JP2002260192A - Method and device for supporting prevention of collision with pedestrian - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent a vehicle from colliding with a pedestrian and a bicycle due to the delay of detection by an operator, erroneous judgment and operation by properly providing running support information to the vehicle to support the operation by the operator when there is a danger of collision of the vehicle against a movable body such as the pedestrian and bicycle crossing or expected to cross a road. SOLUTION: In a road traffic scene where the vehicle approaches the pedestrian and bicycle crossing or expected to cross the road, the behaviors of the movable body such as the pedestrian and bicycle and the vehicle are predicted to determine the possibility of collision of both of the movable body and the vehicle. If the possibility of collision is high, it is judged whether the objective vehicle can stop at a position before a predicted collision position and, if it is judged that the vehicle cannot stop there, the running support information for supporting the prevention of collision accident is provided to the objective vehicle to support the prevention of collision accident of both the movable body and the vehicle.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a driving support road system (AHS: Advanced Cruise-As).
In a sist Highway System, a pedestrian collision prevention support method and a pedestrian collision prevention method for supporting a target vehicle, for example, to prevent a collision accident with a moving body such as a pedestrian or a cyclist who is crossing or crossing a road. It concerns the device.

[0002]

2. Description of the Related Art In recent years, research and development of AHS aiming at a safe and comfortable road traffic system has been promoted. Among them, as safe driving support services for the purpose of reducing traffic accidents, safe vehicle keeping, obstacle collision prevention, lane keeping,
Services to prevent head-on collisions, right-turn collisions, and cross-pedestrian collisions are being studied. In order to realize these services, it is necessary to provide appropriate information to the driver by performing wireless communication between roadside equipment installed on the roadside and a moving vehicle.

[0003]

Particularly, in a road traffic scene where a vehicle approaches a moving object such as a pedestrian or a bicycle who is crossing or crossing a road, attention is required by a driver of the vehicle by looking aside. Due to the road environment such as lack or poor visibility, there is a problem that there is a risk that a collision accident with a pedestrian or a bicycle always occurs due to a delay in discovery, an error in determination, or an error in operation.

[0004] The present invention has been made in view of the above circumstances, and provides a driving support information providing service to a vehicle having a risk of collision with a moving object such as a pedestrian or a bicycle. It is an object of the present invention to provide a pedestrian collision prevention support method and apparatus thereof that can solve the above-described problems and can enhance the safety of pedestrians, moving objects such as bicycles, and vehicles.

[0005]

SUMMARY OF THE INVENTION In order to achieve the above object, the present invention is directed to a method for preventing pedestrian collision, which is for crossing or crossing a road. By extracting the traveling vehicles approaching the moving body such as pedestrian and bicycle, the behavior of the pedestrian and the moving body such as bicycle and the vehicle are predicted to determine the possibility of collision between the two, and the possibility of collision is determined. If it is high, it is determined whether the target vehicle can be stopped by the expected collision position, and if it is determined that the target vehicle cannot be stopped, driving support information for supporting the target vehicle in preventing a collision accident is provided. It is characterized by providing.

[0006] According to a second aspect of the invention, the pedestrian collision avoidance support device, with respect to a vehicle and pedestrian and the region of interest to help prevent collisions with the mobile such as a bicycle, a vehicle and a pedestrian It is connected to road condition grasping means for acquiring information on moving objects such as moving objects and information on obstacles on the road, and the road condition grasping means. A driving support device to be updated, a vehicle mounted on the vehicle, acquisition of information on the mounted vehicle, provision of driving support information to a driver of the vehicle regarding prevention of a collision accident with a moving body such as a pedestrian, and a vehicle based on the driving support information A vehicle-mounted device for assisting operation; and a road-to-vehicle communication device for mediating information wirelessly between the traveling support device and the vehicle-mounted device. .

According to a third aspect of the present invention, there is provided an area which is connected to the driving support device and which serves to assist in preventing a collision accident between a vehicle and a moving object such as a pedestrian or a bicycle.
It has a road surface condition grasping means for acquiring information such as a road surface condition and a weather condition of the road.

According to a fourth aspect of the present invention, an area which is connected to the driving support device and which serves to assist in preventing a collision accident between a vehicle and a moving object such as a pedestrian or a bicycle is provided.
It has traffic flow control means for acquiring the current signal display state, transition information of the signal display, and the like.

According to a fifth aspect of the present invention, in the driving support device, a vehicle to be supported to prevent a collision accident with a moving body such as a pedestrian or the like, collides with a moving body such as a pedestrian or the like. It is characterized in that the necessity of outputting driving assistance information on an accident is determined.

