JP4277554B2 - Time required estimation device - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a required time estimating device that estimates a required time required to pass a road link that is not a target of road traffic information.
[0002]
[Prior art]
Currently, for major roads, for example, VICS (registered trademark) (Vehicle Information & Communication System), such as road traffic information such as the congestion status of the road and the time required for a specific road section. Is provided. Since the road traffic information provided by such a road traffic information providing system is based on data from sensors such as vehicle detection sensors installed on the road, only information limited to the road where the sensor is installed is provided. Has been.
[0003]
Therefore, in such a road traffic information providing system, since the required time for all roads is not provided by the road traffic information, for example, using the road traffic information provided in this way, In a navigation device or the like that searches for a route to a destination, when searching for a route that can arrive at the destination in the shortest time, if the road traffic information does not provide information on the required time, the route Cannot calculate the required time.
[0004]
Therefore, it is desired to propose a technique for estimating the required time even for roads for which road traffic information is not provided. For example, in Patent Document 1 and Patent Document 2, information on required time is provided by road traffic information. Several methods have been proposed for estimating the time required for roads that do not exist.
[0005]
Patent Document 1 discloses a technique for estimating a traffic flow in a lane that does not have a sensor or an arbitrary point with respect to a road having a plurality of sensors that obtain vehicle travel information on the road. This technique simulates traffic flow across the road and adjusts the traffic flow simulation parameters so that the resulting estimate of where the sensor is located matches the data from the actual sensor Is.
[0006]
Patent Document 2 discloses a technique for directly collecting information such as the position of a vehicle from a vehicle traveling on the road and estimating the time required for the road on which the vehicle traveled.
[0007]
[Patent Document 1]
Japanese Patent Laid-Open No. 2000-222669 (pages 2 to 8, FIGS. 1 to 9)
[Patent Document 2]
JP 2003-16570 A (2nd to 9th pages, FIGS. 1 to 11)
[0008]
[Problems to be solved by the invention]
However, the technology disclosed in Patent Document 1 is a technique for estimating a lane where a sensor is not installed or an arbitrary position on the road based on the data of the sensor with respect to a road where the sensor is installed. In other words, it is a data complementing technique for “a road portion without sensor data by a sensor” in a traffic information target road. Therefore, it cannot be applied to roads where the sensor is not originally installed, that is, “roads for which required time information is not provided by road traffic information” as described above. The disclosed technique according to Patent Document 1 has a problem that it is not possible to estimate the required time regarding “a road where the required time information is not provided by road traffic information”.
[0009]
In addition, since the disclosed technique according to Patent Document 2 requires a device that collects data from a running vehicle, when data cannot be collected from a sufficient number of vehicles, “ It becomes difficult to accurately estimate the time required for the “road for which information is not provided”, and there is a practical problem.
[0010]
The present invention has been made in order to solve the above-described problems, and an object of the present invention is to provide a time required for easily estimating a time required for a road for which no information on the time required is provided by road traffic information. It is to implement an estimation device.
[0011]
[Means for solving the problems and functions and effects of the invention]
  In order to achieve the above object, in the travel time estimation apparatus according to claim 1, traffic information acquisition means for acquiring traffic information including travel time data of a traffic information target road link which is a target of road traffic information from outside, Based on the traffic information acquired by the traffic information acquisition means, a required time interpolation means for interpolating a required time of a traffic information non-target road link that is not a target of road traffic information, and the traffic information acquisition means Based on the obtained traffic information and the required time interpolated by the required time interpolation means, PlaceTime estimation means for estimating the time required;The required time interpolation means includes predetermined area specifying means for specifying a road network by dividing the road network into predetermined areas, and the length of each road link and the required time data for the traffic information target road link in the predetermined area. The average vehicle speed of each road link is calculated from the above, the calculated average vehicle speed is classified by a predetermined value, the total distance of the road links included in each classification is calculated, and the total distance of the road links for each classification is calculated. The traffic information target link congestion degree classifying means for calculating the ratio, and the traffic information non-target road link in the predetermined area, so as to maintain the ratio of the total distance to the road link in the predetermined area, Traffic information non-target link required time estimating means for assigning the average vehicle speed and estimating the required time of the road link from the assigned average vehicle speed and the length of the road link;It is a technical feature to have.
[0012]
Note that the “traffic information target road link” is a requirement of the road link corresponding to the road based on the vehicle travel information output from the vehicle travel information detecting means that is installed on the road and can detect the travel information of the vehicle. Time is calculated, and the required time is a road link available as “road traffic information” (hereinafter the same). More specifically, for example, the road link can directly calculate the required time of the road from sensor data such as a traffic flow measurement sensor as an infrastructure, and can use the calculated value. The “traffic information non-target road link” is a road link that does not have vehicle travel information detecting means that can detect the travel information of the vehicle, and the road time required for the road link cannot be obtained as “road traffic information”. It means a link (the same applies hereinafter). More specifically, for example, a road link in which a traffic flow sensor or the like as an infrastructure is not installed, and the required time of the road cannot be directly calculated from the sensor data of the road.
