JPH03246799A - Traffic flow variance monitor device - Google Patents

Abstract

PURPOSE:To quickly forecast occurrence or resolution of traffic snarl by monitoring the variance of traffic flow by the speeds or the like of individual vehicles and distances among continuous vehicles. CONSTITUTION:The vehicle sense signal from a vehicle sensor 11 provided on a road is detected by a signal detecting part 12, and a vehicle sense data editing part 13 which generates vehicle sense data by the vehicle sense signal, a vehicle sense data classifying part 14 which classifies vehicle sense data, an inter-vehicle distance data editing part 15 which generates inter-vehicle distance data by the vehicle sense signal, and an inter-vehicle distance data classifying part 16 which classifies inter-vehicle distance data are provided. A variance deciding part 17 compares ranked classification results related to vehicle sense data and inter-vehicle distance data with preliminarily determined combinational discrimination values to monitor the change with time, and the variance of traffic flow is discriminated. Thus, occurrence or resolution of snarl is quickly forecasted.

Description

DETAILED DESCRIPTION OF THE INVENTION Field of the Invention The present invention relates to a traffic flow fluctuation monitoring device that collects and analyzes information regarding road traffic and provides accurate information to road users.

Conventional technology In recent years, as society's demand for information provision services for drivers has increased, there has been a demand for enhanced traffic control equipment to support this. There is a need for improved functionality in monitoring equipment.

Hereinafter, a conventional traffic flow fluctuation monitoring device will be explained based on the drawings.

FIG. 3 is a block diagram showing the configuration of a conventional traffic flow fluctuation monitoring device.

In FIG. 3, 1 is a vehicle detection sensor installed on the road, such as an ultrasonic sensor, 2 is a signal detection unit that detects a vehicle detection signal from the vehicle detection sensor 1, and 3 is a signal detection unit 2.
This is a vehicle sensing data editing section that edits the detected vehicle sensing signal as parameters such as vehicle speed.

Reference numeral 4 denotes a vehicle sensing data classification section, which ranks the vehicle sensing data edited by the vehicle sensing data editing section 3 using a predetermined threshold value regarding the vehicle sensing data.

Reference numeral 5 denotes a fluctuation determination section, which monitors the temporal changes in the ranking of vehicle sensing data by the vehicle sensing data classification section 4 and determines changes in traffic flow. Reference numeral 6 denotes an output unit that outputs the determination result by the fluctuation determination unit 5.

Next, the operation of the above conventional example will be explained.

When a vehicle traveling on a road passes through the sensing range of the vehicle detection sensor 1, the signal detection unit 2 detects the passage of the vehicle as a vehicle sensing signal. This vehicle sensing signal is edited by the vehicle sensing data editing section 3 into parameters such as pulses indicating a signal detection time according to the vehicle speed, and sent to the vehicle sensing data classification section 4 in the form of a pulse or the like that is summarized in units of time.

The vehicle sensing data classification unit 4 compares the parameterized vehicle sensing data with a predetermined threshold value to classify each vehicle sensing data. The classification results are sent to the fluctuation determining section 5, which monitors changes over time in the classification results of vehicle sensing data at the same measurement point to determine changes in traffic flow, and outputs the determination results from the output section 6.

In this way, even with the conventional traffic flow fluctuation monitoring device described above, fluctuations in traffic flow can be monitored by processing the vehicle detection signal obtained from the vehicle detection sensor.

Problems to be Solved by the Invention However, the conventional traffic flow fluctuation monitoring device described above monitors traffic flow fluctuations based on the speed of individual vehicles, etc.
There is a problem in that it is not possible to monitor the positional relationship of vehicles running continuously, and therefore it is not possible to quickly predict the occurrence or resolution of traffic jams or to quickly detect unexpected events such as accidents.

The present invention solves the above-mentioned conventional problems, and aims to provide an excellent traffic flow fluctuation monitoring device that can quickly and accurately detect traffic flow fluctuations.

Means for Solving the Problems In order to achieve the above object, the present invention provides a signal detection unit that detects a vehicle detection signal from a vehicle detection sensor installed on the road, and a vehicle detection unit that detects a vehicle detection signal detected by the signal detection unit. Vehicle sensing data editing means for generating vehicle sensing data based on the signal; vehicle sensing data classification means for classifying the vehicle sensing data; and vehicle distance data editing means for generating vehicle distance data using the vehicle sensing signal detected by the signal detection section. The present invention includes a vehicle-to-vehicle data classification means for classifying vehicle-to-vehicle distance data, and a fluctuation determining means for determining a change in traffic flow based on the classification results of vehicle sensing data and vehicle-to-vehicle data.

Effect: With the above configuration, the present invention monitors changes in traffic flow based on the speed of each vehicle and the distance between successive vehicles, so it is possible to monitor the positional relationship of successive vehicles. Therefore, it is possible to quickly predict the occurrence and resolution of traffic jams,
Unexpected events such as accidents can be detected quickly.

Example Hereinafter, one embodiment of the present invention will be described based on the drawings.

FIG. 1 is a block diagram showing the configuration of a traffic flow fluctuation monitoring device according to an embodiment of the present invention.

In FIG. 1, reference numeral 11 indicates a vehicle detection sensor such as an ultrasonic sensor, which is installed at each measurement point on the road to detect a vehicle, and 12 indicates a vehicle detection signal from each vehicle detection sensor 11. , a signal detection unit that classifies the vehicle presence signal into a vehicle presence signal corresponding to the speed of the vehicle and a vehicle absence signal corresponding to the inter-vehicle distance; The vehicle sensing data editing unit 14, which is a means for generating vehicle sensing data corresponding to the average vehicle speed, generates vehicle sensing data based on predetermined rank-based reference values regarding vehicle sensing data, that is, a plurality of threshold values. A vehicle sensing data classifier is a means for ranking vehicle sensing data.