[0010] According to a sixth aspect of the present invention, in the vehicle-mounted device,
And characterized in that the vehicle of interest to help prevent collisions with the moving body such as a pedestrian, to determine the necessity of output of the drive support information relating to a collision accident prevention and the moving body such as a pedestrian it is intended to.

According to a seventh aspect of the present invention, the driving support device and the on-vehicle device are provided for a vehicle, such as a pedestrian, that supports the prevention of a collision accident with the pedestrian. It is characterized in that the necessity of outputting the driving support information regarding the prevention of a collision accident with the vehicle is determined.

[0012]

Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 shows, as an example, a traffic situation in a situation where there is a risk of collision with a pedestrian H crossing a pedestrian crossing when a service target vehicle A approaching an intersection makes a left turn. As shown in FIG. 1, a device for realizing the pedestrian collision prevention support method of the present invention includes a road condition grasping sensor 1, a road surface condition grasping sensor 2, a traffic flow control device 3 such as a traffic light, and a road-vehicle communication device 4. And each device such as the driving support device 5.

That is, the operation of each of the above-described element devices will be described. The road condition grasping sensor 1 uses the information (for example, position, speed, acceleration,
, Etc.) and information (for example, position, size, etc.) related to obstacles. The road surface condition grasping sensor 2 acquires information such as a road surface condition (for example, dryness, wetness, etc.) of a road, a weather condition (for example, weather, wind direction, wind speed, rainfall, snowfall, etc.). These sensors may be in the form of, for example, visible light, infrared light, laser, or the like.

The traffic flow control device 3 such as a traffic light acquires the current signal display state and transition information of the signal display. The detecting devices such as the road condition grasping sensor 1 and the road surface condition grasping sensor 2 and the traffic flow control device 3 such as a traffic light are connected to the driving support device 5 and have a constant period (for example, 100 ms).
For each ec), information on the service target area and road traffic conditions in the vicinity thereof is acquired and transmitted to the driving support device 5. The road-to-vehicle communication device 4 has a role of mediating information by radio (optical or radio wave communication) with an in-vehicle device mounted on the vehicle.

By the way, detection devices such as the road condition grasping sensor 1 and the road surface condition grasping sensor 2 and the road-vehicle communication device 4
Needs to these detection range and coverage is installed so as to include the entire area of the service target area. Driving support device 5
Is a device that is the core of pedestrian collision prevention support, and implements all or a part of a program for implementing the pedestrian collision prevention support method, and is installed for each service target area. The information obtained from each of the above-described detection sensors is collected, and stored and updated in a database in the driving support device 5.

The driving support device 5 executes processing according to the processing flow of the pedestrian collision prevention method as shown in FIG. 2 based on such information, and it is necessary to output the driving support information to the service target vehicle. Judge the gender.

Some of the processes of the pedestrian collision prevention support method are performed by elemental devices other than the travel support device 5 (each detection sensor,
OBE can be mounted at equal). The vehicle-mounted device mounted on the vehicle transmits information (moving distance, speed, acceleration, steering angle, braking state, etc.) regarding the traveling behavior of the vehicle collected on the vehicle side to the road-to-vehicle at regular intervals (for example, 100 msec). The information is transmitted to the driving support device 5 via the communication device 4. As a result, the driving support device 5 transmits the road-vehicle communication device 4
Receiving the driving support information (e.g., providing pedestrian presence information, warning against the risk of collision with pedestrians, emergency operation support to avoid collision with pedestrians, etc.) Depending on the content of the driving support information and the functions of the vehicle-mounted device, the driver is notified by means such as characters, voices, and alarm sounds, and the vehicle is braked and steered.

Next, the overall operation of the pedestrian collision prevention support device shown in FIG. 1 will be described with reference to the processing flowchart of the pedestrian collision prevention method shown in FIG. In the traffic environment as shown in FIG. 1, in the driving environment information acquisition processing, the driving environment information of the service target area is acquired at regular intervals by the roadside road condition grasping sensor 1 and the road surface condition grasping sensor 2, and the traveling support device Send to 5. Vehicles in the service area,
When a pedestrian enters, the road condition grasping sensor 1 detects these, acquires information on these movement behaviors, and transmits the information to the driving support device 4. When the vehicle is equipped with an on-board unit, information on the running behavior of the vehicle is transmitted to the driving support device 5 at regular intervals via the road-to-vehicle communication device 4.

