[1]LIN Guoqing,XIONG Haocheng,XU Hao,et al.Vehicle Active Collision Avoidance Considering Road Adhesion Coefficient[J].Journal of Zhengzhou University (Engineering Science),2026,47(XX):1-9.[doi:10.13705/j.issn.1671-6833.2026.03.001]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
47
Number of periods:
2026 XX
Page number:
1-9
Column:
Public date:
2026-09-10
- Title:
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Vehicle Active Collision Avoidance Considering Road Adhesion Coefficient
- Author(s):
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LIN Guoqing1 ; XIONG Haocheng1 ; XU Hao2 ; QING Yu1 ; GUO Yan1
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1. Chan g′an University, Key Laboratory of Transportation New Energy Development, Application and Automotive Energy Conservation of Shanxi Province, Xi′an 710064, China; 2. BYD Automobile Industry Company Limited, Shenzhen 518100, China
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- Keywords:
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active collision avoidance; unscented kalman filter; adhesion coefficient; decoupling control; joint simulation
- CLC:
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U461.91
- DOI:
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10.13705/j.issn.1671-6833.2026.03.001
- Abstract:
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To improve the effectiveness of the active collision avoidance strategy, a risk assessment method for collision time margin is proposed. The three-degree-of-freedom vehicle model and the Dugoff tire model were established, and the state parameters were calculated to obtain the normalized tire force. The pavement adhesion coefficient estimator is designed based on the traceless Kalman filtering algorithm, and the effectiveness of the adhesion coefficient estimator is verified through simulation. The road adhesion coefficient was added to the safety distance model to address the limitations of the traditional collision avoidance model, which only considers the position and the vehicle movement conditions. Generate the active collision avoidance path using a fivetic polynomial and calculate the required safe steering distance. Based on the risk assessment method, a collision avoidance mode selection strategy was designed, enabling intelligent vehicles to select the appropriate collision avoidance mode according to the kinematic relationship with obstacles. The longitudinal control based on the vehicle inverse dynamic model and the lateral control using MPC are adopted to decouple the control of intelligent vehicles. The effectiveness of the collision avoidance strategy was verified through the joint simulation experiment of Carsim and Simulink and the real vehicle test.