving ratio by dividing the difference between the user's refueling unit price loaded by the refueling unit price loading module 61 and the standard unit price by the standard unit price.

The refueling point calculation module 65 is configured to calculate points based on the rental car user's refueling cost savings ratio, and calculates the refueling points to receive a discount by multiplying the savings ratio calculated by the savings ratio calculation module 64 by the amount of refueling the user has performed.

The automatic oil cost deduction module 66 is configured to automatically reflect and deduct the refueling points calculated by the refueling point calculation module 65 from the oil cost, and when the automatic oil cost billing module 54 bills for the oil cost, only the refueling points are automatically deducted and billed.

The fine calculation unit 7 is configured to calculate and claim fines in advance for violations of traffic laws by rental car users, and claims and receives fines in advance when traffic laws are violated at locations where traffic law enforcement cameras are installed, and pays the received fine immediately when enforcement information reaches the operation server. When a rental car user violates traffic laws and is caught by a traffic enforcement camera, the rental car user was found later and the fine was claimed separately and paid, but there was a problem that the fine was not properly imposed if information about the rental car user was registered incorrectly or if the rental car user's information was changed. Therefore, the fine calculation unit 7 can use the driving information of the rental car 200 to determine whether or not a traffic violation has occurred and receive the fine in advance, so that the fine for the traffic violation of the rental car 200 can be imposed promptly and without omission, and if it is later found that the traffic violation has not occurred, the fine that was received in advance can be automatically returned immediately, so that the fine can be prevented from being unjustly charged. For this purpose, the fine calculation unit 7 can include a location information loading module 71, a speed information loading module 72, a enforcement location collection module 73, a violation determination module 74, a fine calculation module 75, an automatic fine claim module 76, and a fine return module 77.

The location information loading module 71 is configured to read the location information of the rental car, and allows the driving route of the rental car to be understood through the location information.

The speed information loading module 72 is configured to read the speed information of the rental car, and is capable of determining whether the rental car is speeding and whether the rental car is parking or stopping at a specific location.

The enforcement location collection module 73 is configured to collect location information of cameras that enforce traffic law violations, and can be configured to collect location information of cameras that enforce speeding violations, parking violations, bus-only lanes, and no-cutting regulations.
The violation determination module 74 is configured to determine whether the rental car has violated traffic laws, and determines whether the rental car 20 exceeds the specified speed at a location photographed by a speed violation camera, whether it enters a bus-only lane at a location photographed by a camera that regulates bus lanes, whether it parks beyond the parking time at a location photographed by a camera that regulates parking and stopping, whether it cuts in at a location photographed by a camera that regulates cutting in, etc.

The fine calculation module 75 is configured to calculate the fine for traffic violations determined by the violation determination module 74, and calculates the fine by adding up the fines for each type of traffic violation.

The automatic penalty fee claim module 76 is configured to claim the calculated penalty fee from the rental car user, and can be configured to claim the fee together with fuel fees via the user terminal 300 when the rental car is returned.

The fine refund module 77 is configured to automatically refund the fine if it is discovered that a rental car user who has paid the fine in advance has not been caught, and the fine can be automatically refunded via the user's account.

The tourist route providing unit 8 is configured to analyze the movement route of the rental car user and provide the frequently visited tourist route to the rental car user, and analyzes the movement characteristics according to the characteristics and environmental information of the rental car user to provide the tourist route. The tourist route providing unit 8 can collect information of users who enter an area where a rental car is used during a certain period of time and stay information to perform big data analysis, and analyzes the correlation of the movement route according to the personal characteristics and environmental information of the rental car user to provide the rental car user with the tourist route that the user frequently visits. To this end, the tourist route providing unit 8 can include a user information collecting module 81, a weather information collecting module 82, a time information collecting module 83, a stay information collecting module 84, a correlation analysis module 85, a recommended route providing module 86, and a store information display module 87.

The user information collection module 81 is configured to collect personal information of rental car users, and can collect information on age, gender, nationality, etc., for example.

The meteorological information collection module 82 is configured to collect meteorological information on a daily basis, and can collect meteorological information such as temperature, precipitation, wind speed, and humidity.

The time information collection module 83 is configured to collect information about the time of rental car use, and can be configured to collect information such as the day of the week and month.

The staying information collection module 84 is configured to collect information on the staying position of the rental car user, and is capable of collecting staying information by analyzing the driving route of the rental car and determining that the user has stayed at a position for a certain period of time or more.

The correlation analysis module 85 is configured to analyze the correlation between the rental car user's personal characteristic information, time information, and weather information and stay information. It places information about the rental car user's gender, age, and nationality, weather information about temperature, precipitation, wind speed, and humidity, and time information such as month and day of the week at the input end, places the probability of visiting each area of the tourist destination at the output end, and analyzes the correlation between the input end and the output end using machine learning, etc.

