KR102002303B1 - Pedestrian-Vehicle Conflict Risk Analysis System - Google Patents

Abstract

Pedestrians (especially the elderly, persons with disabilities, children with stray cars, etc.) - Interaction between pedestrians and vehicles to identify the interactions between vehicles and to analyze the risk of conflicts accurately by automating conflict risk indicators. The present invention relates to a risk analysis system, which includes an information collecting unit for collecting information for analyzing a risk of a conflict between a pedestrian and a vehicle, a data collecting unit for collecting data from the information collecting unit, A risk data evaluation unit for analyzing the risk data generated by the risk data generation unit to calculate a risk risk assessment index and analyzing the risk risk risk assessment index to determine a risk risk level; And the information on the result of the analysis by the calculation and analysis section Analysis results, including providing parts, the pedestrian-implement a trade-off between the risk analysis system vehicle.

Description

[Background Art] [0002] Pedestrian-Vehicle Conflict Risk Analysis System [

The present invention relates to a system for analyzing the risk of collision between a pedestrian and a vehicle, and particularly relates to a system for analyzing the risk of collision between a pedestrian (particularly, an elderly person, a disabled person, a child with a stroller, The present invention relates to a pedestrian-vehicle conflict risk analysis system that can automate and accurately analyze conflict risk.

According to the statistics of the Korea Traffic Safety Authority (KSA) in 2015, the number of traffic accident fatalities in Korea was 4,621, and the number of pedestrian traffic accidents was 1,795. The traffic accident of the undercarriage is more vulnerable to the pedestrian than the occupant of the vehicle, so there is a high probability of serious traffic accidents such as death. The number of traffic accidents at intersections during the accident of an undercarriage reached 1407 persons, and crossing accidents accounted for 42.6% of the total accidents. As a method for mitigating the traffic accident of the undercarriage, research on alert notification and avoidance strategy through P2V (Pedestrian to Vehicle) or V2P (Vehicle to Pedestrian) wireless communication is actively being carried out. It is important to understand the behavior characteristics (position, speed, acceleration / deceleration, and direction) of vehicles and pedestrians in real time, or to track and model them. In defining the trade-off relationship between pedestrian and vehicle, it is necessary to first collect the position, velocity, and directional index of each object, calculate TA (Time to Accident) I for each analysis time, It is important.

Conflicts have been defined in two ways in the previous studies. First, according to ICTCT (International Cooperation on Theories and Concepts in Traffic safety), potential traffic conflicts exist in the same risk zone at the same time. Second, GM defines "as an interaction between two or more road users, an event that causes road users to evade actions to avoid impending accidents."

In addition, Chriter Hyden (1987) classified the conflicts occurring during driving into four stages: Undisturbed Passages, Potential Conflicts, Slight Conflicts, and Serious Conflicts. He explained that the peak of serious conflicts in driving leads to accidents and deadly accidents such as death and serious injury are located at the peak.

On the other hand, the crosswalk of the road and the intersection is a point where the pedestrian crosses the vehicle by judging whether or not the vehicle enters, enters, and the remaining time through the change of the left and right eyes. Recently, transverse accidents such as elderly pedestrians are becoming a social problem because older pedestrians have weaknesses in vehicle recognition.

In order to prevent the transit accident of such a traffic abbreviation, conventionally proposed techniques for analyzing the intention of the pedestrian to transit are disclosed in the following Patent Documents 1 to 4.

The prior art disclosed in Patent Document 1 acquires the user's walking data using the acceleration sensor, learns the user's walking data using the obtained walking data through the neural network, and obtains the learned walking data and the user's walking Comparing the gait data with each other, and providing health related services such as a left / right unbalance and a health condition according to a gait pattern on the basis of the comparison result.

With this configuration, not only systematic health related services can be provided, but also the accuracy of user authentication can be improved if the unique walking characteristics of the pedestrian are utilized in the user authentication service.

The conventional art disclosed in Patent Document 2 includes a walking sensor for detecting the state of the gait and a walking sensor installed on a part of the body where the state of the gait is changed when walking, A controller for receiving and analyzing walking data sensed by the walking sensor to generate calibration data for calibrating a walk and displaying the generated calibration data through the display unit, and a control unit for housing the display unit and the controller, And a wearing portion for wearing.