[0013]
  In the first aspect of the invention, the traffic information including the required time data of the traffic information target road link which is the target of the road traffic information is acquired from the outside by the traffic information acquisition means, and based on the acquired traffic information The required time of the traffic information non-target road link that is not the target of the road traffic information is interpolated by the required time interpolation means. Based on the traffic information acquired by the traffic information acquisition means and the required time interpolated by the required time interpolation means, the required time between the predetermined positions including the traffic information non-target road link is estimated by the required time estimation means. .The required time interpolation means includes a predetermined area specifying means, a traffic information target link congestion degree classifying means, and a traffic information non-target link required time estimating means. When the road network is specified by dividing it into predetermined areas, the traffic information in the predetermined area is determined. For the target road link, the average vehicle speed of each road link is calculated from the length and required time data of each road link, the calculated average vehicle speed is classified by a predetermined value, and the total distance of the road links included in each classification And the ratio of the total distance of the road links for each classification is calculated. In addition, for the traffic information non-target road links in the predetermined area, the average vehicle speed is assigned so as to maintain the ratio of the total distance to all road links in the predetermined area, and the assigned average vehicle speed and the length of the road link are assigned. To estimate the time required for the road link.As a result, it is possible to obtain the required time of the road for which the required time information is not provided by the road traffic information by such interpolation. Therefore, a device for collecting data from other traveling vehicles is provided separately. The required time can also be estimated for the road. Therefore, it is possible to easily estimate the required time for a road for which the required time information is not provided by the road traffic information.
[0018]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment of a required time estimation device of the present invention will be described with reference to the drawings.
First, the configuration of the information center 20 will be described with reference to FIG.
As shown in FIG. 1, the information center 20 mainly includes a CPU 21, a memory 22, a map / road link DB 23a, a traffic demand prediction DB 23b, a communication control device (hereinafter referred to as “CCU”) 25, and the like. “DB” is an abbreviation for database, and hereinafter, the database is referred to as “DB”.
[0019]
The CPU 21 is a central processing unit that controls the information center 20, and is connected to a memory 22, a map / road link DB 23a, a traffic demand prediction DB 23b, a CCU 25, and the like via a system bus. The CPU 21 includes a control unit, an arithmetic logic unit, and the like, and is configured with the memory 22 as, for example, a personal computer or a workstation.
[0020]
The memory 22 is a semiconductor memory that constitutes a main storage space used by the CPU 21 and is connected to the CPU 21 via a data bus. In addition to the system program 22a for controlling the CPU 21, the memory 22 stores various control programs 22b to 22g. The CPU 21 reads these computer programs from the memory 22 and executes them sequentially.
[0021]
The map / road link DB 23a and the traffic demand prediction DB 23b are a hard disk device, a compact disk device, a digital versatile disk device, or the like constituting an auxiliary storage space used by the CPU 21, and are connected to the CPU 21 via a data bus.
[0022]
The map / road link DB 23a stores and accumulates road map data from the past used to the latest and road link data associated with the road map data. For this road link data, the traffic information acquired by the traffic information acquisition program 22c, which will be described later, from the traffic information center 100 such as the VICS center, for example, the required time data of the traffic information target road link and the traffic interpolated by the required time interpolation program 22d. Interpolation required time data of information non-target road link is included.
[0023]
The CCU 25 is a communication control device that controls communication with the outside of the information center 20. For example, the CCU 25 is a data controller between the electric information communication network 105 such as the Internet connected via a communication line or the telephone line switching center 110 and the CPU 21. It is responsible for communication control related to exchanges, and performs data communication with the navigation device 50 mounted on the vehicle via the telephone circuit switching center 110 or the latest acquisition from the traffic information center 100 via the electric information communication network 105. It has a function to obtain road traffic information such as required time data. Although not shown in FIG. 1, the information center 20 is provided with an input device for instructing operation of the information center 20, an output device for displaying an operation state, and the like.
[0024]
On the other hand, the navigation device 50 facing the information center 20 is mainly composed of a control device 52, an output device 53, an input device 54, a position detection device 56, a wireless communication device 58, etc., as in the information center 20. .
[0025]
The control device 52 includes an unillustrated CPU, memory, and the like, like the CPU 21 and memory 22 of the information center 20. In this memory, the shortest route in terms of time is uniquely searched and guided based on the required time data received from the information center 20 via the wireless communication device 58, the search conditions input via the input device 54, etc. A possible route search / guidance program 52a, a traffic information acquisition program 52b that can acquire traffic information from the information center 20 via the wireless communication device 58, and the like are stored.
[0026]
The output device 53 is connected to the control device 52 via an input / output interface (not shown), and displays route guidance information from the current location to the destination, estimated time required to reach the destination, etc. It is a device that can output by voice. When the route guidance is performed using images, the output device 53 is composed of, for example, a liquid crystal display or a CRT display, and is provided on the operation panel of the navigation device 50. When route guidance is performed by voice, it is composed of a voice synthesizer, sound generator, amplifier, speaker, and the like. Some of these are configured to provide route guidance and the like using both images and sound.
[0027]
The input device 54 is an information input device provided on the operation panel of the navigation device 50 and is connected to the control device 52 via an input / output interface (not shown). The input device 54 is used for inputting information on a destination or the like that the user desires to search for a route. The input device 54 has a configuration in which a predetermined number of push switches are arranged, or a touch panel provided on the surface of the output device 153. Some of them are of the formula type, or are constituted by a microphone, a voice recognition device, etc. that recognizes the voice of the user and converts it into input information to the navigation device 50.