The recommended route providing module 86 is configured to collect locations frequently visited by rental car users using the correlation analyzed by the correlation analysis module 85 and provide a recommended route. It inputs information on the age, sex, and nationality of the user who intends to use the rental car, weather information at the time of using the rental car, and time information such as the day of the week and month into the correlation to calculate locations where the user is likely to visit, and collects these to provide a recommended route. Therefore, the recommended route providing module 86 can easily find and visit tourist spots frequently visited by other users without a separate search.

The store information display module 87 is configured to display information on the recommended store location provided by the store information providing unit 9 on the recommended route, and the location can be displayed via the rental car navigation or the user terminal 300. The store information providing unit 9 provides the tourist product provider with locations with high purchasing and preference levels for a specific product group according to the rental car user's travel route so that the tourist product provider can set up a mobile store, and the store information display module 87 displays the location information of the recommended mobile store on the rental car user's recommended route so that the tourist product can be easily purchased, increasing satisfaction with the purchase and also increasing sales profits of the tourist product provider. A detailed explanation of this will be given later.

The store information providing unit 9 is configured to analyze product purchase information according to the travel route of the rental car user and provide the recommended location of the mobile store to the tourism product provider, and analyzes product purchase information by location in the area where the rental car is used, and provides the location where the user purchases a lot of specific products and has a high preference as the recommended location of the mobile store. In addition, the store information providing unit 9 can recommend the location of the mobile store on the travel route recommended to the rental car user, thereby maximizing the sales rate of the specific product group at the mobile store. For this purpose, the store information providing unit 9 can include a purchase analysis module 91 and a location recommendation module 92.

The purchase analysis module 91 is configured to analyze purchase information by location in the area where the rental car is used, and analyzes information on purchases by location for a specific product group. The purchase analysis module 91 can collect card payment information, cash receipt information, etc. for product purchases from an external server and analyze purchase information, and calculates a purchase index according to the purchase ratio for a specific product group by location and the preference for a specific product group purchased at each location. For this purpose, the purchase analysis module 91 can include a location information input module 911, a purchase information analysis module 912, a preference information analysis module 913, and a purchase index calculation module 914.

The location information input module 911 is configured to input location information of each area in which a rental car can travel, and divides the area into units of a certain area or jurisdiction.

The purchase information analysis module 912 is configured to analyze purchase information for products at each location, and analyzes information such as card payments and cash receipts for each product group according to the type of product, allowing sales volume to be analyzed by location.

The preference information analysis module 913 is configured to analyze preference information for product groups by location, and analyzes online post-sale information for products purchased at each location and analyzes preferences through sentiment analysis, etc.

The purchasing index calculation module 914 is configured to calculate a purchasing index for a product group by location, and calculates a purchasing index indicating a purchasing ratio and preference through an analysis of purchase information and preference information. As an example, the purchasing index calculation module 914 may calculate the ratio of sales volume by location from the total sales volume of a region where rental cars are used for a specific product group, and may add up the preference level for each location to calculate a purchasing index. Therefore, a location with a high purchasing index can be determined as a region with a high purchasing probability and high preference for a specific product group, and such a location can be recommended as a location for a mobile store, thereby providing useful information that can increase sales rates to sellers of local tourism products, etc.

The location recommendation module 92 is configured to recommend the location of a mobile store in consideration of the recommended route of the rental car user, and recommends the location of the mobile store using the purchase index calculated by the purchase analysis module 91. The tourist route providing unit 8 provides the rental car user with recommended routes that the user frequently visits, and various routes are provided according to the user's personal characteristics. Therefore, the location recommendation module 92 reads the routes recommended through the tourist route providing unit 8, compares the purchase index by location for each route, and recommends the mobile store to the location with the highest purchase probability in consideration of the number of times each location is recommended and the purchase index. For this purpose, the location recommendation module 92 may include a product information input module 921, a recommended route loading module 922, a purchase index comparison module 923, and a recommended location providing module 924.

The product information input module 921 is configured to input information about a product group for which a mobile store location recommendation is desired, and inputs the type of product according to the product group analyzed by the purchase analysis module 91.

The recommended route loading module 922 is configured to load recommended route information for rental car users provided by the tourist route providing unit 8, and loads recommended route information provided to users who have reserved a rental car for a certain unit period, for example, one day.

The purchasing index comparison module 923 is configured to compare the purchasing index for each location of each route loaded by the recommended route loading module 922, and compares the purchasing index taking into account all of the multiple recommended routes during a unit period. In other words, the purchasing index comparison module 923 calculates the number of times each location is recommended by a recommended route, multiplies the calculated number of times by the purchasing index for each location, and compares the multiplied values by location.

The recommended location providing module 924 is configured to recommend the location of a mobile store based on the comparison result by the purchasing index comparison module 923, and recommends a location with a high purchasing index for a specific product group and a high probability of user visit as the location of a mobile store, thereby maximizing the product sales rate.

