JP-2026074748-A - Surrounding environment recognition device and surrounding environment recognition method

JP2026074748AJP 2026074748 AJP2026074748 AJP 2026074748AJP-2026074748-A

Abstract

[Challenge] Improve the accuracy of risk assessment. [Solution] The surrounding environment recognition device 30 has a first calculation unit 322 that calculates the probability of a moving object reaching a divided region A after a unit of time, and the first time when the moving object reaches a divided region A, for each divided region A obtained by dividing the area around the vehicle S into predetermined sizes based on the predicted position where a moving object moves around the vehicle S; a second calculation unit 323 that calculates the second time when the vehicle S reaches each divided region A; and a third calculation unit 324 that calculates a risk level indicating the degree to which the vehicle S and the moving object will come into contact for each divided region A based on the first time and the second time. The third calculation unit 324 adds an additional value corresponding to the probability of reaching the divided region A to the risk level from the unit time before in a divided region A where the time difference between the first time and the second time is less than a threshold, and subtracts a predetermined value from the risk level from the unit time before in a divided region A where no additional value is added. [Selection Diagram] Figure 1

Inventors

笠井勇希

Assignees

いすゞ自動車株式会社

Dates

Publication Date: 20260507
Application Date: 20241021

Claims (10)

An acquisition unit acquires vehicle information, including the speed of the vehicle, and movement prediction information, including predicted position, which predicts the position of moving objects around the vehicle for each unit of time within a predetermined period, for each unit of time. Based on the predicted position, a first calculation unit calculates, for each divided region obtained by dividing the area surrounding the vehicle into predetermined sizes, the probability that the moving body will reach the divided region after the unit time, and the first time the moving body will reach the divided region. A second calculation unit calculates the second time the vehicle arrives at each of the divided regions, It includes a third calculation unit that calculates a risk level indicating the degree to which the vehicle and the moving object come into contact for each divided region, based on the first time and the second time. The third calculation unit, in the divided region where the time difference between the first time and the second time is less than a threshold, adds an additional value corresponding to the probability of the divided region to the risk level from the unit time prior to the current time, and in the divided region where the additional value is not added, subtracts a predetermined value from the risk level from the unit time prior to the current time. A device for recognizing the surrounding environment.
The second calculation unit calculates the second time for each of the divided regions based on the distance between each divided region and the vehicle, the speed of the vehicle, and the maximum acceleration of the vehicle stored in the memory unit. The surrounding environment recognition device according to claim 1.
The third calculation unit adds, in the division region from the division region where the time difference is less than the threshold to the division region within a predetermined range, an additional value corresponding to the probability of the division region where the time difference is less than the threshold and the distance from the division region to the risk level from the current time to the risk level from the unit time prior to the current time. The surrounding environment recognition device according to claim 1.
The first calculation unit calculates the probability based on the probability calculated at a time unit time prior to the current time and the predicted position obtained at the current time. The surrounding environment recognition device according to claim 1.
The first calculation unit calculates a first time based on the first time calculated at a time prior to the current time by the unit time and the predicted position acquired at the current time, if the predicted position is included in the divided region, and calculates a subtracted value as the first time at the current time by subtracting the unit time from the first time calculated at a time prior to the current time by the unit time. The surrounding environment recognition device according to claim 1.
The first calculation unit further calculates the time it takes for the moving body to pass through each of the divided regions based on the predicted position. The surrounding environment recognition device according to claim 1.
The movement prediction information includes a division value obtained by dividing the sum of the total length of the moving body and the length of one side of the divided region by the speed of the moving body. The first calculation unit calculates the passage time based on the passage time calculated at a time prior to the current time by the unit time and the division value obtained at the current time if the predicted position is included in the divided area, and maintains the passage time calculated at a time prior to the current time by the unit time if the predicted position is not included in the divided area. The surrounding environment recognition device according to claim 6.
The second calculation unit calculates the threshold value for each divided region based on the length of one side of the divided region, the sum of the total length of the vehicle stored in the storage unit, and the speed of the vehicle, and the passage time. The surrounding environment recognition device according to claim 6.
The first calculation unit generates a moving object map showing the probability and first time for each of the divided regions, The third calculation unit generates a risk map showing the risk level for each of the divided regions. The surrounding environment recognition device according to claim 1.
A computer executes An acquisition step of acquiring vehicle information including the speed of the vehicle, and predicted movement information including predicted position, which predicts the position of moving objects around the vehicle for each unit of time within a predetermined period, for each unit of time, Based on the predicted position, a first calculation step is performed to calculate, for each divided region obtained by dividing the area around the vehicle into predetermined sizes, the probability that the moving body will reach the divided region after the unit time, and the first time the moving body will reach the divided region. A second calculation step of calculating the second time the vehicle arrives at each of the divided regions, The system includes a third calculation step, which calculates a risk level indicating the degree to which the vehicle and the moving object come into contact for each divided region, based on the first and second time points. In the third calculation step, in the divided region where the time difference between the first time and the second time is less than a threshold, an additional value corresponding to the probability of the divided region is added to the risk level from the unit time prior to the current time, and in the divided region where the additional value is not added, a predetermined value is subtracted from the risk level from the unit time prior to the current time. Methods for recognizing the surrounding environment.