[0028]
The position detection device 56 is for detecting the current position of the vehicle on which the navigation device 50 is mounted and outputting current position data. For example, the position detection device 56 receives signals from a plurality of GPS satellites to determine the absolute position of the user. It consists of a GPS sensor that measures and a gyro sensor that measures the relative position of the vehicle. The gyro sensor is used for autonomous navigation, and the relative position measured by the gyro sensor is obtained in a tunnel where the GPS receiver cannot receive radio waves from the satellite, or is measured by the GPS receiver. This is used to correct the positioning error of the absolute position.
[0029]
The wireless communication device 58 is a wireless communication device for transmitting and receiving data to and from the information center 20 via a wireless communication line, and is connected to the control device 52 via an input / output interface (not shown). For example, a wireless communication system such as a mobile phone or PHS is used.
[0030]
Here, an outline of the input program 22b, the traffic information acquisition program 22c, the required time interpolation program 22d, the required time estimation program 22e, the traffic demand prediction program 22f, and the output program 22g stored in the memory 22 of the information center 20 will be described. To do.
[0031]
The input program 22b is a function for reading road link data and the like to be interpolated by the required time interpolation program 22d from the map / road link DB 23a, and for a user of the information center 20 (occupant of the vehicle 70) to use the navigation function. It has a function of accepting requests for various information such as necessary road traffic information via the CCU 25 and delivering the requests to other programs and processes.
[0032]
The traffic information acquisition program 22c has a function of acquiring road traffic information including a required time from the traffic information center 100 (for example, VICS center) via the CCU 25 connected to the electrical information communication network 105 such as the Internet. As a result, road traffic information that changes every moment is acquired in real time. The traffic information acquisition program 22c corresponds to “traffic information acquisition means” described in the claims.
[0033]
  The required time interpolation program 22d has a function of interpolating the required time of the traffic information non-target road link that is not the target of the road traffic information based on the road traffic information acquired by the traffic information acquisition program 22c, as will be described later. It is what you have. In addition, as traffic information non-target road link, for example, the required time of the road is directly calculated from sensor data such as traffic flow measurement sensor as infrastructureCan't, Its calculated value can be usedAbsentA road link is mentioned. The required time interpolation program 22d corresponds to “required time interpolation means” described in the claims.
[0034]
The required time estimation program 22e is based on the road traffic information acquired by the traffic information acquisition program 22c and the required time interpolated by the required time interpolation program 22d, and the required time between predetermined positions including the traffic information non-target road link. It has the function to estimate. The required time estimation program 22e corresponds to “required time estimation means” described in the claims.
[0035]
The traffic demand prediction program 22f has a function of predicting traffic demand by time zone for each road link according to a predetermined procedure to be described later, and data predicted thereby is stored and accumulated in the traffic demand prediction DB 23b.
[0036]
The output program 22g has a function of writing the interpolation required time interpolated by the required time interpolation program 22d in the map / road link DB 23a, and a result processed in response to a request from the navigation device 50 received by the input program 22b. It has a function to output to the navigation device 50 via the CCU 25 as various information such as traffic information.
[0037]
Next, the flow of the required route time processing performed by the information center 20 will be described with reference to FIGS. The route required time estimation process described below is executed by the above-described input program 22b, traffic information acquisition program 22c, required time interpolation program 22d, required time estimation program 22e, traffic demand prediction program 22f, and output program 22g. The system program 22a is started from the main routine (DB creation / update control unit) at regular time intervals. In FIG. 13, the DB creation / update control unit 22 a ′ is illustrated.
[0038]
As shown in FIG. 2, in the route required time estimation process, after a predetermined initialization process, a process of acquiring link information is first performed in step S101. This process is performed by the input program 22b, and performs a process of reading the road link data to be subjected to the route required time estimation process from the map / road link DB 23a. The road link data read in step S101 is, for example, link coordinate information, link length, link type, and the like. FIG. 3 shows an example of information (cost information) related to the cost of the road link created by a predetermined calculation process (cost creation unit) based on the information about the road link, etc., and passed through a memory or a file. It is shown. In this cost information data structure, the link information includes a link ID and travel time information, and the travel time information includes forward travel time and reverse travel time.
[0039]
Note that the “travel time” shown in the data structure of FIG. 3 is a required time. For example, when the data corresponds to the traffic information target road link data that is the target of the road traffic information, the road The data related to the required time when traveling in the forward direction is stored in the “travel time (order) item”, and the data related to the required time when traveling in the reverse direction is “travel time ( It is stored in “Reverse items”. In addition, when it corresponds to traffic information target road link data that is not subject to road traffic information, NULL data indicating that the corresponding data does not exist is “travel time (order) item” and “travel time (reverse) ) Item ".
[0040]
In the subsequent step S103, a traffic information acquisition process is performed. This processing is performed by the traffic information acquisition program 22c, and traffic information including required time data of the traffic information target road link is obtained from the outside of the information center 20, for example, the traffic information center 100 (VICS center or the like) via the CCU 25. Perform the acquisition process.
[0041]
In the next step S105, required time interpolation processing is performed. This process is performed by the required time interpolation program 22d. Specifically, for example, a required time interpolation process (part 1) by a subroutine shown in FIG. 4 is performed. Here, details of the required time interpolation processing (part 1) will be described with reference to FIGS.