The network diagnostic unit 10 is configured to manage the network status between the rental car 200 and the operation server 100, and transmits a signal to the rental car 200 at regular time intervals to check for a response, and diagnoses the network status depending on the response. In particular, the network diagnostic unit 10 determines that a communication failure has occurred if a response signal is not received a certain number of times within a certain unit of time, and notifies the network of a decrease in performance if the response is not received for a certain range below the range that is determined to be a failure even if it is not determined to be a failure, so that an inspection can be performed. Also, if the non-reception state continues continuously within a certain unit of time, it determines that the network is completely disconnected, and promptly notifies the network of the decrease even before it is diagnosed as a failure, so that a prompt response can be taken. For this purpose, the network diagnostic unit 10 may include a failure detection unit 101, an abnormality diagnosis unit 102, and an emergency notification unit 103.

The fault detection unit 101 is configured to detect a network fault and diagnoses a network fault when the number of times a response signal is not received within a certain unit time exceeds a reference value. To this end, the fault detection unit 101 may include a confirmation signal transmission module 101a, a response signal reception module 101b, a non-reception frequency calculation module 101c, and a fault determination module 101d.

The confirmation signal transmission module 101a is configured to transmit a signal to each rental car 200 to confirm the network status, and transmits the confirmation signal at regular intervals.

The response signal receiving module 101b is configured to receive a response signal to the confirmation signal transmitted by the confirmation signal transmitting module 101a, and the rental car 200 automatically transmits a response signal to the confirmation signal, allowing the operation server 100 to confirm whether the network is operating normally.

The non-reception frequency calculation module 101c is configured to calculate the frequency at which a response signal is not received within a fixed unit time interval, and calculates the non-reception frequency as the number of times a response signal is not received relative to the number of confirmation signals sent within a fixed unit time.

The failure determination module 101d is configured to determine that the network is broken when the failure frequency calculated by the failure frequency calculation module 101c exceeds a reference value, and to notify the failure so that a prompt response can be taken. In addition, the failure determination module 101d does not determine a failure when a response signal is not received once, but determines that a failure has occurred when the failure frequency for a certain unit of time exceeds a reference value, thereby determining that a failure has occurred when a response signal is not received due to a temporary abnormality, and preventing the inefficiency of inspections, etc.

The abnormality diagnosis unit 102 is configured to determine that network performance has deteriorated and notify the network if the frequency of non-reception of a response signal is not at a level that would be detected as a failure but continues within a certain range below that level, thereby making it possible to diagnose not only network failures but also performance deterioration, thereby preventing communication problems caused by deterioration of network performance. To this end, the abnormality diagnosis unit 102 may include a danger range recognition module 102a, a duration count calculation module 102b, a reference count comparison module 102c, and an inspection notification transmission module 102d.

The danger zone recognition module 102a is configured to recognize when the frequency of non-reception of a response signal reaches a danger zone, where the danger zone refers to a certain zone below a reference value for the frequency of non-reception that is diagnosed as a failure.

The duration count calculation module 102b is configured to calculate the duration count when the frequency of non-reception of a response signal reaches a danger range, and calculates the number of times that a unit time during which the frequency of non-reception during a certain unit time reaches the danger range.

The reference number comparison module 102c is configured to compare the sustained number calculated by the sustained number calculation module 102b with a reference number, and sets a reference number that can be determined as a degradation in network performance so that the comparison can be performed.

The inspection notification transmission module 102d is configured to determine that the network performance has deteriorated if the sustained number of times exceeds the reference number as a result of the comparison by the reference number comparison module 102c, and notify the user of this so that a prompt inspection of the network can be performed.

The emergency notification unit 103 is configured to notify the user of a consecutive failure to receive a response signal even if the network state is not diagnosed as a failure or performance degradation, so that the user can take prompt action. If the response signal is not received consecutively within a unit time, the emergency notification unit 103 determines that the network has been completely disconnected, so that the user can take prompt action before the network is diagnosed as a failure. For this purpose, the emergency notification unit 103 may include a failure information receiving module 103a, a consecutive failure count calculation module 103b, and an emergency abnormality transmission module 103c.

The unanswered information receiving module 103a is configured to receive information regarding unreceived response signals, and determines whether unreceived response signals continue.

The consecutive number calculation module 103b is configured to calculate the number of consecutive times that a response signal has not been received, and checks whether or not the response signal has not been received consecutively within a certain unit of time.

The emergency abnormality transmission module 103c is configured to determine that the network connection has been completely cut off and transmit an emergency abnormality signal if the number of consecutive occurrences calculated by the consecutive occurrence count calculation module 103b exceeds a predetermined number, thereby quickly notifying the user of the abnormality even before a failure is detected, enabling a prompt response.

A rental car operation system according to another embodiment of the present invention will be described with reference to Figures 15 to 20. As in the first embodiment, the rental car operation system includes an operation server 100, a rental car, and a user terminal 300. The operation server 100 calculates the rental fee for the rental car 200 according to the rental car usage rate predicted based on big data, thereby determining a fair and reasonable price for both the rental car company and the user. Therefore, only the parts added to the operation server 100 will be described below.