With this configuration, the wrist can be easily worn on the wrist, and analysis and correction information on the walking of the body to be calibrated is also provided by the management server located remotely through the network.

The prior art disclosed in Patent Document 3 includes a first support fixed to a waist of a user and connected to a rail and a second support fixed to a thigh of the user and connected to the first support and the rail, The support may move along the rail about the first support in response to the user's walking state.

With such a configuration, the user's walking state is analyzed through a walking state analyzing device fixed to the user's waist and thighs.

In the prior art disclosed in Patent Document 4, the pedestrian is an elderly person, a disabled person, a sick person, an athlete, or a learner. The measuring unit measures walking information of a pedestrian, generates data representing the walking information, And acts on the arm of the pedestrian according to the walking information data measured by the walking section, thereby improving the walking motion by the arm movement during walking.

Korean Patent Publication No. 10-2011-0093283 (Published Aug. 18, 2011) (Gait Pattern Analysis Apparatus and Method) Korean Patent Laid-Open No. 10-2012-0085064 (published on Jul. 31, 2012) (worn type walking analysis apparatus and gait analysis system including the same) Korean Registered Patent No. 10-1338687 (Registered on December 2, 2013) (Gait Analysis Apparatus and Method, and Gait Imbalance Evaluation Apparatus) Korean Patent Laid-Open No. 10-2015-0100797 (Published on May 21, 2015) (Walking Support Device and Walking Support Method)

However, the above-mentioned conventional methods of analyzing the conflict between the pedestrian and the vehicle and the related art have not been studied in detail regarding the risk level and the risk level in the determination of the elderly person situation, even though the number of the road traffic accident fatalities and mortality rate of the elderly person is high. And the data collection and analysis method for the data is also performed manually. These manual processes are costly and time-consuming and difficult to use easily in many areas.

In addition, the conventional method of analyzing the conflict between the pedestrian and the vehicle and the conventional techniques are difficult to accurately grasp the behavior characteristics (position, speed, acceleration / deceleration, directionality) between the vehicle and the pedestrian in real time, There are also difficult disadvantages.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made keeping in mind the above problems occurring in the prior art, and it is an object of the present invention to provide a method and apparatus for preventing interactions between pedestrians (particularly, transportation abbreviations such as elderly persons, persons with disabilities, children, The present invention provides a system for analyzing the risk of collision between automobiles and pedestrians.

According to an aspect of the present invention, there is provided a system for analyzing the risk of collision between a pedestrian and a vehicle, comprising: an information collecting unit for collecting information for analyzing a risk of conflict between a pedestrian and a vehicle; A data generator for processing the information collected by the information collecting unit to generate raw data for analyzing the risk of collision between the pedestrian and the vehicle; A conflict risk assessment index calculation and analysis unit for analyzing the log data generated by the log data generation unit to calculate a conflict risk assessment index and analyzing the calculated conflict risk assessment index to determine a conflict risk level; And a conflict risk analysis result providing unit for providing information as a result of analysis by the conflict risk evaluation index calculation and analysis unit.

The information collecting unit may include a road and environment information collecting unit for collecting environmental information, which is information on the geometry, road width, road type, and location of the road; An image information collecting unit for collecting the pedestrian image information by using image equipment for monitoring an intersection; A vehicle information collecting unit for collecting vehicle factor information using the VDS equipment; And a pedestrian information collecting unit for acquiring the behavior characteristic information of the pedestrian using the personal wearable equipment.

The pedestrian information collecting unit uses the pedestrian information and the heading information of the pedestrian to calculate the pedestrian position, the number of steps, the step, the walking time, the information about the walking speed, the visual information of the walking direction of the pedestrian, , Age, sex, and identification information (name, address, resident registration number).

The data generation unit generates an arithmetic factor of the evaluation index for analyzing the risk of conflict between the pedestrian and the vehicle based on the road geometry and intersection information collected by the information collection unit, the behavior characteristic information of the pedestrian, the image information, .