[0042]
  As shown in FIG. 4, in the required time interpolation process (part 1), first, in step S201, a process of dividing the link information into predetermined areas is performed. This process specifies the road network by dividing it into predetermined areas, and corresponds to “predetermined area specifying means” recited in the claims. Specifically, for example, as shown in FIG. 5, based on the road map data read from the map / road link DB 23a, a process of creating a set of road link information for each section called, for example, a secondary mesh is performed. In the example shown in FIG. 5, the road map data in Aichi Prefecture is divided into 21 sections by setting and dividing into one section and about 10 km square, and X3 when expressed in XY coordinates.Y3The predetermined area α corresponding to the section is specified. In the specified area α thus identified, traffic information target road links (thick solid lines shown in the lower frame of FIG. 5) and traffic information non-target road links (thin solid lines shown in the lower frame of FIG. 5) are present. The intermingling is shown in FIG.
[0043]
In the next step S203, processing for calculating a congestion ratio from the traffic information target road link is performed. In this process, the average vehicle speed of each road link is calculated from the length of each road link and the required time data for the traffic information target road link in the predetermined area specified in step S201, and the calculated average vehicle speed is set to a predetermined value. Classify by value, calculate the total distance of road links included in each classification, and calculate the ratio of the total distance of road links for each classification. This corresponds to “degree classification means”. Specifically, for example, in the case of the predetermined area α shown in FIG. 5, as shown in FIG. 6A, the respective congestion degrees are calculated for the traffic information target road links existing in the predetermined area α, Next, a ratio (total distance ratio) in the predetermined area α is obtained for each calculated degree of congestion.
[0044]
The degree of congestion here refers to, for example, calculating the average vehicle speed from the length of the road link and the required time (travel time), and the type of the road link (for example, general road, urban expressway, intercity expressway, etc.) For example, it is defined as shown in the chart shown in FIG. 6 (B). Note that the length and type of such road links are stored in the map / road link DB 23a along with the road map data.
[0045]
That is, in the example of the definition shown in FIG. 6B, in the case of a general road, “congestion” occurs when the average vehicle speed is 5 km / h or less, and “congestion” occurs when the average vehicle speed exceeds 5 km / h and is 15 km / h or less. When it exceeds 15 km / h, it is defined as “normal”. In the case of urban expressways, “congestion” occurs when the average vehicle speed is 10 km / h or less, “congestion” when the vehicle speed exceeds 10 km / h and 30 km / h or less, and “normal” when vehicle speed exceeds 30 km / h. Is defined. Furthermore, in the case of intercity highways, “congestion” occurs when the average vehicle speed is 20 km / h or less, “congestion” occurs when the vehicle speed exceeds 20 km / h and is 50 km / h or less, and “normal” occurs when it exceeds 50 km / h. Is defined. In addition to the case where the degree of congestion is divided into three levels of “congestion”, “congestion”, and “normal” as described above, for example, the congestion level may be further divided into 10 levels from level 1 to level 10. , And may be divided into 11 or more stages. This makes it possible to increase the accuracy of the degree of congestion.
[0046]
When the congestion degree is calculated for each traffic information target road link in this way, the ratio within the predetermined area α is obtained for each calculated congestion degree. For example, in the example of the predetermined area α shown in FIG. 6 (A), when the total link length of all traffic information target road links in the predetermined area α is 100%, this is indicated by a dotted line. The ratio of road links corresponding to “congestion” is 25%, the ratio of road links corresponding to “congestion” represented by a one-dot chain line is 10%, and further corresponds to “normal” represented by a broken line. The percentage of road links is 65%.
[0047]
The process which acquires demand prediction data by step S205 is performed. That is, the process which acquires the demand predicted value about each of traffic information object road link from traffic demand prediction DB23b by each link ID as a key is performed.
[0048]
Here, the traffic demand prediction DB 23b will be described with reference to FIG.
Each data is stored in the traffic demand prediction DB 23b in accordance with a data table as shown in FIG. 7A. This data table is, for example, a town page DB or a traffic volume DB as shown in FIG. 7B. Based on the traffic demand prediction program 22f. Specifically, for example, the following procedure is performed. The town page DB is provided by NTT Number Information Co., Ltd., and “town page” is a registered trademark.
[0049]
First, a plurality of ODs (abbreviations for departure and destination, the same applies hereinafter) are selected from the town page DB according to parameters relating to the movement of people such as morning, noon, night, weekdays, and holidays. Next, the route search is tried several times by the number of ODs. Then, the number of passes is counted for each road link (by forward direction and by reverse direction). Here, the OD is selected according to the purpose of travel, for example, in the case of commuting, the departure place is a cleaning shop (facility correlated with population) and the destination is a company (building). Further, in the case of entertainment, the database is extracted from the genre of DB such as that the departure place is a cleaning shop and the destination is a popular tourist destination.
[0050]
The extraction of OD can be classified as follows for the purpose of moving people, for example. These include attendance and attendance at school, business A (no cargo), business B (with cargo), private affairs / entertainment, return to work, return home, commercial passengers, commercial trucks, etc. First, an OD town page genre is set for each movement purpose. For example, when going to work or attending school, if the departure place is the home of each household and the destination is a company, the genre of the home is a facility that correlates with the population, such as a laundry shop, the genre of the company is a building. To do. Then, based on the inflow / outflow data for each time zone, the movement purpose data for each time zone, and the OD town page genre for each movement purpose, OD coordinate information for each movement purpose is appropriately extracted from the town page DB. In addition, the inflow / outflow data by time zone and the movement purpose data by time zone in a certain region include, for example, those created based on the road traffic census implemented by the Ministry of Land, Infrastructure, Transport and Tourism (Fig. 7 (B) The quantity DB corresponds to this).
