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International Journal of Automotive Technology > Volume 18(5); 2017 > Article
International Journal of Automotive Technology 2017;18(5): 923-932.
doi: https://doi.org/10.1007/s12239-017-0090-9
Manjiang Hu1, Jian Wu1, Hongmao Qin1, Yougang Bian1, Biao Xu1, Qing Xu1, Jugang He7, Jianqiang Wang1
1Tsinghua University
7Chongqing Changan Automobile Co. Ltd.
Vehicular collision often leads to serious casualties and traffic congestion, and the consequences are worse for multiple-vehicle collision. Many previous works on collision avoidance have only focused on the case for two consecutive vehicles using on-board sensors, which ignored the influence on upstream traffic flow. This paper proposes a novel coordinated collision avoidance (CCA) strategy for connected vehicles, which has potential to avoid collision and smooth the braking behaviors of multiple vehicles, leading to an improvement of traffic smoothness. Specifically, model predictive control (MPC) framework is used to formulate the CCA into an optimization problem, where the objective is to minimize the total relative kinetic energy density (RKED) among connected vehicles. Monte Carlo simulations are used to demonstrate the effectiveness of proposed CCA strategy by comparison with other two strategies. Among all the three control strategies, the RKED based control strategy shows the best performance of collision avoidance, including the best crash prevention rates (99.2 % on dry asphalt road and 90.5 % on wet asphalt road) and the best control of distance headways between vehicles.
Key Words: Connected vehicle, Coordinated Collision Avoidance (CCA), Total relative kinetic energy density, Model Predictive Control (MPC)
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