In the above, the arithmetic factor of the evaluation index includes the number of lanes, the number of people to be measured, the estimated distance of conflict from the vehicle measurement position, the distance from the vehicle measurement position to the stop line, the crossing distance from the curb to the extension line of the lane, Pedestrian average crossing time, average pedestrian crossing time, number of vehicles passing by means, number of pedestrian crossing per unit time, total vehicle traffic per second , And an estimated amount is included in the tolerance weight.

In the above, the calculation and analysis unit for the risk of conflict index is to detect the position, speed, and direction of the vehicle and the pedestrian, estimate the conflict point among them first, estimate the arrival of the pedestrian at the crossing point to the point of conflict, And estimating a pedestrian safety interval that is a time difference, thereby quantifying the risk of conflict.

In the above, the calculation and analysis section of the risk and risk management index is composed of a safety margin, a pedestrian risk index, an exposure index, a severity index, a risk index, (level of safety) is calculated as a conflict risk evaluation index.

In the above, the result of the conflict risk analysis result provides the analysis results in the form of synchronizing the road geometry and intersection information, the pedestrian behavior characteristic information, the image information and the vehicle factor information after the analysis unit time, and displays the gait characteristic index, And displaying the indicator.

According to the present invention, it is possible to confirm the interaction between pedestrians (in particular, traffic abbreviations such as elderly persons, persons with disabilities, children, strollers, etc.) and vehicles, and automate the risk- There is an advantage to doing.

1 is a block diagram of a system for analyzing a conflict risk between a pedestrian and a vehicle according to the present invention;
2 is an exemplary view of an information collecting screen in the present invention,
FIG. 3 is an exemplary view for extracting a gaze direction of a person wearing equipment,
FIG. 4 is a conceptual diagram of a system application of an evaluation in an external monitoring environment and a personal wearable collection-
FIG. 5 is an application example of the monitoring system,
6 is a diagram illustrating an example of calculating a PSM value according to a conflict type between a pedestrian and a vehicle,
Figure 7 is an example of cross-over conflict type classification.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a system for analyzing conflict risk between a pedestrian and a vehicle according to a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of a system for analyzing a conflict risk between a pedestrian and a vehicle according to a preferred embodiment of the present invention.

The system for analyzing the risk of collision between pedestrian and vehicle according to the present invention includes an information collecting unit 10, a raw data generating unit 20, a conflict risk evaluation index calculating and analyzing unit 30, 40).

The information collecting unit 10 collects information for analyzing the risk of conflict between the pedestrian and the vehicle.

The information collecting unit 10 includes a road and environment information collecting unit 11 for collecting environmental information, which is information on the geometry, road width, road type, and location of the road, and video equipment for monitoring the intersection, A vehicle information collecting unit 13 for collecting vehicle factor information using the VDS equipment, a pedestrian information collecting unit for acquiring behavior characteristic information of the pedestrian using the personal wearable equipment 14).

The pedestrian information collecting unit 14 uses the pedestrian information and the heading information of the pedestrian to calculate the position of the pedestrian, the number of steps, the step width, the walking time, the information on the walking speed, the visual information of the walking direction of the pedestrian, Age, gender, and identification information (name, address, resident registration number).

The log data generator 20 processes the information collected by the information collector 10 and generates raw data for analyzing the risk of collision between the pedestrian and the vehicle.

The road data generation unit 20 is configured to analyze the risk of collision between the pedestrian and the vehicle based on the road geometry and intersection information collected by the information collection unit 10, the behavior characteristic information of the pedestrian, the image information, It is preferable to generate an arithmetic factor of the evaluation index.

Here, the arithmetic factor of the evaluation index includes the number of lanes (i), the number of people to be measured (j), the distance (L3) from the vehicle measurement position to the stop line (L3) A walking speed v1 from the curb to the extension line of the lane to the center line of the lane, an average distance G between the vehicles, an average crossing of the pedestrian (Mg), the total number of vehicles per second (lambda), and the tolerance weight (t1), the average transit pedestrian walking time (t2) .

Also, the trade risk evaluation index calculation and analysis unit 30 analyzes the log data generated by the log data generation unit 20 to calculate a trade risk measure index, analyzes the trade risk measure index, As shown in FIG.