[0051]
In subsequent step S207, processing for setting a congestion threshold for the demand forecast value is performed. That is, processing for obtaining a congestion threshold value is performed so as to be equal to the congestion degree ratio calculated in step S203. Specifically, for example, in the example of the predetermined region α shown in FIG. 6A, it is assumed that the demand forecast value is obtained as shown in FIG. If a graph is created with the horizontal axis as the demand forecast value (traffic demand) and the total distance of the road links corresponding to this demand forecast value as the vertical axis, a characteristic diagram as shown in Fig. 8 (B) is obtained. The regions K, L, and M according to this characteristic diagram are divided by an area ratio that is equal to the congestion degree ratio obtained in S203. The boundary between the region K and the region L (the thick broken line on the left side in FIG. 8B) is a congestion threshold that separates “normal” and “congested”. The boundary between the region L and the region M (the thick broken line on the right side in FIG. 8B) is a congestion threshold that separates “congestion” from “congestion”.
[0052]
In the example of the characteristic diagram shown in FIG. 8B, the percentage of congestion obtained in step S203 is 25% for “congestion”, 10% for “congestion”, and 65% for “normal”. Accordingly, the region K is set to 65%, the region L is 10%, and the region M is 25% corresponding to each. In addition, the demand forecast value shown in FIG. 8 (A) is normalized so that the maximum value is 100, and the horizontal axis of the graph shown in FIG. 8 (B) is also set to 100 as the maximum value. ing.
[0053]
In step S209, processing for estimating the congestion status of the traffic information non-target road link is performed. This process includes a process for estimating “congestion”, “congestion”, or “normal” for each of the traffic information non-target road links existing in the predetermined area based on the congestion threshold set in step S207. Done. For example, in the example of the predetermined region α shown in FIG. 6 (A), if the traffic is distributed to “congestion”, “congestion”, and “normal” according to the congestion threshold set in step S207, the upper left side of FIG. It is estimated like “the congestion situation of each road link by the demand forecast value”. In the “congestion status of each road link based on the demand prediction value”, “congestion” is represented by a dotted line, “congestion” is represented by a one-dot chain line, and “normal” is represented by a broken line. The thickness of each line represents “traffic information target road link” (thick line) and “traffic information non-target road link” (thin line).
[0054]
On the other hand, as shown in FIG. 6 (A), the upper right side of FIG. 9 (A) shows the congestion status of each road link based on traffic information, that is, the degree of congestion for each traffic information target road link. Has been. Here, there are three road links surrounded by an ellipse in the predetermined area α of the “congestion status of each road link by traffic information”. The corresponding road link of “the congestion status of each road link” indicates a road link whose degree of congestion does not match. In this way, when “the congestion status of each road link based on the demand forecast value” is estimated to be different from the “the congestion status of each road link based on the traffic information”, priority is given to the traffic information that is actual data. Therefore, for the road link having the difference, a process of overwriting the congestion degree due to “the congestion state of each road link by the traffic information” with “the congestion situation of each road link by the demand predicted value” is performed. As a result, the “congestion status of each road link after interpolation processing” as shown in the lower part of FIG. 9A is obtained.
[0055]
In the subsequent step S211, processing for estimating the time required for the traffic information non-target road link is performed. This process assigns an average vehicle speed for the traffic information non-target road links in the predetermined area α so as to maintain the ratio (total distance ratio) in the predetermined area α with respect to all road links in the predetermined area α. The required time of the road link is estimated from the assigned average vehicle speed and the length of the road link, and corresponds to “traffic information non-target link required time estimation means” described in the claims.
[0056]
Specifically, according to the congestion threshold set in step S207, the traffic information non-target road links are assigned to “congestion”, “congestion”, and “normal” in step S209, respectively. The ratio within the predetermined area α (the ratio of the total distance) can be maintained with respect to the road link. On the other hand, since the allocation of the average vehicle speed is known from the road link type stored in the map / road link DB 23a accompanying the road map data, the road type of the non-target road link is based on this, An appropriate average vehicle speed is defined within the range of the definition of the degree of congestion shown in FIG. For example, as shown in FIG. 9B, in the case of a general road, the vehicle speed is 5 km / h when “congested”, the vehicle speed is 15 km / h when “crowded”, the vehicle speed is 40 km / h when “normal”, Respectively. In the case of an urban highway, the vehicle speed is defined as 10 km / h when “congested”, 30 km / h when “congested”, and 40 km / h when “normal”. Further, in the case of an intercity highway, the vehicle speed is defined as 20 km / h when “congested”, the vehicle speed is defined as 50 km / h when “congested”, and the vehicle speed is defined as 60 km / h when “normal”. As a result, the average vehicle speed according to each road type and the degree of congestion is defined, and by determining the average vehicle speed for each road link according to this, it is stored in the map / road link DB 23a along with the road map data. By dividing the length of each road link by the corresponding average vehicle speed, the required time can be calculated and estimated for each road link.
[0057]
When the required time for each of the traffic information non-target road links is estimated in step S211, it is determined whether or not the interpolation processing has been completed for all the predetermined areas divided in step S213. For example, in the example of Aichi Prefecture shown in FIG. 5, the processes in these steps are repeated for each section until the interpolation processing from step S <b> 203 to S <b> 211 is completed for all divided into 21 sections. When it is determined that the interpolation processing has been completed for all the divided predetermined areas (Yes in S213), the required time interpolation processing (No. 1) is terminated, and the required route required time estimation process shown in FIG. The process proceeds to S107.