On the other hand, in the support target extraction processing, the service target vehicle A, the pedestrian H, and the surroundings that affect the collision prevention support are extracted from the driving environment information of the service target area acquired in the driving environment information acquisition processing. Out the traveling vehicle of
The mobile behavior information, information on road surface conditions and weather conditions which affect the prediction of the mobile behavior are extracted. In the driving situation as shown in FIG. 1, information on the pedestrian H and the vehicle A approaching the pedestrian H is extracted from the traveling environment information, and information on the vehicles B and C that do not affect the pedestrian H is Do not extract.

The history of the movement behavior information of the vehicle A and the pedestrian H extracted in the support target extraction processing and the movement behavior information of the vehicle and the pedestrian acquired and extracted in the past control cycle are also stored. At the same time, a vehicle behavior prediction process and a pedestrian behavior prediction process are performed. Subsequently, a collision possibility determination process and a stop possibility determination process are performed. When it is determined that the driving support information needs to be output as a result of these processes, the driving support information is output from the driving support device 4 to the service target vehicle A in the driving support information processing. The content and form of the driving support information vary depending on the level of support for collision prevention, the vehicle-mounted device mounted on the service target vehicle A, and the equipment installed on the roadside. For example, it varies depending on the lane in which the roadside service target vehicle A runs. In the case where the display board 6 is installed, the presence of a pedestrian on the course of the service target vehicle A or the pedestrian walking before the service target vehicle A passes near the location where the variable display board 6 is installed. The possibility of collision with the person is displayed as character information.

When the service target vehicle A has a vehicle-mounted device corresponding to the driving support information, an alarm sound, voice output, and character information display are transmitted via the road-vehicle communication device 5. When the service target vehicle A has a control function corresponding to the driving support information, a control command such as steering and braking of the vehicle is transmitted to the service target vehicle A via the road-to-vehicle communication device 5. . These series of processes are started and executed at a constant control cycle (for example, 100 mesc), and the contents of each process in the process flow are described below.

In the traveling environment information acquisition processing, information obtained from various devices and sensors installed on the road side, various devices and sensors mounted on the vehicle, and the like is acquired. The information to be obtained is information on an area (hereinafter, referred to as a service target area) serving as a support for preventing a collision accident between a pedestrian and a vehicle and road traffic conditions in the vicinity thereof. Specifically, migration behavior information of the vehicle and pedestrians (e.g., position, velocity, acceleration, etc.), road of the road surface condition (e.g., dry, wet, etc.), weather conditions (e.g., weather, wind direction, wind speed, precipitation Quantity, snowfall, etc.).

[0023] In support object information extracting process, from the travel environment information of the service target area acquired by the travel environment information acquisition process, the vehicle of interest to assist the collision prevention (hereinafter, service target vehicle) and pedestrians, Then, surrounding traveling vehicles that affect the collision prevention support are extracted, and their movement behavior information, information on road surface conditions and weather conditions that affect the prediction of these movement behaviors are extracted. The moving behavior information of the vehicle and the pedestrian stores a certain amount of information extracted in the past as history information, and registers the information extracted from the history information for each control cycle in which this process is started, and records the history information. Delete the oldest information in.

In the vehicle behavior prediction processing and the pedestrian behavior prediction processing, based on the history of the movement behavior information of the vehicle and the pedestrian acquired / extracted in the current control cycle, the future movement course of the vehicle and the pedestrian is determined. The position of the vehicle and the pedestrian are predicted at predetermined prediction time intervals.

In the vehicle behavior prediction method, the predicted course is narrowed according to the distance from the service target area, and the service target vehicle arrives at a pedestrian crossing area (when a pedestrian crossing exists) or an area near a pedestrian. A predicted time and a predicted existence position are calculated.

At this time, when the road structure of the service target area can take a plurality of routes as in the intersection shown in FIG. 3, when the vehicle exists at a position sufficiently distant from the intersection, as shown in FIG. Next, predicted course patterns are created for all possible courses of the vehicle at that time. At the time the vehicle enters the lane change regulation region of intersection closer to the intersection, narrow the predicted route as shown in FIG. 3 (b). When the information of the direction indicator is obtained from the vehicle, and when the vehicle that can further narrow down the predicted course enters the intersection, the final predicted course is determined as shown in FIG. Several methods are conceivable for predicting the position of the vehicle at each predicted time on the predicted course. For example, at a position distant from the intersection as shown in FIGS. 3A and 3B, Predicted by applying to the average running behavior modeled from the running performance data of the vehicle in the service target area collected in advance, and obtained from the vehicle at the position where the vehicle approaches the pedestrian as shown in FIG. There is a method of predicting with a constant velocity motion model using speed information or a Kalman filter.

