JPH083880B2 - Road traffic information monitoring device - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to a road traffic information monitoring device for providing accurate information to road users and for effective use of road facilities by appropriate traffic flow control. Regarding

2. Description of the Related Art Conventionally, this type of road traffic information monitoring device is equipped with a sensor installed around the road and a processing device for grasping a phenomenon of traffic flow, and various traffic data obtained from the sensor is collected at all points. The current state of traffic flow was monitored by processing with uniform criteria.

DISCLOSURE OF THE INVENTION Problems to be Solved by the Invention However, since the above-mentioned conventional road traffic information monitoring device processes the data obtained from the sensor by a uniform standard, the temporal and spatial change characteristics of the traffic flow are incorporated. There was a problem that it was not possible to monitor traffic flow accurately and immediately.

The present invention solves such a conventional problem, and an object of the present invention is to provide an excellent traffic flow information monitoring device capable of accurate and immediate traffic flow monitoring.

Means for Solving the Problems In order to solve the above problems, the present invention detects the number of vehicles, the occupancy rate, and the speed by means of the data collecting means, and the predicting means so that the actual curve with respect to the approximate curve of the traffic density and the alternating current amount can be obtained. By detecting the values of the traffic density and the traffic volume as changes in the distance over time, it is configured to predict traffic congestion when there are large positive and negative fluctuations.

With the above-described configuration, the present invention can incorporate the temporal and spatial change characteristics of the traffic flow from the data obtained from the data collection means, so that accurate and immediate monitoring of the traffic flow can be performed. .

Embodiment FIG. 1 is a block diagram of a road traffic information monitoring device according to an embodiment of the present invention.

In FIG. 1, 1 is a data collecting means for detecting road traffic information, 2 is a phenomenon grasping means for detecting the current traffic state from the signal of the data collecting means 1, and 3 is a future traffic state from the signal of the phenomenon grasping means 2. Is a prediction means for predicting.

4 is a vehicle detector for detecting the number of vehicles passing through a certain point, occupancy rate, speed, vehicle type, etc., 5 is an image sensor,
Image processing and recognition are performed from the signals of the TV camera to detect sudden events such as traffic accidents. Reference numeral 6 is an AVI sensor, which detects the travel time of the vehicle by reading the license plate of the vehicle and comparing them at a plurality of locations. A man-machine 7 is used by a person in charge to input site information such as a traffic accident.

8 is a signal of the number of vehicles, occupancy rate, speed, etc., a signal of an unexpected event,
It is a microscopic grasping means that performs traffic flow judgment and sudden event detection from a travel time signal and outputs a traffic flow mode signal. Reference numeral 9 is a macro grasping means for calculating the section state quantity from the signals of the number of vehicles, occupancy rate, speed, etc., travel time signals, and traffic flow signals.

10 is a traffic flow mode signal, a normal time prediction means for predicting the normal time from the section state quantity signal, 11 is a traffic flow mode signal,
It is a predicting means after occurrence of an unexpected event that performs prediction after occurrence of an unexpected event from a section state quantity signal.

 Next, the operation of the above embodiment will be described.

In FIG. 1, when the data collecting means 1 collects data, the micro grasping means 8 and the macro grasping means 9 process the data in a cycle according to the purpose, and the past and present spatial characteristics and temporal characteristics are processed. By taking into consideration the current state of traffic flow, detection of a sudden accident, or calculation of the state quantity in the target section. Further, those results are used for prediction of traffic flow by the prediction means 3.

As described above, according to the above-described embodiment, the data is collected by the data collecting unit 1 and is used by the micro grasping unit 8, the macro grasping unit 9, and the predicting unit 3 in consideration of the change characteristic, and the traffic flow is accurately identified. You can grasp the current situation and make predictions,
As a result, accurate information will be supplied to road users and efficient use of road resources.

 The operation of the present invention will be described in more detail.

First, the relationship between the traffic volume and the speed at one point in the traffic flow for judging the traffic congestion based on the characteristics of the traffic flow is generally expressed as shown in FIG. This characteristic is the relationship between traffic volume and occupancy,
It is known that this is also seen in the relationship between traffic volume and density.
As can be seen from this figure, the distribution of data shows a specific tendency during free running, but shows a discrete distribution during traffic jams, and no specific tendency is seen. However, as far as FIG. 2 is seen, it is impossible to accurately separate free running and congestion. As a result, conventionally, a method has been adopted in which a threshold value is set for a single parameter such as only speed or occupancy rate to make a judgment. However, by observing the approximate curve of FIG. 2, the actual value, and the distance over time, it becomes possible to separate between free running and congestion. This is shown in FIG.

FIG. 3 is a characteristic diagram showing the values of the actual traffic density and the traffic volume with respect to the approximate curve of FIG. 2 as changes in distance over time. The distance in FIG. 3 is derived from the absolute distance from the traffic density and traffic value to the approximate curve by plotting the actual traffic density and traffic value in FIG. The positive / negative setting of the distance in FIG. 3 is set to be positive when the values of the actual traffic density and the traffic volume are plotted within the approximate curve, and is set to be negative when plotted outside the approximate curve. Figure 3 shows
This derived positive or negative distance is represented with the passage of time.