The management server 100 communicates with the user terminal 300 via wired or wireless communication, concludes a usage contract for the rental car 200, and manages and provides various information regarding the rental car 200. In particular, the management server 100 determines rental fees for the rental cars 200 and provides them by categorizing them according to rental car companies. When a rental car 200 reservation is canceled, the management server 100 ensures the reliability of the management system and reduces damage to the user due to cancellation by reselling the rental car 200 product. In particular, the management server 100 determines the price of the rental car 200 using big data, thereby providing a reasonable price, and adjusts the price according to the reservation time for the rental car 200, thereby increasing the reservation rate and enabling efficient management. To this end, the management server 100 may include a price model determination unit 1', a price calculation unit 2', a price adjustment unit 3', a provider-specific provision unit 4', and a cancellation and resale unit 5'.

The price model determination unit 1' is configured to derive a correlation that can determine the rental price of a rental car (hereinafter referred to as "price"), and derives a correlation that can predict the rental car usage rate by analyzing big data. Therefore, the price model determination unit 1' can collect information on variables that affect the rental car usage rate and the rental car usage rate during a certain period of time to derive the correlation, and the price calculation unit 2' can determine the rental car price for a specific unit period using the derived correlation. As an example, the price model determination unit 1' can collect information on variables and usage rates on a daily basis to derive the correlation, and can update the correlation based on the information collected every day to increase the accuracy of the correlation. To this end, the price model determination unit 1' can include a variable information storage module 11', a usage rate information storage module 12', a correlation derivation module 13', and a correlation update module 14'.

The variable information storage module 11' is configured to collect and store information on variables that affect the rental car usage rate, and may include a vehicle type information storage module 111' for storing the type of vehicle, a time information storage module 112' for storing information on time such as days of the week and months, a season information storage module 113' for storing information on seasons such as peak season, off-season, semi-peak season, and consecutive holidays, a weather information storage module 114' for storing weather information such as temperature, precipitation, wind speed, and humidity, and an inflow rate storage module 115' for storing information on the inflow rate of tourists and the like who inflow into the area where the rental car 200 is used. Here, the inflow rate stored by the inflow rate storage module 115' is set as the ratio of the actual number of inflow passengers to the total number of passengers that can be transported by transportation means such as ships and airplanes that inflow into the area, and the information is collected and stored.

The usage rate information storage module 12' is configured to collect and store information regarding the usage rate of the rental cars 200, and the ratio of the number of actually used rental cars 200 to the total number of available rental cars 200 is set as the usage rate, which is collected and stored. For example, the usage rate can be calculated and stored on a daily basis.

The correlation derivation module 13' is configured to derive a correlation between the variables stored by the variable information storage module 11' and the rental car 200 usage rate stored by the usage information storage module 12', and derives the correlation using big data collected for a certain period of time for the variables and usage rate. The correlation derivation module 13' may analyze the correlation using various machine learning methods such as an artificial neural network, and may analyze the correlation between the variables and the usage rate on a daily basis. In addition, the correlation derivation module 13' may derive the correlation for each vehicle type, and may set input variable values according to the day of the week, month, and season, and input weather information such as precipitation, temperature, humidity, and wind speed and inflow rate as input variables to derive the correlation with the rental car usage rate.

The correlation update module 14' is configured to update the correlation derived by the correlation derivation module 13', and allows the correlation to be continuously corrected using variables and usage data collected after the correlation is derived. Therefore, the correlation update module 14' can improve the accuracy of the correlation over time.

The price calculation unit 2' is configured to calculate and determine the rental price for the rental car 200, and predicts the usage rate of the rental car 200 at a specific time point using the correlation derived by the price model determination unit 1', and calculates the price based on the predicted usage rate. In other words, the higher the predicted usage rate of the rental car at a specific time point, the greater the demand for rental cars, so the price calculation unit 2' can set a higher price as the predicted usage rate of the rental car is higher. In addition, the price calculation unit 2' can calculate and determine the price on a daily basis, and can calculate and provide the price by day according to the rental period selected by the user. To this end, the price calculation unit 2' can include a selection information receiving module 21', a variable information loading module 22', an expected usage rate calculation module 23', a price standard setting module 24', and a price calculation module 25'.

The selected information receiving module 21' is configured to receive information selected via the user terminal 300, and receives information such as the type and rental period of the rental car 200 desired by the user.

The variable information loading module 22' is configured to read input variables for predicting the rental car usage rate and calculating the price, and reads variables for the vehicle type and rental period selected by the user. Thus, the variable information loading module 22' predicts the usage rate of the rental car 200 for the vehicle type and rental period selected by the user, and determines the price based on the predicted usage rate. To this end, the variable information loading module 22' reads information about the vehicle type selected by the user through the vehicle type information loading module 221', reads time information such as the day of the week and month for the period during which the user intends to use the rental car 200 through the time information loading module 222', reads information about the season such as the peak season through the season information loading module 223', reads weather forecast information such as precipitation and temperature through the weather information loading module 224', and reads reservation rate information about transportation means such as ships and airplanes arriving in the area where the rental car 200 is used through the reservation rate information loading module 225'. At this time, the weather information loading module 224' can be configured to load weather forecast information from an external weather forecasting system, and the reservation rate information loading module 225' loads reservation rate information for the period during which the rental car 200 is desired to be used via a server of an operating entity that manages reservations for ships, airplanes, etc.