[0058]
Returning to FIG. 2, a link information output process is performed in step S107. This processing is performed by the output program 22g, and processing for writing the required time data of the traffic information non-target road link interpolated in step S105 as interpolation required time data to the map / road link DB 23a is performed. Thus, the interpolation required time data is written for both the travel time (forward) and travel time (reverse) items in the data structure of the map / road link DB 23a shown in FIG.
[0059]
In the subsequent step S109, a required time estimation process is performed. This process is performed by the required time estimation program 22e, and corresponds to the “required time estimation means” described in the claims.
[0060]
That is, in the map / road link DB 23a, the required time data acquired by the traffic information target road link acquired in step S103 and the required interpolation time data by the traffic information non-target road link interpolated in step S105 are written. Since both are readable from the map / road link DB 23a, processing for estimating the required time between predetermined positions including the traffic information non-target road link is performed based on the required time data.
[0061]
For example, data relating to a departure place and a destination (for example, coordinate data based on longitude / latitude) is received from a navigation device 50 mounted on the vehicle 70 or a personal computer 120 connected to an electrical information communication network 105 (for example, the Internet). It searches for the shortest time route between the place and the destination and provides the user with the route and the required time. For the route search, for example, a route search by the Dijkstra method or the like is performed based on the road map data stored in the map / road link DB 23a, and traffic information target road links included in each searched route candidate correspond. The road link acquisition time data, and for the traffic information non-target road links included in the route, the corresponding road link interpolation time data are read from the map / road link DB 23a, respectively, and the sum of those is used to obtain the predetermined position. Estimate the time required between. Then, the route with the minimum required time is output to the user via the output program 22g as the shortest time route. The processing by the required time estimation program 22e is to obtain the shortest time route by using the required time of each road link as a cost value and using the sum of the required times of the road links included in each route candidate as an evaluation function for obtaining a so-called optimal solution. It is.
[0062]
Thus, in the route required time estimation process by the information center 20 according to the present embodiment, as shown in FIGS. 1 and 2, the traffic that is the target of the road traffic information by the traffic information acquisition program 22c (S103). Traffic information including acquisition time data of the information target road link is acquired from the traffic information center 100. Based on the acquired acquisition time data of the traffic information, the required time interpolation program 22d (S105) determines the road traffic information. Interpolate the time required for non-target traffic information non-target road links. Based on the required time data of the traffic information acquired by the traffic information acquisition program 22c (S103) and the required interpolation time data interpolated by the required time interpolation means, the required time estimation program 22e (S109) Estimate the required time between the predetermined positions including the target road link. As a result, it is possible to obtain the required time of the road for which the required time information is not provided by the road traffic information by such interpolation. Therefore, a device for collecting data from other traveling vehicles is provided separately. The required time can also be estimated for the road. Therefore, it is possible to easily estimate the required time for a road for which the required time information is not provided by the road traffic information.
[0063]
Further, when the required time interpolation program 22d (S105) specifies the road network by dividing the road network into the predetermined area α in step S201 by the required time interpolation processing (part 1) shown in FIG. The average vehicle speed of each road link is calculated from the length of each road link and the required time data, and the calculated average vehicle speed is “congested”, “crowded” and “normal”. The total distance of road links included in “congestion”, “congestion”, and “normal” is calculated, and the ratio to the total distance of road links is calculated for each classification. Further, in step S211, the average vehicle speed of the traffic information non-target road links in the predetermined area α is maintained so as to maintain the ratio (total distance ratio) in the predetermined area α with respect to all road links in the predetermined area α. And the required time of the road link is estimated from the assigned average vehicle speed and the length of the road link. Thus, if the length of the road link and the required time data for the road information target road link are known, it is possible to easily estimate the required time regarding the road for which the required time information is not provided by the road traffic information. .
[0064]
Here, the required time interpolation process (part 2) as another example of the subroutine for executing the required time interpolation process in step S105 shown in FIG. 2 will be described with reference to FIGS. This required time interpolation process (part 2) is different from the required time interpolation process (part 1) described with reference to FIG. 4 in that the traffic demand prediction DB 23b is not required.
[0065]
As shown in FIG. 10, in the required time interpolation process (part 2), first, in step S301, a process of creating a link set for each predetermined area including the traffic information target road link is performed. That is, the coordinate information of each road link is acquired from the road map data stored in the map / road link DB 23a, and the predetermined area is such that the range where the traffic information non-target road link exists is surrounded by the traffic information target road link. A process for dividing the data into each group and creating a link set included in the predetermined area is performed. For example, in the example shown in FIG. 11, the right side of the figure is such that the traffic information non-target road link represented by the dotted line is surrounded by the traffic information target road link represented by the solid line from the road map β on the left side of the figure. Is divided into predetermined areas βa, βb, and βc to create a link set.
[0066]
  In the subsequent step S303, a process of extracting a parallel road link including the traffic information target road link and estimating a required time of the traffic information non-target road link is performed. For example, in the case of the predetermined area βa shown in FIG. 11, as shown in FIG. 12, the traffic information non-target road link (FruitThe road links (dotted line) corresponding to “congestion” and the road links (dashed line) corresponding to “normal” are extracted as “traffic information target road links located in parallel with each other” which are parallel road links including lines) To do. This parallel road link extraction is performed based on whether or not the two road links are positioned in parallel so that the angle formed by the two road links falls within a predetermined range and whether or not they face the same route. However, as in the case of the predetermined area βc shown in FIG. 11, when a river is included in the predetermined area, the angle formed by the road links on the adjacent bridges passing through the bridge over the river is formed by the road links on both bridges. Even if it is not within the predetermined range, the road links on both bridges may be regarded as being located in parallel.