As can be seen from FIG. 3, there is a relatively stable distribution in the initial stage, and at a certain moment, a violent positive trigger is observed, followed by a violent negative trigger, followed by a large fluctuation. In this fluctuation pattern, when a strong positive trigger is seen, it is when a traffic jam occurs.

The approximate curve in FIG. 2 is based on the least square method. By utilizing this characteristic, it is possible to judge whether the free flowing state of the traffic flow is a traffic jam.

Secondly, it is possible to select a collection cycle that suits the purpose by utilizing the result of the previous judgment of traffic jam. In traffic flow monitoring during traffic congestion, when calculating a state quantity that represents a stable overall tendency in a specific section, the collection cycle of the data to be processed is set in units of several minutes, and the occurrence of an unexpected event is immediately detected. When it is necessary to make a judgment, the data collection cycle shall be in seconds. Precise monitoring is possible by selecting such a collection cycle.

Thirdly, by extracting and using the change characteristics of traffic data at a specific time zone at the location where the sensor is installed, it is possible to know the scale, time and impact of traffic flow fluctuations such as traffic congestion. It can be used for prediction.

Fourth, by comparing the characteristics of changes in the traffic data extracted for each sensor installation point with the characteristics of the points that are thought to affect it, the propagation of traffic flow can be captured and used to predict traffic congestion and detect unexpected events. To do.

In terms of the above, not only conventional vehicle detectors that collect point data such as traffic flow, occupancy rate, speed,
Even in the case of a sensor that collects spatial data using an ITV camera, the same effect can be obtained by extracting and utilizing a change characteristic such as a luminance distribution by performing image processing.

 This embodiment has the following advantages.

(1) Accurate traffic congestion can be determined by using the change characteristics of traffic data.

(2) Since the processing cycle according to the purpose is adopted by using the result of (1), the phenomenon of traffic flow can be accurately grasped.

(3) By using the time-series change characteristics of each point, it is possible to accurately grasp and predict the occurrence time, scale, and impact of traffic flow fluctuations such as traffic congestion.

(4) By utilizing the spatial change characteristics of multiple points, it is possible to grasp the propagation of traffic flow, etc., and to accurately grasp and predict traffic flow fluctuations.

(5) As a result, traffic control operators can reduce their work and use road resources efficiently.

(6) In addition, it is possible to judge effective road use by receiving appropriate information provided to road users.

EFFECTS OF THE INVENTION The present invention has the following effects, as is apparent from the above-described embodiments.

(1) Plotting the traffic volume and the traffic density with respect to the approximate curve of the traffic volume and the traffic density, calculating the absolute distance from this plot to the above approximate curve, and for the absolute distance, the above plot is the above approximate curve. Negative value if
If the above plot is outside the approximate curve, set a positive value, and by observing the change in this absolute distance over time, it is possible to separate free running and congestion without setting a threshold value. , It is possible to accurately grasp changes in traffic flow.

(2) Absolute distance does not change positively or negatively over time during free running, but when traffic congestion occurs, absolute distance fluctuates greatly from negative to positive, so the movement of this absolute distance is grasped. By doing so, it is possible to accurately grasp and predict the occurrence of traffic congestion.

(3) Further, by grasping the movement of the absolute distance in the course of time, it is possible to grasp the occurrence time of the traffic flow fluctuation and the influence after the occurrence.

[Brief description of drawings]

FIG. 1 is a block diagram of a road traffic information monitoring device according to an embodiment of the present invention, FIG. 2 is a characteristic diagram of traffic density and traffic volume according to the same embodiment, and FIG. 3 is an actual curve for the approximate curve of FIG. It is a characteristic view which represented the value of traffic density and the amount of traffic as change of the passage of time of distance. 1 ... Data collection means, 2 ... Phenomenon understanding means, 3 ... Prediction means, 4 ... Vehicle detector, 5 ... Image sensor, 6
... AVI, 7 ... Man-machine, 8 ... Micro grasping means, 9 ... Macro grasping means, 10 ... Normal prediction means,
11 …… Prediction means after occurrence of an unexpected event.

Claims (1)

[Claims] 1. A data collection means for sensing traffic volume and traffic density at one point, and a traffic volume and traffic sensed by the data collection means for an approximate curve preset in relation to traffic volume and traffic density. Plot the density, calculate the absolute distance from this plot to the above approximation curve, and if this plot is within the above approximation curve with respect to this absolute distance, make it a negative value In some cases, when the phenomenon grasping means that takes a positive value and the absolute distance calculated by the phenomenon grasping means momentarily greatly change from negative to positive in the course of time are considered to be congestion occurrences. A road traffic information monitoring device, comprising: a prediction means for determining.