The expected usage rate calculation module 23' is configured to predict the expected usage rate of the rental car 200 for the period during which the user desires to use the rental car 200, and predicts the usage rate using the correlation derived by the price model determination unit 1'. Therefore, the expected usage rate calculation module 23' inputs the variables loaded by the variable information loading module 22' into the correlation by the price model determination unit 1' to calculate the expected usage rate of the rental car 200 for the period during which the rental car 200 is used.

The price standard setting module 24' is configured to set a standard for determining the price according to the usage rate of the rental car 200, and can divide the usage rate of the rental car 200 into multiple sections and set a price for each section, and can set a price according to the usage rate for each vehicle type.

The price calculation module 25' is configured to calculate and provide the price for the rental car 200 desired by the user, and provides the price for the vehicle type and period desired by the user. The price calculation module 25' can determine the price according to the standard set by the price standard setting module 24' based on the expected usage rate calculated by the expected usage rate calculation module 23', and can calculate and display the price for each date of the desired period of use.

The price adjustment unit 3' is configured to adjust the price according to the time when the user reserves the rental car, and can adjust the price calculated by the price calculation unit 2'. The price adjustment unit 3' can make the price lower the further in advance the rental car is reserved, and can also adjust the degree to which the price is adjusted according to the time, season, and reservation rate at the time when the rental car is to be used. Therefore, the price adjustment unit 3' can adjust the price according to the level of demand at the time when the rental car is used, and can make the price determination according to the time of reservation more rational and accurate. For this purpose, the price adjustment unit 3' can include a period index setting module 31', a weight setting module 32', an adjustment index calculation module 33', and a price change module 34'.

The period index setting module 31' is configured to set the degree to which the price is adjusted depending on the time remaining until the rental car usage period, and can be set so that the longer the remaining time, the lower the price is adjusted.

The weight setting module 32' is configured to set a weight for the period index set by the period index setting module 31', and can adjust the degree to which the price is adjusted according to the time, season, and reservation rate when the rental car 200 is used. Therefore, the weight setting module 32' can include a period setting module 321', a season setting module 322', and a reservation rate setting module 323', and the period setting module 321' can set the degree to which the price is adjusted according to the month and day of the week when the rental car is used, the season setting module 322' can set the degree of price adjustment according to the season type related to the busy season when the rental car is used, and the reservation rate setting module 323' can set the degree of price adjustment according to the reservation rate of the rental car. At this time, the period setting module 321' can reduce the degree of price adjustment for Friday, Saturday, Sunday, etc., the season setting module 322' in the busy season, and the reservation rate setting module 323' as the reservation rate increases. In addition, the reservation rate setting module 323' can set a weight to the extent to which the price is adjusted based on the ratio of the current reservation rate to the rental car usage rate predicted for the time when the rental car is used.

The adjustment index calculation module 33' is configured to set the degree to which the rental car price is finally adjusted, and can set the weight set by the weight setting module 32' to the period index set by the period index setting module 31' so that the final adjustment index is set.

The price change module 34' is configured to change the price calculated by the price calculation unit 2' and display it on the user terminal 300, and changes the price by reflecting the final adjustment index calculated by the adjustment index calculation module 33'.

The vendor-specific provision unit 4' is configured to classify and provide information such as the price of the rental car 200 by rental car vendor, and the calculation of the price of the rental car 200 can also be performed separately for each vendor and provided. In the case of this system, multiple rental car vendors can be registered and used, and the rental cars 200 owned by each vendor can be registered, and a usage contract for each rental car 200 can be concluded to use the rental car 200. Therefore, the vendor-specific provision unit 4' can separately display and provide the rental car 200 information of each rental car vendor, separately analyze the correlation with the rental car usage rate of each rental car vendor, and separately calculate and provide the price based on the correlation. In addition, the vendor-specific provision unit 4' can analyze the rating, description, etc. of the rental car for each vendor and provide the price reflecting the preference for each vendor. Therefore, the vendor-specific provision unit 4' allows a high price to be calculated for a vendor with a high usage rate under the same conditions for each vendor, and increases the rental car price of a vendor that is popular with users, making it possible to determine a reasonable price. Also, the more preferred a vendor is by users, the higher the price can be determined, which motivates the vendor to manage the quality of rental cars and thus makes it possible to improve the profitability of the vendor. To this end, the vendor-specific provision unit 4' can include a vendor-specific price display module 41', a rating information loading module 42', a later-described analysis module 43', a preference index calculation module 44', a preference standard setting module 45', and a price reflection module 46'.

The vendor-specific price display module 41' is configured to classify the rental car usage price for each rental car vendor and display it on the user terminal 300. It derives a correlation with the rental car usage rate for each vendor through the price model determination unit 1', calculates the price through the price calculation unit 2' and price adjustment unit 3', and displays it for each vendor.

The rating information loading module 42' is configured to read rating information for each rental car company, and can read rating information for the rental car entered through the user terminal 300 after using the rental car 200. The system can register a rating for the rental car 200 used by the user through the user terminal 300, and can store information related to this by company and read it through the rating information loading module 42'.

