基于实际换挡规律的卡车列队行驶起步控制
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摘要
为了解决卡车列队行驶起步过程中的控制问题,在车辆行驶3.5万公里的实验数据中提取456段起步过程的挡位数据,对该数据中各挡位的使用情况进行统计与分析.根据统计结果制定相应的换挡规则,利用自适应模糊控制算法设计车辆列队行驶的控制模型,在模型中通过跟随车辆的挡位信息对模糊控制器的输入量进行加权系数调整,提高控制算法的自适应性,通过TruckSim和Matlab的联合仿真,将实车实验数据作为头车模拟工况,模拟3辆卡车在车联网环境下的列队起步过程,仿真结果表明起步过程中的行驶间距误差可以控制在车辆单位时间内行驶距离的5%以内,具有一定的控制精度.
456segments gear status data in the start process were extracted from the experiment vehicle traveling 35,000 kilometers in order to solve the starting control problem of platooning trucks.The corresponding gearshift rule was developed with the statistics and analysis.The control model of vehicle platoon was established by using adaptive fuzzy control algorithm.The weight coefficients were decided through the gear status information of the following vehicle.They were used to adjust the input scale of fuzzy controller in order to improve the adaptability of control algorithm.Through co-simulation of TruckSim and Matlab,three trucks platoon was simulated in the case of vehicle-vehicle communication environment using the test data from real vehicle as the simulation conditions of the leader truck.The simulation results show that the travel space error between two vehicles can be controlled within 5percent of driving distance in unit time.The control model has certain control accuracy.
456segments gear status data in the start process were extracted from the experiment vehicle traveling 35,000 kilometers in order to solve the starting control problem of platooning trucks.The corresponding gearshift rule was developed with the statistics and analysis.The control model of vehicle platoon was established by using adaptive fuzzy control algorithm.The weight coefficients were decided through the gear status information of the following vehicle.They were used to adjust the input scale of fuzzy controller in order to improve the adaptability of control algorithm.Through co-simulation of TruckSim and Matlab,three trucks platoon was simulated in the case of vehicle-vehicle communication environment using the test data from real vehicle as the simulation conditions of the leader truck.The simulation results show that the travel space error between two vehicles can be controlled within 5percent of driving distance in unit time.The control model has certain control accuracy.
引文
[1]中华人民共和国国家统计局.2014年国民经济和社会发展统计公报[EB/OL].(2015-02-26)[2015-09-27].http:∥www.stats.gov.cn/tjsj/zxfb/201502/t20150226_685799.html.
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[11]高振海,吴涛,尤洋.基于粒子群算法的汽车自适应巡航控制器设计[J].农业机械学报,2013,44(12):11-16.GAO Zhen-hai,WU Tao,YOU Yang.Design of vehicle adaptive cruise controller based on PSO algorithm[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(12):11-16.
[12]岳伟,郭戈.自主车队的非线性建模与控制[J].控制与决策,2009,24(7):996-1000.YUE Wei,GUO Ge.Nonlinear modelling and control of autonomous platoon[J].Control and Decision,2009,24(7):996-1000.
[13]任殿波,张策,张继业.考虑前后信息的车辆跟随自适应控制[J].哈尔滨工业大学学报.2011,43(6):76-80.REN Dian-bo,ZHANG Ce,ZHANG Ji-ye.Vehicle following adaptive control using front and back information[J].Journal of Harbin Institute of Technology,2011,43(6):76-80.
[2]中华人民共和国交通运输部.2014年交通运输行业发展统计公报[EB/OL].(2015-07-23)[2015-09-27].http:∥www.mot.gov.cn/zhuzhan/jiaotonggaikuang/201507/t20150723_1853384.html.
[3]NIEUWENHUIJZE M R I,KEULEN T V,NCS,et al.Cooperative driving with a heavy-duty truck in mixed traffic:experimental results[J].Transactions on Intelligent Transportation Systems,2012,13(3):1026-1032.
[4]TSUGAWA S,KATO S,AOKI K.An automated truck platoon for energy saving[C]∥Intelligent Robots and Systems.San Francisco,USA:[s.n.],2011:4109-411.
[5]FRANKE U,BTTIGER F,et al.Truck platooning in mixed traffic[C]∥Proc.of the Intelligent Vehicle Symposium.Detroit,USA:[s.n.],1995:1-6.
[6]GEHRIG S K,STEIN F J.Collision avoidance for vehicle-following systems[J].Intelligent Transportation Systems,2007.5(4):112-120.
[7]GEHRING O,FRITZ H.Practical results of a longitudinal control concept for truck platooning with vehicle to vehicle communication[C]∥Intelligent Transportation System.Boston,USA:[s.n.],1997:117-122.
[8]VINEL A,LIN L,LYAMIN N.Vehicle-to-vehicle communication in c-acc/platooning scenarios[J].Communications Magazine,2015,53(8):192-197.
[9]TSUGAWA S,KATO S.Energy ITS:another application of vehicular communications[J].Communications Magazine,2010,48(11)120-126.
[10]马育林,吴青,张蕊,等.模拟自治车队行驶过程变工况速度跟踪控制[J].机械工程学报,2011,47(7):140-147.MA Yu-lin,WU Qing,ZHANG Rui,et al.Speed tracking control for a simulated intelligent vehicle platoon under variable road conditions[J].Journal of Mechanical Engineering,2011,47(7):140-147.
[11]高振海,吴涛,尤洋.基于粒子群算法的汽车自适应巡航控制器设计[J].农业机械学报,2013,44(12):11-16.GAO Zhen-hai,WU Tao,YOU Yang.Design of vehicle adaptive cruise controller based on PSO algorithm[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(12):11-16.
[12]岳伟,郭戈.自主车队的非线性建模与控制[J].控制与决策,2009,24(7):996-1000.YUE Wei,GUO Ge.Nonlinear modelling and control of autonomous platoon[J].Control and Decision,2009,24(7):996-1000.
[13]任殿波,张策,张继业.考虑前后信息的车辆跟随自适应控制[J].哈尔滨工业大学学报.2011,43(6):76-80.REN Dian-bo,ZHANG Ce,ZHANG Ji-ye.Vehicle following adaptive control using front and back information[J].Journal of Harbin Institute of Technology,2011,43(6):76-80.