The prediction of the behavior of the pedestrian is as shown in FIG.
It is performed on the assumption that a pedestrian crosses or is about to cross a road. When the pedestrian crossings C1 to C4 exist, the pedestrian crossings are predicted for all the traversable pedestrian crossings existing within a certain predicted distance R from the pedestrian. In the case where the road structure of the service target area and the location of the pedestrian are as shown in FIG. 4, the pedestrian crossings C1 and C2 existing within the predicted distance R from the pedestrian are set as the targets of the course prediction. The predicted course of the pedestrian at this time is shown in FIG.
RT1 and RT2.

When the pedestrian is located at the position shown in FIG.
The route of “moving to the side of the pedestrian crossing” → “waiting for a traffic light” (when a traffic signal is present) → “crossing the pedestrian crossing” is composed of line segments. As shown in FIG. 4, the predicted course to the pedestrian crossing is obtained by a straight line from the current position to the entrance point of the pedestrian crossings C1 and C2. I do. Based on the predicted time of arrival at the signal waiting position and the signal transition information obtained from the traffic light, the time of stopping at the signal waiting is based on the time from the stop at the signal waiting position until the signal display changes to blue. It is assumed that the time is predicted and the pedestrian starts crossing when the signal is switched. The course prediction when traversing the pedestrian crossings C1 and C2 is assumed to traverse a straight line from the signal waiting position to the nearest exit point of the pedestrian crossing. However, in the course prediction after the pedestrian starts crossing, it is predicted to take a straight course in the direction of the pedestrian movement vector obtained from the pedestrian position or speed information.

There are several methods for estimating the position of a pedestrian at each predicted time on a predicted course. For example, a method of estimating the position of a pedestrian using a constant velocity motion model using pedestrian speed information is available. There is. If the pedestrian's speed information cannot be obtained, the instantaneous speed is obtained from the movement amount from the position information acquired in the previous control cycle using the pedestrian's position information. However, since the pedestrian may stop like a stop behavior, if the pedestrian's speed or instantaneous speed is 0, the maximum speed obtained from the stored history information of the pedestrian's movement behavior is retained. In addition, a method of using this for prediction is also required.

In the collision possibility determination processing, the possibility that both the pedestrian and the service target vehicle are present at the predicted position at each predicted time is predicted, and the degree of the possibility that both exist on the road plane is considered. Is represented as a possibility of collision, and when this value exceeds a certain threshold value, it is determined that there is a possibility of collision between the two.

There are several methods for estimating the possibility of the existence of a vehicle. For example, as shown in FIG. 5, the existence area X, Y, There is a method of considering the distribution of Z as a constant rectangular parallelepiped.

The method of predicting the possibility of the presence of a pedestrian is such that the predicted position of the pedestrian is determined by irregular movement of the pedestrian or the like.
Since the prediction error is considered to be larger than that of the vehicle, it is more important to stochastically determine the possibility of the pedestrian at each predicted position and to represent the probability as a distribution. As a function representing the distribution of the possibility of existence, several methods such as a normal distribution function are conceivable. For example, as shown in FIG. There is a method of using an elliptical cone representing a distribution in which the possibility of existence is reduced. As shown in FIG. 6, the size of the bottom surface of the existence possibility (elliptical cone) becomes larger as the predicted movement amount becomes larger around each predicted position on the predicted path of the pedestrian obtained by the above-described pedestrian behavior prediction. Increase the radius of the bottom according to a certain ratio.
The ratio of increasing the radius of the bottom surface of the possibility of existence (elliptical weight) is determined by calculating the increase ratio of the radius RY3 of the pedestrian's predicted course direction such that RY3 of the pedestrian's predicted course direction becomes the long axis of the ellipse. It is made larger than the increase rate of the radius RX3 in the direction perpendicular to the predicted course. This is because the prediction error in the predicted course direction is considered to be larger than the prediction error in the direction perpendicular to the predicted course.

Incidentally, detection devices such as the road condition grasping sensor 1 and the road surface condition grasping sensor 2 and the road-vehicle communication device 4
Must be installed so that these detection ranges and communication ranges include the entire service target area. Driving support device 5
Is a device that is the core of pedestrian collision prevention support, and implements all or a part of a program for implementing the pedestrian collision prevention support method, and is installed for each service target area. The information obtained from each of the above-described detection sensors is collected, and stored and updated in the database of the driving support device 5.