The follow-up analysis module 43' is configured to analyze rental car usage reviews for each rental car company, and can analyze positive and negative preferences for the rental car company. The follow-up analysis module 43' can analyze reviews created through the user terminal 300 and stored in the operation server 100, such as a rating, and can also collect follow-up information for rental car companies from various external media to analyze preferences.

The preference index calculation module 44' is configured to calculate a preference index indicating the degree of preference for a rental car company, and the preference index can be calculated based on the rating information loaded by the rating point information loading module 42' and the preference information described below analyzed by the analysis module 43'. As an example, the preference index calculation module 44' can calculate the preference index by adding up the average rating score and the score according to the preference described below.

The preference criterion setting module 45' is configured to set the degree of price adjustment according to the preference index, and can divide the preference index calculated by the preference index calculation module 44' into sections, and determine the degree of price adjustment according to each section. In this case, the preference criterion setting module 45' can set a standard such that the higher the preference for the rental car company, the higher the price will be.

The price reflection module 46' is configured to reflect the preference index in the price, and adjusts the price according to the preference index based on the criteria set by the preference criteria setting module 45'.

The cancellation and resale unit 5' is configured to resell the cancelled rental car reservation when the user cancels the rental car reservation, and resells the rental car reservation at a discounted price without immediately cancelling it. If frequent cancellations occur for rental car reservations made through this system, the rental car company's trust in this system may decline, and the user may also incur losses by having to pay a cancellation fee. Therefore, when a cancellation request is made through the user terminal 300, the cancellation and resale unit 5' first determines whether cancellation is possible, and if cancellation is possible, requests the user to resell the reservation on the condition that the cancellation fee is discounted, and if the user approves the resale, the rental car reservation is resold at a discounted price. As a result, the cancellation and resale unit 5' enables the system operator to maintain trust by minimizing cancellations of rental car reservations, and can reduce losses due to cancellations by discounting cancellation fees for users who cancel reservations, and can also increase the sales rate of cancelled reservations through discounted sales of rental car reservations. For this purpose, the cancellation and resale unit 5' may include a cancellation request receiving module 51', a sale availability determination module 52', a sales recommendation module 53', and a sales posting module 54'.

The cancellation request receiving module 51' is configured to receive cancellation information for a rental car reservation from a user, and receives the cancellation request information transmitted from the user terminal 300.

The sales possibility determination module 52' is configured to determine whether a rental car reservation that has been requested to be cancelled can be cancelled, and determines whether the rental car reservation can be resold. The sales possibility determination module 52' determines whether a rental car reservation can be sold by considering the rental car reservation rate at the time of rental car use, the remaining period, etc., and determines whether the rental car reservation can be resold by considering whether a predicted usage rate can be met when the remaining period until the rental car is used. To this end, the sales possibility determination module 52' may include a predicted usage rate receiving module 521', a reservation rate receiving module 522', a reservation progress rate calculation module 523', a period reflection module 524', and a yes/no determination module 525'.

The predicted usage rate receiving module 521' is configured to receive predicted usage rate information for the time of use of the rental car for which cancellation has been requested, and receives the predicted usage rate information calculated by the predicted usage rate calculation module 23'.

The reservation rate receiving module 522' is configured to receive current reservation rate information for the time of use of the rental car for which cancellation has been requested, and receives information on the ratio of the number of currently reserved rental cars to the total number of rental cars owned.

The reservation progress rate calculation module 523' is configured to calculate the reservation progress rate for the time of use of the rental car for which cancellation has been requested, and calculates the reservation progress rate by dividing the reservation rate received by the reservation rate receiving module 522' by the predicted usage rate received by the predicted usage rate receiving module 521'. Therefore, the reservation progress rate calculation module 523' can grasp how much the current reservation has progressed compared to the predicted usage rate.

The period reflection module 524' is configured to reflect the period remaining until the time of rental car use in the calculation of the reservation progress rate, and corrects the reservation progress rate calculated by the reservation progress rate calculation module 523' at a certain ratio, taking into account the period remaining from the time of the cancellation request until the time of rental car use.

The possibility determination module 525' is configured to determine whether or not the rental car for which a cancellation request has been made can be resold, and determines whether or not the rental car can be resold using reservation progress rate information that takes into account the remaining period by the period reflection module 524'. The possibility determination module 525' sets a certain reference value for determining whether or not resale is possible, and can determine that resale is possible if the reservation progress rate corrected by the period reflection module 524' exceeds the reference value. For example, it can determine that resale is possible if the expected reservation progress rate based on the rental car use date exceeds 90%.

The sales recommendation module 53' is configured to invite a user who cancels a rental car reservation to resell the car if the sales feasibility determination module 52' determines that the car rental reservation can be resold, and also provides information that a cancellation fee will be reduced if the car rental reservation is resold.

The sales posting module 54' is configured to allow the rental car reservation to be resold if the canceled user agrees to the resale of the rental car reservation, and displays the rental car at a discounted price for sale.