Description

This invention relates to a surrounding environment recognition device and a surrounding environment recognition method. The surrounding environment recognition device described in Patent Document 1 determines, based on the position of the moving object detected by the vehicle's external sensors and the vehicle's control model, a region including the positions of both the vehicle and the moving object at a time after the current time, and the time during which they may exist within that region. Then, based on the determined region and time, the surrounding environment recognition device calculates a risk level indicating the probability of the vehicle coming into contact with the moving object for each region in which the vehicle can move. Japanese Patent Publication No. 2017-224237 This is a diagram illustrating the surrounding environment recognition system 1.This figure shows an example of a processing sequence in the control unit 32.This figure shows an example of a processing sequence for generating a moving object map.This diagram illustrates the general operation of moving arrival prediction information.This figure shows an example of a processing sequence for updating arrival prediction information.This figure shows an example of a processing sequence for deleting arrival prediction information.This figure shows an example of a processing sequence for calculating the contact position.This diagram illustrates the process of calculating the second time point, te.This figure shows an example of a processing sequence for generating a risk map.This figure shows an example of a processing sequence for adding a value to the risk level.This figure shows an example of a processing sequence for subtracting a deduction value from the risk level. <Overview of the surrounding environment recognition system 1> Figure 1 is a diagram illustrating the overview of the surrounding environment recognition system 1. The surrounding environment recognition system 1 shown in Figure 1 comprises a vehicle sensor 10, an external sensor 11, a moving object recognition device 12, a path generation device 20, a driving control device 21, an actuator 22, and a surrounding environment recognition device 30. The surrounding environment recognition system 1 is a system installed in an autonomously driven vehicle (hereinafter referred to as "the vehicle") and has the function of steering the vehicle so that it moves along a path that makes it less likely for the vehicle to come into contact with moving objects in its vicinity. Moving objects include, for example, pedestrians, light vehicles such as bicycles, and other vehicles different from the vehicle. The area around the vehicle is, for example, an area within a radius of 40 meters from the center of the vehicle, but this radius may be different from 40 meters. The vehicle sensor 10 is a sensor for detecting the state in which the vehicle is moving, and includes a speed sensor. For example, the vehicle sensor 10 outputs vehicle information, including the vehicle's speed detected by the speed sensor, to the surrounding environment recognition device 30. The external environment sensor 11 includes a camera, a LiDAR (Light Detection and Ranging) sensor or a millimeter-wave sensor, and a GNSS (Global Navigation Satellite System) receiver. The external environment sensor 11 outputs, for example, the captured image generated by the camera capturing images of the area around the vehicle, the distance between the vehicle and the moving object detected by the LiDAR sensor or millimeter-wave sensor, and the vehicle's position received by the GNSS receiver to the moving object recognition device 12. The moving object recognition device 12 is a device that calculates a predicted position by predicting the movement of moving objects in the vicinity of the vehicle. For example, the moving object recognition device 12 calculates the position and speed of the moving object based on the distance between the vehicle and the moving object and the position of the vehicle, which are acquired from the external sensor 11 at unit time intervals, and calculates the predicted position if the moving object moves from that position at that speed. The unit time is, for example, 0.1 seconds. The moving object recognition device 12 then outputs the movement prediction information, including the calculated predicted position, to the surrounding environment recognition device 30. The route generation device 20 is a device that generates a route for the vehicle to travel. For example, the route generation device 20 obtains the degree of risk, which is the degree to which the vehicle is likely to come into contact with other vehicles in each area surrounding the vehicle, from the surrounding environment recognition device 30. For example, the route generation device 20 generates a route such that the vehicle travels through the area with the lowest risk on the road it is traveling on, and outputs this route to the