The driving support device 5 executes processing based on such information in accordance with the processing flow of the pedestrian collision prevention method as shown in FIG. 2, and is required to output driving support information to the service target vehicle. Judge the gender.

Some of the processes of the pedestrian collision prevention support method are performed by component devices (each detection sensor,
It is also possible to mount it on a vehicle-mounted device. The vehicle-mounted device mounted on the vehicle transmits information (moving distance, speed, acceleration, steering angle, braking state, etc.) on the traveling behavior of the vehicle collected on the vehicle side at regular intervals (for example, 100 msec) between the road and the vehicle. The information is transmitted to the driving support device 5 via the communication device 4. As a result, the driving support device 5 to the road-to-vehicle communication device 4
Receiving the driving support information (e.g., providing pedestrian presence information, warning about the risk of collision with pedestrians, emergency operation support for avoiding collision with pedestrians, etc.) Depending on the content of the driving support information and the functions of the vehicle-mounted device, the driver is notified by means such as characters, voices, and warning sounds, and the vehicle is braked and steered.

Next, the overall operation of the pedestrian collision prevention support device shown in FIG. 1 will be described with reference to the processing flowchart of the pedestrian collision prevention method shown in FIG. In the traffic environment as shown in FIG. 1, in the driving environment information acquisition processing, the driving environment information of the service target area is acquired at regular intervals by the roadside road condition grasping sensor 1 and the road surface condition grasping sensor 2, and the traveling support device Send to 5. Vehicles in the service area,
When a pedestrian enters, the road condition grasping sensor 1 detects them, obtains information on these movement behaviors, and transmits the information to the driving support device 5. When the vehicle is equipped with an on-vehicle device, information on the running behavior of the vehicle is transmitted to the driving support device 5 at regular intervals via the road-to-vehicle communication device 4.

On the other hand, in the support target extraction process, the service target vehicle A, the pedestrian H, and the surroundings that affect the collision prevention support are extracted from the driving environment information of the service target region obtained in the driving environment information obtaining process. Out the traveling vehicle of
The mobile behavior information, information on road surface conditions and weather conditions which affect the prediction of the mobile behavior are extracted. In the driving situation as shown in FIG. 1, information on the pedestrian H and the vehicle A approaching the pedestrian H is extracted from the traveling environment information, and information on the vehicles B and C that do not affect the pedestrian H is Do not extract.

The history of the movement behavior information of the vehicle A and the pedestrian H extracted in the support target extraction processing and the movement behavior information of the vehicle and the pedestrian acquired and extracted in the past control cycle are also stored. At the same time, a vehicle behavior prediction process and a pedestrian behavior prediction process are performed. Subsequently, a collision possibility determination process and a stop possibility determination process are performed. When it is determined that the driving support information needs to be output as a result of these processes, the driving support information is output from the driving support device 5 to the service target vehicle A in the driving support information processing. The content and form of the driving support information vary depending on the level of support for collision prevention, the vehicle-mounted device mounted on the service target vehicle A, and the equipment installed on the roadside. For example, it varies depending on the lane in which the roadside service target vehicle A runs. In the case where the display board 6 is installed, the presence of a pedestrian on the course of the service target vehicle A or the pedestrian walking before the service target vehicle A passes near the location where the variable display board 6 is installed. The possibility of collision with the person is displayed as character information.

When the service target vehicle A has an on-board unit corresponding to the driving support information, an alarm sound, voice output, and character information display are transmitted via the road-vehicle communication device 5. When the service target vehicle A has a control function corresponding to the driving support information, a control command such as steering and braking of the vehicle is transmitted to the service target vehicle A via the road-to-vehicle communication device 5. . These series of processes are started and executed at a constant control cycle (for example, 100 mesc), and the contents of each process in the process flow are described below.

In the traveling environment information acquisition processing, information obtained from various devices and sensors installed on the road side, various devices and sensors mounted on the vehicle, and the like is acquired. The information to be obtained is information on an area (hereinafter, referred to as a service target area) serving as a support for preventing a collision accident between a pedestrian and a vehicle and road traffic conditions in the vicinity thereof. Specifically, information on the movement behavior of vehicles and pedestrians (eg, position, speed, acceleration, etc.), road surface conditions (eg, dry, wet, etc.), weather conditions (eg, weather, wind direction, wind speed, rainfall) Quantity, snowfall, etc.).