The conflict risk assessment index calculation and analysis unit 30 detects the position, speed, and direction of the vehicle and the pedestrian, estimates the conflict point among them first, estimates the difference between the arrival and departure of the pedestrian at the crossing point to the conflict point It is desirable to estimate the risk of conflict by estimating the pedestrian safety interval which is the time difference with the vehicle.

More specifically, the conflict risk assessment index calculation and analysis unit 30 may calculate the risk index of the risk to be avoided by using the safety risk assessment index such as a saftey margin, a pedestrian risk index, an exposure index, a severity index, the risk index, and the level of safety are calculated as a conflict risk evaluation index.

Also, as a result of the risk analysis, the provider 40 provides information on the result of the analysis performed by the risk-and-risk index calculation and analysis unit 30.

As a result of the analysis of the conflict risk, the providing unit 40 provides an analysis result in the form of synchronizing the road geometry and intersection information, the pedestrian behavior characteristic information, the image information and the vehicle factor information after the analysis unit time, Or to present a risk indicator of conflict.

The operation of the system for analyzing the conflict risk between the pedestrian and the vehicle according to the preferred embodiment of the present invention will be described in detail as follows.

First, in order to analyze the risk of conflict between the pedestrian and the vehicle, the information collecting unit 10 collects information for analyzing the risk of conflict between the pedestrian and the vehicle.

For example, as shown in FIG. 2, the information collecting unit 10 collects environment information, which is information on the geometry, road width, road type, and location of the road through the road and environment information collecting unit 11. Road geometry information and environmental information can be acquired by shooting an intersection to analyze the risk of conflict using a unmanned aerial vehicle such as a drone.

In addition, the image information collecting unit 12 of the information collecting unit 10 collects pedestrian image information using video equipment (for example, CCTV) that monitors an intersection, and provides the pedestrian image information as transverse pedestrian number measurement information.

Also, the vehicle information collecting unit 13 collects vehicle factor information using the VDS equipment. Here, the vehicle factor information may include the location, the approaching speed, the running direction information, the time information when the conflict point passes, the traffic volume of the survey area, and the like.

Next, in order to collect personal information of the pedestrian, the pedestrian information collecting unit 14 acquires the behavior characteristic information of the pedestrian using the personal wearable equipment.

Here, the pedestrian information collecting unit 14 measures the pedestrian's walking behavior information and the heading information using the equipment worn by the pedestrian, and the pedestrian information, the number of steps, the step count, the walking time, Age, gender, and identification information (name, address, resident registration number) of the pedestrian during the walking of the walker. Here, basic information such as age, gender, and identification information can be input directly from the pedestrian and the manager using the input means in advance.

For obtaining the cognitive reaction information, a Depth Perception Test, a Stroop Test, a Sustained Attention Test, a Field Dependency Test, a Divided Attention Test, and a Trail Making Test can be used.

It is preferable that the pedestrian information collecting unit 14 is implemented in a form in which the characteristic of each pedestrian unit can be tracked, and information such as the gaze direction can be extracted and used by using the Google Glass shown in FIG.

Another application is to use the smartphone application to acquire the gait information related to the walking of the pedestrian. Another method is to acquire the pedestrian behavior information using the positioning sensor, acceleration sensor, GPS, etc. have. Here, it is necessary to accurately measure the time at which the walking starts and the time at which the walking starts. In order to measure the start / end time, a separate push button may be added to the equipment for wearing the pedestrian.

Next, the log data generator 20 processes various information collected by the information collecting unit 10 to generate raw data for analyzing the risk of conflict between the pedestrian and the vehicle.

Here, the road data generates an arithmetic factor of the evaluation index for analyzing the risk of conflict between the pedestrian and the vehicle based on the collected road geometry and intersection information, the behavior characteristic information of the pedestrian, and the image information and the vehicle factor information.

2, the arithmetic factor of the evaluation index is calculated from the number of lanes (i), the number of measured persons (j), the estimated conflicting extension distance L1 from the vehicle measurement position, the distance from the vehicle measurement position to the stop line L3, The walking speed v1 to the crossing distance from the curb to the extension of the center of the lane to the center of the lane, the average distance between the vehicles G ), Pedestrian average transit time (t1), average transit pedestrian walking time (t2), vehicle traffic per vehicle (Nk), walking transit per unit time (Np), total vehicle traffic per second (Mg).