[0067]
  As a result, as shown in the lower part of FIG. 12, when a graph with the vertical axis as the required time and the horizontal axis as the distance from the reference point is created, the road link corresponding to “congestion” (dashed line) is used as the reference point. By expressing the required time in the vertical axis direction (left end of the horizontal axis) and the required time of the road link (dashed line) corresponding to “normal” at the position farthest from the reference point (right end of the horizontal axis) Thus, it is possible to interpolate the required time of the road link located between the both road links from the required time of the both road links. That is, in the example shown in FIG. 12, the required time obtained by the thick solid line in the graph of FIG..
[0068]
In step S305, processing for estimating the required time of the unconfirmed traffic information non-target road link is performed. That is, the process of estimating the required time for the traffic information non-target road link for which the required time could not be estimated in step S303 is performed in step S305. The traffic information non-target road link for which the required time could not be estimated in step S303 is, for example, any of the traffic information target road links surrounding the area, such as a predetermined area βb shown in FIG. Is a traffic information non-target road link that is not located in parallel.
[0069]
  In step S305, the time required for such unconfirmed traffic information non-target road link is divided by the time required for the traffic information target road link surrounding the area by dividing the length of the link by the required time. Estimated by calculating the average vehicle speed of the link and dividing the link length of unconfirmed traffic information non-target road links by this average vehicle speed.
[0070]
When the required time of the unconfirmed traffic information non-target road link is also estimated in step S305, it is determined whether or not the interpolation processing has been completed for all the predetermined areas divided in step S307. For example, in the example of the road map β shown in FIG. 11, the processing in these steps is repeated for each region until the interpolation processing in steps S303 and S305 is completed for all of the regions divided into about nine regions. . If it is determined that the interpolation processing has been completed for all the divided predetermined regions (Yes in S307), the required time interpolation processing (part 2) is terminated, and the required route time estimation processing step shown in FIG. The process proceeds to S107.
[0071]
Thus, in the required route time estimation process by the information center 20 according to the present embodiment, the required time interpolation program 22d (S105) of the required route time estimation process shown in FIGS. 1 and 2 performs the required time interpolation shown in FIG. Through the process (part 2), a traffic information target road link located substantially in parallel with the traffic information non-target road link is extracted (steps S301 and S303), and based on the required time data regarding the extracted traffic information target road link. The time required for the traffic information non-target road link is estimated (steps S303 and S305). As a result, if there is a traffic information target road link located substantially in parallel with the traffic information non-target road link, it is possible to easily estimate the required time for a road for which the required time information is not provided by the road traffic information. .
[0072]
The information center 20 is not limited to the configuration shown in FIG. 1, and may be the information center 220 having the configuration shown in FIG. 13, for example.
That is, as shown in FIG. 13, the information center 220 includes a route search unit 126, a route guidance data creation unit 127, and a prediction processing unit 128 while adopting the same hardware configuration as the information center 20 described above. It may be configured. In FIG. 13, the CPU, memory, and the like are not shown. In addition, components substantially the same as those of the information center 20 described above are denoted by the same reference numerals in FIG. 13, and description thereof is omitted here.
[0073]
Here, the route search unit 126, the route guidance data creation unit 127, and the prediction processing unit 128 will be described. These are all realized by a computer program and stored in a data storage device such as a memory constituting the information center 220.
[0074]
The route search unit 126 is based on the road map data obtained from the map / road link DB 23a (map DB 23a1, road link DB 23a2) and the road link data accompanying the road map data. For example, the Dijkstra method is employed as a search algorithm. The road link data referred to by the route search unit 126 is created and updated by the processes in steps S101 to S107 shown in FIG. 14, and the shortest time is obtained by the time slide method based on the concept shown in FIG. A route is searched. In FIG. 14, processing steps that are substantially the same as the processing steps constituting the route required time estimation process shown in FIG. Is omitted.
[0075]
The route guidance data creation unit 127 performs processing for creating data necessary for guiding the shortest time route searched by the route search unit 126. As an algorithm for creating the data, for example, there is one disclosed in Japanese Patent Application Laid-Open No. 2000-113388 by the applicant of the present application, and the created guidance data is the CCU 25 for the navigation device 50 that requested the route guidance data. Sent through.
[0076]
The prediction processing unit 128 performs a process of predicting a required time for every predetermined time (for example, 5 minutes) until, for example, 6 hours later based on the current required time information and past data, and has been described in the first embodiment. , A traffic information acquisition unit (traffic information acquisition program) 22c, a required time interpolation unit (required time interpolation program) 22d, a traffic demand prediction unit (traffic demand prediction program) 22f, etc. This is added in the second embodiment. Examples of algorithms for predicting the required time include those disclosed in JP-A-63-49999, JP-A-3-19100, JP-A-2002-260142, and the like. Is used.
[0077]
As shown in FIG. 14, the prediction processing unit 128 is executed as a required time prediction process interposed between step S105 and step S107, so that, for example, the required time that changes from time to time is converted to time slide cost data. Is output to the road link DB update unit (output program) 22g in step S107. Thereby, the data created by the prediction processing unit 128 can be referred to by the route search unit 126 as time slide cost data estimated every 10 minutes as shown in FIG. Then, it becomes possible to search for the shortest time path by the time slide method.