In the support target information extraction process, a vehicle (hereinafter referred to as a service target vehicle), a pedestrian, or a vehicle to be used to assist in preventing a collision accident is selected from the traveling environment information of the service target region acquired in the traveling environment information acquisition process. Then, surrounding traveling vehicles that affect the collision prevention support are extracted, and their movement behavior information, information on road surface conditions and weather conditions that affect the prediction of these movement behaviors are extracted. The moving behavior information of the vehicle and the pedestrian stores a certain amount of information extracted in the past as history information, and registers the information extracted from the history information for each control cycle in which this process is started, and records the history information. Delete the oldest information in.

In the vehicle behavior prediction processing and the pedestrian behavior prediction processing, based on the history of the movement behavior information of the vehicle or the pedestrian acquired / extracted in the current control cycle, the future movement course of the vehicle or the pedestrian is determined. The position of the vehicle and the pedestrian are predicted at predetermined prediction time intervals.

According to the vehicle behavior prediction method, the predicted course is narrowed according to the distance from the service target area, and the service target vehicle arrives at a pedestrian crossing area (when a pedestrian crossing exists) or an area near a pedestrian. A predicted time and a predicted existence position are calculated.

At this time, when the road structure of the service target area can take a plurality of routes as in the intersection shown in FIG. 3, when the vehicle exists at a position sufficiently distant from the intersection, as shown in FIG. Next, predicted course patterns are created for all possible courses of the vehicle at that time. When the vehicle approaches the intersection and enters the restricted lane change area at the intersection, the predicted course is narrowed as shown in FIG. 3B. When the information of the direction indicator is obtained from the vehicle, and when the vehicle that can further narrow down the predicted course enters the intersection, the final predicted course is determined as shown in FIG. Several methods are conceivable for predicting the position of the vehicle at each predicted time on the predicted course. For example, at a position distant from the intersection as shown in FIGS. 3 (a) and 3 (b), Prediction is performed by applying the model to the average driving behavior modeled from the driving performance data of the vehicle in the service target area collected in advance, and the position is obtained from the vehicle at the position where the vehicle approaches the pedestrian as shown in FIG. There is a method of predicting with a constant velocity motion model using speed information or a Kalman filter.

The behavior of the pedestrian is predicted as shown in FIG.
It is performed on the assumption that a pedestrian crosses or is about to cross a road. When the pedestrian crossings C1 to C4 exist, the pedestrian crossings are predicted for all the traversable pedestrian crossings existing within a certain predicted distance R from the pedestrian. In the case where the road structure of the service target area and the location of the pedestrian are as shown in FIG. 4, the pedestrian crossings C1 and C2 existing within the predicted distance R from the pedestrian are set as the targets of the course prediction. The predicted course of the pedestrian at this time is shown in FIG.
RT1 and RT2.

[0046] Then, the location of the pedestrian, the prediction of the movement path of a pedestrian when a position shown in Figure 4,
The route of “moving to the side of the pedestrian crossing” → “waiting for a traffic light” (when a traffic signal is present) → “crossing the pedestrian crossing” is composed of line segments. As shown in FIG. 4, the predicted course to the pedestrian crossing is obtained by a straight line from the current position to the entrance point of the pedestrian crossings C1 and C2. I do. Based on the predicted time of arrival at the signal waiting position and the signal transition information obtained from the traffic light, the time of stopping at the signal waiting is based on the time from the stop at the signal waiting position until the signal display changes to blue. It is assumed that the time is predicted and the pedestrian starts crossing when the signal is switched. The course prediction when traversing the pedestrian crossings C1 and C2 is assumed to traverse a straight line from the signal waiting position to the nearest exit point of the pedestrian crossing. However, in the course prediction after the pedestrian starts crossing, it is predicted to take a straight course in the direction of the pedestrian movement vector obtained from the pedestrian position or speed information.

There are several methods for estimating the position of a pedestrian at each predicted time on a predicted course. For example, a method for estimating the position of a pedestrian using a constant velocity motion model using pedestrian speed information is available. There is. If the pedestrian's speed information cannot be obtained, the instantaneous speed is obtained from the movement amount from the position information acquired in the previous control cycle using the pedestrian's position information. However, since the pedestrian may stop like a stop behavior, if the pedestrian's speed or instantaneous speed is 0, the maximum speed obtained from the stored history information of the pedestrian's movement behavior is retained. In addition, a method of using this for prediction is also required.

In the collision possibility determination process, the possibility of the presence of both the pedestrian and the service target vehicle at the predicted position at each predicted time is predicted, and the degree of the possibility that both exist on the road plane is considered. Is represented as a possibility of collision, and when this value exceeds a certain threshold value, it is determined that there is a possibility of collision between the two.