15 is a distance data editing section 16 as a means for summing the vehicle non-existence signals classified by the signal detection section 12 for each unit time to generate distance data corresponding to an average distance between vehicles;
is a distance-between-vehicle data classification unit that ranks the distance-between-vehicles data based on predetermined rank-based reference values for the distance-between-vehicles data, that is, a plurality of threshold values.

17 is a fluctuation determination unit that compares the ranking results of vehicle sensing data and inter-vehicle distance data with a predetermined combination determination value, monitors the changes over time, and determines changes in traffic flow; This is an output unit that outputs the determination result of the fluctuation determination unit 17.

Next, the operation of the above embodiment will be explained based on FIGS. 1 and 2.

When a vehicle traveling on the road passes through the sensing range of each vehicle detection sensor 11, the signal detection unit 12 detects the passage of the vehicle as a vehicle sensing signal. As shown in FIG. 2, this vehicle detection signal includes a high-level vehicle presence signal corresponding to the time (value P) that each vehicle passes through the sensing range of the vehicle detection sensor 11, and a high-level vehicle presence signal corresponding to the time when the presence of a vehicle is not detected. (value S) and a low-level vehicle non-existence signal corresponding to the value S.

The signal detection unit 12 assigns numbers to the above-mentioned values P and S according to the running order of the vehicle (P,, 51p2.s2..
), the values (Pl, P2...) are sent to the vehicle sensing data editing section 13, and the values (Sl, S2...) are sent to the inter-vehicle distance data editing section 15, respectively.

In the vehicle sensing data editing section 13, the value (P1P2...
) is divided by a predetermined general vehicle length to calculate the speed of each vehicle, and this calculated value is aggregated for each unit time to generate vehicle sensing data corresponding to the average vehicle speed. The vehicle sensing data is transferred to the vehicle sensing data classification unit 14.
send to The vehicle sensing data classification unit 14 ranks the vehicle sensing data based on a plurality of threshold values and performs classification by rank.

On the other hand, the inter-vehicle distance data editing section 15 selects the value (so.

S2. ) is counted by a clock to calculate the inter-vehicle distance between each vehicle, and this calculated value is aggregated for each unit time to generate inter-vehicle data corresponding to the average inter-vehicle distance, and this inter-vehicle data is used as inter-vehicle data. It is sent to the classification section 16. The inter-vehicle data classification unit 16 ranks the inter-vehicle data based on a plurality of threshold values and performs classification by rank.

The rank-based classification results for each of the vehicle sensing data and inter-vehicle distance data are both sent to the fluctuation determining section 17, and the fluctuation determining section 17 compares the rank-based classification results for each of the vehicle sensing data and inter-vehicle distance data with the combination determination value. By monitoring the change over time, a change in traffic flow is determined, and the determination result is outputted from the output unit 18.

In this embodiment, an ultrasonic sensor is used as the vehicle detection sensor 11, but any sensor that can detect the running condition of each vehicle and the distance between the vehicles may be used, such as an image processing sensor. A sensor may also be used.

Furthermore, as the data obtained from the vehicle detection sensor 11, in this embodiment, data based on time such as the time when the vehicle was detected and the time when the vehicle was not detected was used.
Any other data may be used as long as it serves as a basis for calculating the traveling speed of each vehicle and the inter-vehicle distance.

Effects of the Invention As described above, according to the present invention, vehicle sensing data is generated using a signal detection section that detects a vehicle detection signal from a vehicle detection sensor installed on the road, and a vehicle detection signal detected by this signal detection section. A vehicle sensing data editing means for generating vehicle sensing data, a vehicle sensing data classification means for classifying the vehicle sensing data, a vehicle sensing data editing means for generating vehicle distance data based on the vehicle sensing signal detected by the signal detection section, and a vehicle sensing data editing means for classifying the vehicle sensing data. The present invention includes a vehicle distance data classification means and a fluctuation determination means for determining traffic flow fluctuations based on the classification results of vehicle sensing data and vehicle distance data. This makes it possible to monitor changes in traffic flow.

Therefore, it is possible to monitor the positional relationship of each vehicle running continuously, and therefore, it is possible to quickly predict the occurrence and resolution of traffic jams, and to quickly detect unexpected events such as accidents.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing the configuration of a traffic flow fluctuation monitoring device according to an embodiment of the present invention, FIG. 2 is an explanatory diagram showing an example of a vehicle detection signal by the vehicle detection sensor of FIG. 1, and FIG. 3 is a conventional diagram. 1 is a block diagram showing a traffic flow fluctuation monitoring device of FIG. 11... Vehicle detection sensor, 12... Signal detection unit, 1
3... Vehicle sensing data editing section, 14... Vehicle sensing data classification section, 15... Vehicle data editing section, 16...
Inter-vehicle data classification section, 17... Fluctuation determination section.

Claims (1)

[Scope of Claims] A signal detection unit that detects a vehicle detection signal from a vehicle detection sensor installed on the road; and a vehicle detection signal detected by the signal detection unit,
A vehicle sensing data editing means for generating vehicle sensing data; a vehicle sensing data classification means for classifying the vehicle sensing data; and a vehicle sensing signal detected by the signal detection section.
A distance data editing means for generating distance data; a distance data classification means for classifying the distance data; and a classification result of the vehicle sensing data and the distance data.
A traffic flow change monitoring device comprising: a change determination means for determining a change in traffic flow.