[0078]
As described above, the information center 220 according to the present embodiment includes the route search unit 126 and the route guidance data creation unit 127. As a result, the information center 220 simply estimates the required time information related to the road for which the required time information is not provided by the road traffic information, creates and updates the database, and further, the navigation device mounted on the vehicle 70 or the like. 50, when the information requesting the shortest time route from the departure point to the destination such as the current location is received, the route search unit 126 searches the shortest time route from the departure point to the destination by a time slide method or the like. The route guidance data creation unit 127 creates route guidance information necessary from the departure place to the destination based on the information on the shortest time route obtained by the above. Then, the generated route guidance information is transmitted to the requested navigation device 50. Therefore, the navigation device 50 can obtain route guidance information necessary from the departure place to the destination without searching for the route on the road for which the required time information is not provided by the road traffic information. The route guidance information for the shortest time can be provided to the user.
[0079]
Moreover, according to the information center 220 according to the present embodiment, the prediction processing unit 128 is provided. As a result, the required time information related to the road for which the required time information is not provided by the road traffic information is the same as the required time information related to the road for which the required time information is provided by the road traffic information. The required time can be predicted every time and can be accumulated in the required time database as time slide cost data, for example.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of an information center and a navigation device according to an embodiment of the present invention.
FIG. 2 is a flowchart showing a flow of route required time estimation processing according to the present embodiment.
3 is an explanatory diagram showing an example of the data structure of road link data acquired by the link information acquisition process shown in FIG. 2; FIG.
4 is a flowchart showing a flow of a process (part 1) according to an example of a required time interpolation process shown in FIG. 2;
FIG. 5 is an explanatory diagram showing an example of road links divided by the predetermined time interpolation processing (part 1) shown in FIG. 4;
6A is an explanatory diagram showing an example of the congestion ratio calculated by the predetermined time interpolation process (part 1) shown in FIG. 4, and FIG. 6B is an example of the definition of the congestion degree. It is a chart shown.
7A is an explanatory diagram showing an example of a demand prediction data table stored in the traffic demand prediction DB, and FIG. 7B is an explanatory diagram showing a configuration example for creating the traffic demand prediction DB. It is.
8 is an explanatory diagram showing a setting example of a congestion threshold by the predetermined time interpolation process (part 1) shown in FIG.
9A is an explanatory diagram showing an example of a congestion situation estimated by the predetermined time interpolation process (part 1) shown in FIG. 4, and FIG. 9B shows an example of a definition of the vehicle speed. It is a chart.
10 is a flowchart showing the flow of a process (part 2) according to another example of the required time interpolation process shown in FIG.
11 is an explanatory diagram showing an example of a set of road links created by the predetermined time interpolation processing (part 2) shown in FIG.
12 is an explanatory diagram showing an example of interpolation of the required time of the traffic information non-target link estimated by the predetermined time interpolation processing (part 2) shown in FIG. 10;
FIG. 13 is a block diagram showing another configuration example of the information center according to the embodiment of the present invention.
14 is a flowchart showing a flow of route required time estimation processing by the information center shown in FIG. 13;
15 is an explanatory diagram showing a concept of route search by a time slide method executed by a route search unit of the information center shown in FIG. 13;
[Explanation of symbols]
20, 220 Information center (required time estimation device)
21 CPU (traffic information acquisition means, required time interpolation means, required time estimation means, predetermined area specifying means, traffic information target link congestion degree classification means, traffic information non-target link required time estimation means)
22 memory
22a System program
22a 'DB creation / update control unit
22b Input program
22c Traffic information acquisition program (traffic information acquisition means)
22d Required time interpolation program (Required time interpolation means)
22e Required time estimation program (Required time estimation means)
22f Traffic demand forecasting program
22g output program
23a Map / Road Link DB
23a1 Map DB
23a2 Road Link DB
23b Traffic demand forecast DB
25 Communication control device (traffic information acquisition means)
50 Navigation device
70 vehicles
100 Traffic Information Center (external)
126 Route search unit
127 Route guidance data creation part
128 Prediction processing unit
S103 (traffic information acquisition means), S105 (required time interpolation means), S109 (required time estimation means), S201 (predetermined area specifying means), S203 (traffic information target link congestion degree classification means), S211 (traffic information non-target) Link duration estimation means)

Claims (1)

Traffic information acquisition means for acquiring traffic information including required time data of the traffic information target road link that is the target of the road traffic information;
Based on the traffic information acquired by the traffic information acquisition means, required time interpolation means for interpolating the required time of the traffic information non-target road link that is not the target of road traffic information;
A required time estimating means for estimating the traffic information the acquired by the acquisition unit traffic information and, based on the required time interpolated by the travel time interpolator means, where needed time,
With
The required time interpolation means includes:
A predetermined area specifying means for specifying the road network by dividing it into predetermined areas;
For the traffic information target road link in the predetermined area, the average vehicle speed of each road link is calculated from the length of each road link and the required time data, the calculated average vehicle speed is classified by a predetermined value, A traffic information target link congestion degree classification means for calculating a total distance of road links included in the classification and calculating a ratio of the total distance of road links for each classification;
For the traffic information non-target road link in the predetermined area, the average vehicle speed is assigned so as to maintain the ratio of the total distance to the road link in the predetermined area, and the assigned average vehicle speed and the road link Traffic information non-target link travel time estimation means for estimating the travel time of the road link from the length,
A required time estimation device comprising:

Images