The arithmetic factor of the evaluation index generated in this manner is transmitted to the conflict risk evaluation index calculation and analysis unit 30.

The conflict risk evaluation index calculation and analysis section 30 analyzes the log data generated by the log data generation section 20 to calculate a conflict risk assessment index and analyzes the calculated conflict risk assessment index to determine a conflict risk level do.

For example, the conflict risk evaluation index calculation and analysis unit 30 detects the position, speed, and directionality of the vehicle and the pedestrian, estimates the conflict point between them first, calculates TA (Time to Accident) It is desirable to quantify the risk of conflict by estimating the pedestrian safety interval, which is the time difference between the arrival of the pedestrian at the point and the vehicle approaching the point.

More specifically, the conflict risk assessment index calculation and analysis unit 30 may calculate the risk index of the risk to be avoided by using the safety risk assessment index such as a saftey margin, a pedestrian risk index, an exposure index, a severity index, the risk index, and the level of safety are calculated as a conflict risk evaluation index.

로 산출하고, 보행자 위험 지수(pedestrian risk index) =

으로 산출하고, 노출 지수(exposure index) =

로 산출하며, 심각도 지수(severity index) =

,

,

,

으로 산출하며, 위험 지수(risk index) = 노출 지수(exposure index) × 심각도 지수(severity index)로 산출한다.The pedestrian safety margin (Safety Margin) =

And the pedestrian risk index =

, And the exposure index =

, And the severity index =

,

,

,

, And the risk index (= index of exposure) × severity index.

In addition, the level of safety is as follows.

0 ≤ Risk Index <2.86: Very Safe

2.87 ≤ Risk Index <138.05: Safe

138.06 ≤ Risk Index <478.59: Mouse

478.60 ≤ Risk Index <666.55: Unsafe

666. 56 ≤ Risk Index: Very Unsafe

The result of the analysis based on the trade risk assessment index calculated by the trade risk assessment index calculation and analysis unit 30 is provided to the provider 40 as a result of the trade risk analysis.

As a result of the conflicting risk analysis, the providing unit 40 provides an analysis result in the form of synchronizing the road geometry and intersection information, the pedestrian behavior characteristic information, the image information, and the vehicle factor information after the analysis unit time and displays the gait characteristic index Or a risk indicator of conflict.

The present invention has been applied to a pedestrian-vehicle conflict risk analysis system according to the present invention.

FIG. 4 shows a situation where a vehicle, a pedestrian, and the like approaching an intersection are collected by using a dron for external monitoring evaluation, and FIG. 5 shows a result of application of image collection using CCTV. Personal behavioral information was collected using Google Glass to collect personal walking information. By applying these two pieces of information to the pedestrian-vehicle conflict risk analysis system according to the present invention, the risk of conflict between the pedestrian and the vehicle is calculated, and the conflict type between the pedestrian, vehicle, pedestrian and vehicle during the measurement study time (15 minutes) , And PSM were measured.

The result is shown in Fig. 6, and Fig. 7 is an example of cross-over conflict type classification.

The present invention is to analyze the interaction risk of the pedestrian and the vehicle, and to determine the types of conflicts taking into consideration the position, speed, and direction of the pedestrian and the vehicle, and then analyze the risk of conflict. Generally, in foreign countries and Korea, it is a common practice to use a researcher in the case of gait behavior research, In order to reduce the carelessness of drivers or pedestrians through the index of risk of conflict, crossing speed limit regulation, lighting standard, high plateau It can be used for policies such as pedestrian crossing, zigzag road installation, central bus stop pedestrian crossing prohibition signboard display, zigzag line installation for crosswalk entry, installation of slow and careful road surface indication, navigation accident point guide, and pedestrian remaining time indicator .