There are several methods for estimating the possibility of the existence of a vehicle. For example, as shown in FIG. 5, the existence area X, Y, There is a method of considering the distribution of Z as a constant rectangular parallelepiped.

The method of predicting the possibility of the presence of a pedestrian is such that the predicted position of the pedestrian is determined by irregular movement of the pedestrian or the like.
Since the prediction error is considered to be larger than that of the vehicle, it is more important to stochastically determine the possibility of the pedestrian at each predicted position and to represent the probability as a distribution. As a function representing the distribution of the possibility of existence, several methods such as a normal distribution function are conceivable. For example, as shown in FIG. There is a method of using an elliptical cone representing a distribution in which the possibility of existence is reduced. As shown in FIG. 6, the size of the bottom surface of the existence possibility (elliptical cone) becomes larger as the predicted movement amount becomes larger around each predicted position on the predicted path of the pedestrian obtained by the above-described pedestrian behavior prediction. Increase the radius of the bottom according to a certain ratio.
The ratio of increasing the radius of the bottom surface of the possibility of existence (elliptical weight) is determined by calculating the increase ratio of the radius RY3 of the pedestrian's predicted course direction such that RY3 of the pedestrian's predicted course direction becomes the long axis of the ellipse. It is made larger than the increase rate of the radius RX3 in the direction perpendicular to the predicted course. This is because the prediction error in the predicted course direction is considered to be larger than the prediction error in the direction perpendicular to the predicted course.

It is determined whether there is a time zone in which the pedestrian and vehicle existence probability distributions thus determined overlap. If there is a time period in which the existence probability distributions overlap, the time period is determined to be a certain value. The analysis is performed at every determination cycle (for example, 100 msec), and the size of the overlap of the existence possibility distributions of both (FIG.
The maximum value of PR) is expressed as the possibility of collision. If this value exceeds a predetermined threshold value, it is determined that there is a possibility of collision between the two, and the predicted position of both at that time is set as the predicted collision position L.

As a result of this processing, if it is determined that the possibility of collision is equal to or less than the threshold value and there is no possibility of collision, a series of pedestrian collision prevention support processing ends.

In the stop possibility determination processing, it is determined whether or not the service target vehicle can be stopped by the collision predicted position obtained in the above-described collision possibility determination processing based on the movement behavior information of the service target vehicle. The distance at which the service target vehicle stops due to braking (hereinafter referred to as a stoppable distance) and the distance between the service and the current position of the target vehicle to the collision prediction position obtained by the above-described collision possibility determination processing (hereinafter the collision prediction distance) If the predicted collision distance is shorter than the stoppable distance, it is determined that the service target vehicle cannot be stopped by the predicted collision position.

In this case, several methods are available for calculating the stoppable distance. For example, the following formula (1) is used to model the deceleration stop behavior of the vehicle, as described below. There is a method in which a braking distance La of the vehicle is obtained based on the speed information, and this is set as a stoppable distance. La = Va · Td + (Va · Tr−1 / 6α · Tr ² ) + 1 / (2α) · (Va−α · Tr / 2) ² (1) where, Va: vehicle speed α: determine braking distance Deceleration Td: reaction time Tr: braking rise time

In this case, the speed Va of the vehicle uses the current speed acquired in the support target information extracting process. It is conceivable that several values are used for the deceleration α, the reaction time Td, and the braking rise time Tr, which determine the braking distance La, depending on the support level of collision prevention. For example, the possibility of a collision with a pedestrian is
When an alarm is generated with a higher degree of urgency than that provided as information, the deceleration α is set to 5 m / s ² and the reaction time Td is set to 1.
0 s, and the braking rise time Tr is set to 0.5 s. Furthermore, when it is difficult for the driver to operate to avoid collision and the service target vehicle has a control function, to assist the control operation, the deceleration α is set to 5 m / s ² , the reaction time Td, and the braking. A method of setting the rise time Tr to 0.3 s can be considered.

As a result of this processing, when it is determined that the service target vehicle can be stopped by the predicted collision position, a series of pedestrian collision prevention support processing ends.

In the driving support information output processing, information (hereinafter, driving support information) for avoiding collision with a pedestrian is output to the service target vehicle.

The content of such driving support information varies depending on the support label for preventing collision, the equipment mounted on the service target vehicle, and the equipment installed on the roadside. Textual information, audio information,
It is transmitted to the driver by means such as a warning sound. In an urgent situation where a collision cannot be avoided by the driving operation by the driver, a control command such as steering and braking of the service target vehicle is output.