The applicant has described various embodiments of the present invention above, but these embodiments are merely one embodiment that realizes the technical idea of the present invention, and any modifications or alterations that realize the technical idea of the present invention should be construed as falling within the scope of the present invention.

REFERENCE SIGNS LIST 100 Management server 1 Vehicle information collection unit 2 Traffic information provision unit 3 Traffic information optimization unit 4 Impact monitoring unit 5 Oil cost calculation unit 6 Oil cost discount unit 7 Fine calculation unit 8 Tourist route provision unit 9 Shop information provision unit 10 Network diagnosis unit 1' Price model determination unit 2' Price calculation unit 3' Price adjustment unit 4' Business-specific provision unit 5' Cancellation and resale unit 200 Rental car 300 User terminal

Claims (12)

A rental car service in which a user rents and uses a vehicle for a certain period of time, and then returns the vehicle and measures and transmits operating information about the vehicle;
a user terminal for searching for the rental cars, selecting a rental car to be used, and receiving information regarding the rental car;
an operation server that communicates with the user terminal and the rental car, allows a rental car use contract to be concluded, and receives operation information measured by the rental car;
The operating server analyzes driving information measured by a rental car to provide information required for driving the rental car,
The administration server is
A vehicle information collection unit that collects rental car operation information, and a traffic information provision unit that analyzes and provides traffic information using the collected operation information,
The traffic information providing unit,
The system includes a movement information collection module for collecting movement information of rental cars for each section of a road, a movement speed calculation module for calculating the movement speed of the rental car moving in each section, a speed information refining module for removing speed information of rental cars having excessively low or high movement speeds, an average speed calculation module for calculating an average speed of the rental car for each section, a congestion degree display module for calculating and displaying a congestion degree according to the calculated average speed, and an automatic route reflection module for automatically reflecting the congestion degree in a movement route guided through navigation and updating the route,
The traffic information providing unit,
A filtering module is included to remove rental car information that may be a noise in calculating the travel speed for each section,
The filtering module includes:
This rental car operating system is characterized by including a start time discrimination module which removes information on rental cars which have been turned off for a certain period of time or more, a stop time discrimination module which removes information on rental cars which have been stopped for a certain period of time or more even if the operation is turned on, and a travel route discrimination module which removes information on rental cars which have a route which deviates from the route of each section. The administration server is
a traffic information optimizing unit that optimizes traffic information provided by an external system using the traffic information analyzed by the traffic information providing unit;
The traffic information optimization unit
10. The system according to claim 1, further comprising: an external traffic information collecting module for collecting external traffic information; a traffic information comparing module for comparing the external traffic information with a result analyzed by the traffic information providing unit; an image determining module for checking whether an accident has occurred based on a vehicle image when the external traffic information and the traffic information analyzed by the traffic information providing unit differ by a certain degree or more; an abnormality information generating module for generating abnormality information in the traffic information when an accident cannot be confirmed from the image; an abnormality count calculating module for calculating the number of times the abnormality information occurs; and an abnormality information providing module for providing traffic information by a rental car to be reflected in the external traffic information system when the number of times the abnormality information occurs for a certain period of time or more exceeds a reference value .
The rental car operation system described in. The administration server is
An impact monitoring unit that monitors an impact to a rental car vehicle,
The impact monitoring unit is
2. The rental car operating system of claim 1, further comprising: an impact information receiving module that receives vibration information of a certain level or more measured in the rental car as impact information; and an accident judgment module that judges an impact occurring in the rental car to be an accident and notifies the driver if the impact exceeds the certain level. The impact monitoring unit is
It includes a danger recognition module that detects and takes measures when a rental car is hit within a certain range of impact that is deemed an accident,
The danger perception module includes:
The rental car operating system of claim 3, further comprising: a dangerous impact detection module that detects dangerous impacts within a certain range below the impact that is determined to be an accident; a confirmation signal transmission module that transmits a signal to the rental car to confirm a dangerous impact when the dangerous impact is detected; a response signal confirmation module that recognizes a dangerous situation when no response to the confirmation signal is received within a certain time ; and an emergency dispatch instruction module that instructs an emergency dispatch when the dangerous situation is recognized. The impact monitoring unit is
If the impact of the rental car is not recognized as a dangerous impact but continues within a certain range, the abnormality confirmation module determines that the rental car is abnormal and notifies the user of the abnormality,
The anomaly confirmation module includes:
5. The rental car operating system of claim 4, further comprising: an impact information storage module for storing information about a certain range of impacts below a dangerous impact; a repetition frequency calculation module for calculating the frequency at which impacts within the certain range are repeated; a reference value comparison module for comparing the calculated frequency with a reference value; a consecutive number calculation module for calculating the number of consecutive impacts with a frequency exceeding the reference value; and an abnormality notification module for notifying of an abnormality in the rental car vehicle if the consecutive number exceeds a predetermined number. The administration server is
An oil cost calculation unit automatically calculates the oil cost for a rental car and bills the user for the cost,
The oil cost calculation unit includes:
