公开(公告)号：US11964655B2

公开(公告)日：2024-04-23

申请号：US17766870

申请日：2021-04-12

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu Li ,  Weiming Hu ,  Jinchao Hu ,  Xuefen Zhu

IPC: B60W30/095 ,  G06N3/045 ,  G06N3/0464

CPC classification number: B60W30/0956 ,  G06N3/045 ,  G06N3/0464 ,  B60W2300/125 ,  B60W2420/408 ,  B60W2554/4041 ,  B60W2554/80

Abstract: The present invention discloses a backward anti-collision driving decision-making method for a heavy commercial vehicle. Firstly, a traffic environment model is established, and movement state information of a heavy commercial vehicle and a vehicle behind the heavy commercial vehicle is collected. Secondly, a backward collision risk assessment model based on backward distance collision time is established, and a backward collision risk is accurately quantified. Finally, a backward anti-collision driving decision-making problem is described as a Markov decision-making process under a certain reward function, a backward anti-collision driving decision-making model based on deep reinforcement learning is established, and an effective, reliable and adaptive backward anti-collision driving decision-making policy is obtained. The method provided by the present invention can overcome the defect of lack for research on the backward anti-collision driving decision-making policy for the heavy commercial vehicle in the existing method, can quantitatively output proper steering wheel angle and throttle opening control quantities, can provide effective and reliable backward anti-collision driving suggestions for a driver, and can reduce backward collision accidents.

公开(公告)号：US11648946B2

公开(公告)日：2023-05-16

申请号：US17768765

申请日：2021-04-12

Applicant: SOUTHEAST UNIVERSITY

Inventor： Xu Li ,  Weiming Hu ,  Qimin Xu ,  Kun Wei

IPC: B60W30/18 ,  B60W30/165 ,  B60W40/072 ,  B60W40/114 ,  B60W40/13 ,  B60W50/00 ,  G05D1/02 ,  G08G1/00

CPC classification number: B60W30/18163 ,  B60W30/165 ,  B60W30/18145 ,  B60W40/072 ,  B60W40/114 ,  B60W40/13 ,  B60W50/0098 ,  G05D1/0293 ,  G05D1/0295 ,  G08G1/22 ,  B60W2040/1323 ,  B60W2050/0028 ,  B60W2050/0052 ,  B60W2552/30 ,  B60W2556/60 ,  B60W2710/207 ,  G05D2201/0213

Abstract: The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.