[0059]

As described above, according to the present invention, in a road traffic scene in which a vehicle approaches a moving object such as a pedestrian or a cyclist who is crossing or crossing the road, the pedestrian or the cyclist may be used. Properly providing driving support information to vehicles that are at risk of collision with moving objects to assist the driver's driving, and walking caused by a delay in finding the driver, an error in judgment, or an error in operation It is effective in preventing a collision accident with a mobile object such as a person and a bicycle.

[Brief description of the drawings]

FIG. 1 is a diagram showing an example of a traffic situation at an intersection where a pedestrian collision prevention support device of the present invention is installed.

FIG. 2 is a flowchart showing the overall processing operation of the pedestrian collision prevention support device;

FIGS. 3A, 3B, and 3C are diagrams showing predicted course patterns in a road structure of a service target area at an intersection of a plurality of routes;

FIG. 4 is a diagram showing a pedestrian behavior prediction state;

FIG. 5 is a diagram showing a predicted state of a vehicle presence possibility;

FIG. 6 is a diagram showing a distribution of the possibility of existence of a pedestrian and a vehicle;

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Road condition grasping sensor 2 Road surface condition grasping sensor 3 Traffic flow control device such as traffic light 4 Road-vehicle communication device 5 Driving support device 6 Variable display board A Vehicle (target vehicle) B Vehicle C Vehicle H Pedestrian

 ──────────────────────────────────────────────────続 き Continued on the front page (72) Inventor Hideo Sugawara 3-1-1, Toyosu, Koto-ku, Tokyo Ishikawajima-Harima Heavy Industries, Ltd. Tokyo Engineering Center F-term (reference) 5H180 AA01 BB02 BB04 BB20 EE13 EE14 JJ07 LL01 LL07 LL08 LL09 LL15

Claims (7)

[Claims] 1. Extracting a pedestrian and a bicycle who are crossing or trying to cross a road and a traveling vehicle approaching the road, and predicting the behavior of the pedestrian and the vehicle to determine the possibility of collision between the two, If the possibility of collision is high, it is determined whether the target vehicle can be stopped by the expected collision position.If it is determined that the target vehicle cannot be stopped, it is necessary to assist the target vehicle in preventing a collision accident. A pedestrian collision prevention support method, characterized by providing driving support information. 2. Information relating to a moving object such as a vehicle and a pedestrian and information relating to an obstacle on a road is provided for an area which is a target for supporting prevention of a collision accident between the vehicle and a moving object such as a pedestrian and a bicycle. A driving support device connected to the road condition grasping means for acquiring, the road condition grasping device, and accumulating / updating the information acquired by the road condition grasping device in a database at regular intervals; obtaining information and providing the driving support information about collision prevention with the moving body such as a pedestrian to the driver of the vehicle, and a vehicle-mounted device to provide support for vehicle operation by the driving support information, the driving support apparatus and the vehicle-mounted device A road-vehicle communication device that mediates information by wireless between the device and a pedestrian collision prevention support device. 3. Information on road surface conditions, weather conditions, and the like regarding an area which is connected to the driving support device and which serves to assist in preventing a collision accident between a vehicle and a moving object such as a pedestrian or a bicycle. The pedestrian collision prevention support device according to claim 2, further comprising a road surface condition grasping unit that acquires the information. 4. A current signal display state and a transition of a signal display for an area which is connected to the driving support device and which serves to assist in preventing a collision accident between a vehicle and a moving object such as a pedestrian or a bicycle. 3. The pedestrian collision prevention support device according to claim 2, further comprising a traffic flow control unit that acquires information and the like. 5. The vehicle according to claim 1, wherein the driving support device is provided for supporting a vehicle that assists in preventing a collision with a moving body such as a pedestrian.
4. The method according to claim 2, wherein it is necessary to output driving assistance information relating to a collision with a moving object such as a pedestrian.
Or the pedestrian collision prevention support device according to 4. 6. The vehicle-mounted device according to claim 1, wherein said vehicle-mounted device outputs driving support information relating to a vehicle to be supported for preventing a collision accident with a moving body such as a pedestrian. The pedestrian collision prevention assistance device according to claim 2, wherein the necessity of the pedestrian collision is determined. 7. The driving support device and the vehicle-mounted device are adapted to drive a vehicle that is to assist in preventing a collision accident with a moving body such as a pedestrian, etc. The pedestrian collision prevention support device according to claim 2, wherein the necessity of outputting the support information is determined.