In particular, the present invention firstly collects the position, speed, and directionality of the vehicle, the pedestrian, estimates the point of conflict, and calculates the PSM as an index of risk of conflict to quantitatively calculate the risk situation. Vehicle-pedestrian cross-risk measurement techniques can be used for improvement of accidents, designation of elderly care area, gait safety diagnosis and behavior analysis.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It is obvious to those who have.

The present invention is effectively applied to a technology for analyzing the risk of conflict between pedestrian and vehicle, and it is applied to technologies used for improvement of accidents, designation of the elderly, designation of gait safety and behavior analysis.

10: Information collecting section
11: Road and Environmental Information Collection Department
12: Image information collecting section
13: Vehicle information collecting section
14: Pedestrian information collecting unit
20:
30: Conflict Risk Assessment Index Calculation and Analysis Department
40: Conflict risk analysis result

Claims (8)

A system for analyzing the risk of conflict between pedestrian and vehicle,
An information collecting unit for collecting information for analyzing conflict risk between a pedestrian and a vehicle;
A data generator for processing the information collected by the information collecting unit to generate raw data for analyzing the risk of collision between the pedestrian and the vehicle;
A conflict risk assessment index calculation and analysis unit for analyzing the log data generated by the log data generation unit to calculate a conflict risk assessment index and analyzing the calculated conflict risk assessment index to determine a conflict risk level; And
And a conflict risk analysis result providing unit for providing information as a result of the analysis by the conflict risk evaluation index calculation and analysis unit,
The calculation and analysis unit of the risk and risk index evaluates the position, speed, and direction of the vehicle and the pedestrian, estimates the conflict point among them first, estimates the time of arrival of the pedestrian at the crossing point to the point of conflict, Estimating the pedestrian safety interval, which is the difference, to quantify the risk of conflict,
The result of the analysis of the risk of conflicting risk provides the analysis result in the form of synchronizing the road geometry and intersection information, the pedestrian behavior characteristic information, the image information and the vehicle factor information after the analysis unit time and displays the gait characteristic index, And,
The information collecting unit acquires road geometry information and environment information through shooting of an intersection to analyze the risk of conflict using an unmanned aerial vehicle, collects pedestrian image information using a CCTV monitoring an intersection, and measures cross pedestrian number Information about location, access speed, direction of travel, time information when a conflict point is passed, and traffic volume information of the survey area are collected using the VDS equipment, and the sight direction information is collected using the Google Glass Wherein the pedestrian behavior characteristic information is acquired using at least one of a positioning sensor, an acceleration sensor, and GPS, or acquiring pedestrian behavior information using a smartphone application, .
The information collecting unit may include a road and environment information collecting unit for collecting environmental information that is information on the geometry and road width, road type, and location of the road; An image information collecting unit for collecting the pedestrian image information by using image equipment for monitoring an intersection; A vehicle information collecting unit for collecting vehicle factor information using the VDS equipment; And a pedestrian information collecting unit for acquiring information on the behavior characteristics of the pedestrian using the personal wearable equipments.
The method of claim 2, wherein the pedestrian information collecting unit uses the pedestrian information and the heading information of the pedestrian to calculate the position of the pedestrian, the number of steps, the step width, the walking time, the information on the walking speed, (Name, address, and resident registration number) of the pedestrian-vehicle between the pedestrian and the vehicle.
The method according to claim 1, wherein the route data generation unit comprises: an evaluation index for analyzing the risk of conflict between the pedestrian and the vehicle based on the road geometry and intersection information collected by the information collection unit, the behavior characteristic information of the pedestrian, Wherein the arithmetic factor is generated by the arithmetic operation unit.
The arithmetic factor of the evaluation index includes a number of lanes, a number of measurement persons, a conflicting estimated extension distance from the vehicle measurement position, a distance from the vehicle measurement position to a stop line, a crossing distance from the curb to the extension line of the center of the lane, The average speed of pedestrians, the average pedestrian crossing time, the average pedestrian crossing time, the number of vehicles passing by the means of transportation, the number of pedestrian crossings per unit time, A total vehicle traffic per second, and an estimated weight on the tolerance weight.
delete The risk index, the risk index, the pedestrian risk index, the exposure index, the severity index, the risk index, , And a level of safety is calculated as a conflict risk evaluation index.
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