The system includes a correlation analysis module that analyzes the correlation between the operating state and fuel consumption of each rental car, an operation information receiving module that receives operation information during the rental period of the rental car for which an oil fee is to be claimed, an oil fee calculation module that inputs the operation information into the correlation analyzed by the correlation analysis module to calculate the oil fee, and an automatic oil fee claim module that automatically claims the calculated oil fee to a user when the rental car is returned,
The correlation analysis module includes:
2. The rental car operating system of claim 1, further comprising: an operation information loading module that reads rental car start information, speed information, and acceleration/deceleration information; a refueling information loading module that reads refueling information for the rental car; and a correlation derivation module that derives the correlation between the operation information and fuel consumption for each rental car. The administration server is
An oil cost discount unit that allows a discount on oil costs to be given according to the unit price of refueling by a rental car user,
The oil cost discount department
7. The rental car operating system of claim 6, further comprising: a refueling unit price loading module that reads refueling unit price information from refueling information of a user's refueling; a unit price information collecting module that collects oil unit price information in the area where the rental car is used at the time the user refuels; a standard unit price setting module that sets the average value of the oil unit prices collected by the unit price information collecting module as a standard unit price; a savings ratio calculation module that calculates an oil cost savings ratio based on the difference between the user's refueling unit price and the standard unit price; a refueling point calculation module that calculates refueling points by multiplying the savings ratio by the amount of refueling by the user; and an automatic oil cost deduction module that automatically deducts the calculated refueling points from the oil cost paid by the user to reflect the result. The administration server is
A tourist route providing unit that analyzes the travel route of a rental car user and recommends a tourist route,
The tourist route providing unit,
The rental car operating system of claim 1, characterized in that it includes a user information collection module that collects information regarding the age, gender, and nationality of the rental car user, a weather information collection module that collects weather information at the time of rental car use, a timing information collection module that collects information regarding the time of rental car use, a stay information collection module that collects information on the rental car user's stay location based on the rental car's driving route, a correlation analysis module that analyzes the correlation between user, weather, timing information and the stay location, and a recommended route providing module that provides the rental car user with a recommended sightseeing route based on the analyzed correlation. The administration server is
A store information providing unit that analyzes product purchase information according to the travel route of a rental car user and recommends the location of a mobile store for tourists,
The store information providing unit,
A purchase analysis module that analyzes purchase information of products by region, and a location recommendation module that recommends and provides a location of a mobile store based on a result of the analysis by the purchase analysis module,
The purchasing analysis module includes:
The system includes a location information input module for inputting location information of an area where a rental car is used, a purchase information analysis module for analyzing purchase information for a specific product group at each location, a preference information analysis module for analyzing preference information for the specific product group purchased at each location, and a purchase index calculation module for calculating a purchase index based on the purchase level and preference level for the specific product group at each location according to a travel route,
The location recommendation module:
9. The rental car operating system of claim 8, further comprising: a product information input module for inputting information on a product group for which a mobile store is to be installed; a recommended route loading module for loading information on a travel route recommended to a rental car user by the tourist route providing unit; a purchasing index comparison module for comparing purchasing indexes by positions of the recommended route during a unit period; and a recommended position providing module for recommending the position of the mobile store at a position with a high purchasing index, taking into account the number of visits by positions according to the recommended route. The administration server is
a network diagnostic unit for diagnosing communication abnormalities with the rental car by transmitting a confirmation signal to the rental car at regular time intervals;
The network diagnostic unit includes:
a failure detection unit that determines that a communication failure has occurred when a response to a confirmation signal is not received at a certain frequency or more;
The failure detection unit is
2. The rental car operating system of claim 1, further comprising: a confirmation signal transmitting module that transmits a confirmation signal to the rental car at regular time intervals; a response signal receiving module that receives a response signal to the confirmation signal; a non-reception frequency calculating module that calculates the frequency at which the response signal is not received at regular unit time intervals; and a failure determining module that determines and notifies of a failure if the non-reception frequency exceeds a reference value. The network diagnostic unit includes:
and an abnormality diagnosis unit for determining that network performance has deteriorated and notifying the same when the frequency of non-reception of a response signal continues within a certain range even if it is not detected as a failure,
The abnormality diagnosis unit is
The rental car operating system according to claim 10, further comprising: a danger range recognition module for recognizing when the frequency of non-reception of a response signal reaches a danger range below the frequency at which a failure is detected; a duration count calculation module for calculating the number of times the non-reception frequency continues in the danger range; a reference value comparison module for comparing the duration count with a reference value; and an inspection notification instruction module for determining that performance has deteriorated and notifying the same if the duration count exceeds the reference value . The network diagnostic unit includes:
an emergency notification unit for detecting and notifying an emergency abnormality in the network even before the failure detection unit or the abnormality diagnosis unit diagnoses a failure or performance degradation;
The emergency notification unit,
12. The rental car operating system according to claim 11, further comprising: a no-response information receiving module for receiving no-response information; a consecutive number calculation module for calculating the number of consecutive no-responses if the no-response occurs consecutively; and an emergency abnormality transmission module for determining that an emergency abnormality has occurred and notifying the user if the consecutive number of no-responses exceeds a predetermined value.