车辆防撞预警系统在近年得到快速发展，有效提升了道路交通的安全性。然而现有避撞算法大多考虑相邻两车间的安全关系，并未涉及前车行为对连续后车造成的不利影响。该文提出一种基于模型预测控制（model predictive control，MPC）的多车纵向协同避撞算法，通过综合考虑队列运动学关系，基于模型预测控制，以总相对动能密度最小作为优化目标，将连续时间优化问题离散化为二次规划的数值计算，以避免或减少队列整体的碰撞损失。最后通过MATLAB进行数值仿真，验证了所提方法的有效性。
Abstract
The rapid development of vehicle collision warning systems has improved the road traffic safety. Current collision avoidance strategies, however, solely focus on the relationship between two consecutive vehicles, while ignoring the influence of avoidance strategies on the traffic flow behind the vehicle. A longitudinal coordinated collision avoidance (CCA) strategy was developed based on model predictive control (MPC) for multiple connected vehicles. The model considers multiple vehicle flow dynamics to minimize the total relative kinetic energy density (RKED) as the objective with and the optimization problem in continuous time discretized into a quadratic programming problem for numerical calculations to avoid or reduce the total loss of vehicle collisions. The effectiveness of this method is verified by MATLAB simulations.
关键词
协同避撞 /
相对动能密度 /
模型预测控制
Key words
coordinated collision avoidance (CCA) /
relative kinetic energy density /
model predictive control
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参考文献
[1] 谢伯元, 王建强, 秦晓辉, 等. 基于车路协同的车辆状态估计方法[J]. 汽车工程, 2014, 36(8):968-973.XIE Boyuan, WANG Jianqiang, QIN Xiaohui, et al. Vehicle state estimation based on V2L system[J]. Automotive Engineering, 2014, 36(8):968-973. (in Chinese)[2] Wang J, Li S E, Zheng Y, et al. Longitudinal collision mitigation via coordinated braking of multiple vehicles using model predictive control[J]. Integrated Computer-Aided Engineering (ICAE), 2015, 22:171-185.[3] Jansson J, Johansson J, Gustafsson F. Decision Making for Collision Avoidance Systems[R]. New York:Society of Automotive Engineers, 2002.[4] Passmann C, Brenzel C, Meschenmoser R. Wireless Vehicle to Vehicle Warning System[R]. New York:Society of Automotive Engineers, 2000.[5] Sengupta R, Rezaei S, Shladover S E, et al. Cooperative collision warning systems:Concept definition and experimental implementation[J]. Journal of Intelligent Transportation Systems, 2007, 11(3):143-155.[6] 李珣, 曲仕茹. 物联网架构下的车辆动态避险路径规划方法研究[J]. 西北工业大学学报, 2012, 30(5):729-733.LI Xun, QU Shiru. An effective differential evolution algorithm for collision avoidance of vehicles under IOT(internet of things)[J]. Journal of Northwestern Polytechnical University, 2012, 30(5):729-733. (in Chinese)[7] Xiang X, Qin W, Xiang B. Research on a DSRC-based rear-end collision warning model[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(3):1054-1065.[8] Li S E, Xu S, Kum D. Efficient and accurate computation of model predictive control using pseudospectral discretization[J]. Neuro Computing, 2015, 16(3):1199-1209.[9] Li S E, Jia Z, Li K, Cheng B. Fast online computation of a model predictive controller and its application to fuel economy-oriented adaptive cruise control[J]. IEEE Transactions on Intelligent Transportation System, 2015, 16(3):1199-1209.[10] Lu X Y, Wang J, Li S E, et al. Multiple-vehicle longitudinal collision mitigation by coordinated brake control[J]. Mathematical Problems in Engineering, 2014(3):1-13.[11] 公路部交通管理局. 中华人民共和国道路交通事故统计年报[R].北京:公安部交通管理局, 2014.The Traffic Management Bureau of the Ministry of public security. The People's Republic of China Road Traffic Accident Statistics[R]. Beijing:The Traffic Management Bureau of the Ministry of Public Security, 2014. (in Chinese)[12] 余志生. 汽车理论[M]. 北京:机械工业出版社, 2009.YU Zhisheng. Automobile Theory[M]. Beijing:China Machine Press, 2009. (in Chinese)[13] 陈家瑞. 汽车构造[M]. 北京:机械工业出版社, 2009.CHEN Jiarui. Automobile Construction[M]. Beijing:China Machine Press, 2009. (in Chinese)
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