理论(学习稳定性)
控制(管理)
国家(计算机科学)
车辆动力学
计算机科学
工程类
运输工程
汽车工程
人工智能
机器学习
算法
作者
Cong Wang,Zhenpo Wang,Lei Zhang,Jun Chen,Dongpu Cao
标识
DOI:10.1109/tits.2024.3368370
摘要
Reducing traffic accidents and associated casualties is a growing concern for modern human society. The secondary or even chain collisions for an unstable vehicle after an initial impact can result in more hazards and fatalities. Passive safety systems such as airbags and seat belts only provide limited level of protection for vehicle occupants, but cannot prevent collision accidents, while active safety systems usually work before the initial collision. Therefore, it is of great significance to develop dedicated post-impact stability control systems to help vehicles quickly restore stability to mitigate and/or avoid secondary collisions. However, the loss of original nonholonomic constraint property and the nonlinearity and saturation of tire forces due to post-impact sideslip, over-spinning, and drifting motions pose great challenges in controller design. Moreover, how to simulate and analyze the collision process and to further construct a simulation environment is the primary problem to solve for enabling controller development. Also, exploring repeatable, effective and low-cost experiment methods lays the foundation for controller verification. This paper aims to provide an overview of the latest technological advancements in collision modeling, control synthesis, and experimental procedures for post-impact stability control. The advantages and disadvantages of different modeling, control and experimental approaches are compared in succession. Finally, the paper discusses the challenges encountered in existing research and the prospects for post-impact active safety control systems.
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