-
摘要: 考虑自主车辆队列的节能安全问题,本文提出一种车辆队列协同控制方法,该方法可保证车队低能耗安全行驶.首先,充分考虑道路坡度以及车队异质性建立车队非线性模型,利用基于油耗模型的优化指标构建车队速度优化问题,提出一种滚动时域动态规划算法(Receding horizon dynamic programming,RHDP),获得车队的参考速度.然后,基于非线性车辆模型,运用反步法设计车辆跟踪控制器,并进行车队队列稳定性分析.这种协同控制方法的有效性已通过数值仿真和智能交通实验平台的验证.Abstract: This paper considers the problem of fuel-efficient and safe of autonomous platoons. A cooperative control is presented, which can guarantee safety driving of a platoon with the lowest fuel consumption. First, we develop a nonlinear platoon vehicle dynamic model considering road topography and platoon heterogeneity. The optimization problem is formulated by using the optimization index, which is a function of fuel consumption. A receding horizon dynamic programming (RHDP) methodology is proposed to obtain the reference velocity. Then, based on the nonlinear vehicle model and exploiting backstepping methodology, the tracking controller is designed, and further the string stability of the platoon is analyzed. The effectiveness of the presented cooperative method is demonstrated by both numerical simulation and experiments with laboratory-scale Arduino cars.1) 本文责任编委 吕宜生
-
表 1 油耗对比
Table 1 Comparison on fuel consumed
第$i$辆车, 基于速度 基于速度 车重 规划的油耗(mL) 设定的油耗[9] (mL) 0, 20 t 476.7 625.4 1, 20 t 302.3 384.1 2, 35 t 396.2 488.5 3, 40 t 427.7 523.4 4, 40 t 427.6 523.3 总油耗 2 030.5 2 544.7 -
[1] Alam A. Fuel-Efficient Heavy-Duty Vehicle Platooning [Ph. D. dissertation], KTH Royal Institute of Technology, 2014. [2] European Commission. EU Transport in Figures-Statistical Pocketbook. Luxembourg: European Commission, 2014. http://www.chinautc.com/templates/H_guojidongtai/content.aspx?nodeid=3998&page=ContentPage&contentid=77934 [3] Shladover S E. PATH at 20-history and major milestones. In: Proceedings of the 2006 IEEE Intelligent Transportation Systems Conference. Toronto, Canada: IEEE, 2006. 1-22-1-29 https://www.researchgate.net/publication/3428064_PATH_at_20-History_and_Major_Milestones [4] Hellström E, Åslund J, Nielsen L. Design of an efficient algorithm for fuel-optimal look-ahead control. Control Engineering Practice, 2010, 18(11): 1318-1327 doi: 10.1016/j.conengprac.2009.12.008 [5] Bonnet C, Fritz H. Fuel consumption reduction in a platoon: experimental results with two electronically coupled trucks at close spacing. In: Proceedings of the Future Transportation Technology Conference & Exposition. Costa Mesa, USA, 2000. [6] Al Alam A, Gattami A, Johansson K H. An experimental study on the fuel reduction potential of heavy duty vehicle platooning. In: Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems. Funchal: IEEE, 2010. 306-311 https://www.researchgate.net/publication/224190659_An_experimental_study_on_the_fuel_reduction_potential_of_heavy_duty_vehicle_platooning [7] Shladover S E. Longitudinal control of automotive vehicles in close-formation platoons. Journal of Dynamic Systems, Measurement, and Control, 1991, 113(2): 231-241 doi: 10.1115/1.2896370 [8] Dolk V S, Ploeg J, Heemels W P M H. Event-triggered control for string-stable vehicle platooning. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(12): 3486-3500 doi: 10.1109/TITS.2017.2738446 [9] Stankovic S S, Stanojevic M J, Siljak D D. Decentralized overlapping control of a platoon of vehicles. IEEE Transactions on Control Systems Technology, 2000, 8(5): 816-832 doi: 10.1109/87.865854 [10] Guo G, Yue W. Autonomous platoon control allowing range-limited sensors. IEEE Transactions on Vehicular Technology, 2012, 61(7): 2901-2912 doi: 10.1109/TVT.2012.2203362 [11] Yue W, Wang L Y, Guo G. Event-triggered platoon control of vehicles with time-varying delay and probabilistic faults. Mechanical Systems and Signal Processing, 2017, 87: 96-117 doi: 10.1016/j.ymssp.2016.09.042 [12] Wang Q, Guo G, Cai B B. Distributed receding horizon control for fuel-efficient and safe vehicle platooning. Science China Technological Sciences, 2016, 59(12): 1953-1962 doi: 10.1007/s11431-016-0856-8 [13] Wang C, Nijmeijer H. String stable heterogeneous vehicle platoon using cooperative adaptive cruise control. In: Proceedings of the 18th International Conference on Intelligent Transportation Systems. Las Palmas, Spain: IEEE, 2015. 1977-1982 https://www.researchgate.net/publication/308819306_String_Stable_Heterogeneous_Vehicle_Platoon_Using_Cooperative_Adaptive_Cruise_Control [14] Zheng Y, Li S E, Wang J Q, Cao D P, Li K Q. Stability and scalability of homogeneous vehicular platoon: study on the influence of information flow topologies. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(1): 14-26 doi: 10.1109/TITS.2015.2402153 [15] Guo X G, Wang J L, Liao F, Teo R S H. Distributed adaptive integrated-sliding-mode controller synthesis for string stability of vehicle platoons. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(9): 2419-2429 doi: 10.1109/TITS.2016.2519941 [16] Harfouch Y A, Yuan S, Baldi S. An adaptive switched control approach to heterogeneous platooning with inter-vehicle communication losses. IEEE Transactions on Control of Network Systems, 2017, DOI: 10.1109/TCNS.2017.2718359 [17] 田涛涛, 侯忠生, 刘世达, 邓志东.基于无模型自适应控制的无人驾驶汽车横向控制方法.自动化学报, 2017, 43(11): 1931-1940 http://www.aas.net.cn/CN/abstract/abstract19168.shtmlTian Tao-Tao, Hou Zhong-Sheng, Liu Shi-Da, Deng Zhi-Dong. Model-free adaptive control based lateral control of self-driving car. Acta Automatica Sinica, 2017, 43(11): 1931-1940 http://www.aas.net.cn/CN/abstract/abstract19168.shtml [18] 孙景亮, 刘春生.基于自适应动态规划的导弹制导律研究综述.自动化学报, 2017, 43(7): 1101-1113 http://www.aas.net.cn/CN/abstract/abstract19086.shtmlSun Jing-Liang, Liu Chun-Sheng. An overview on the adaptive dynamic programming based missile guidance law. Acta Automatica Sinica, 2017, 43(7): 1101-1113 http://www.aas.net.cn/CN/abstract/abstract19086.shtml [19] Schwarzkopf A B, Leipnik R B. Control of highway vehicles for minimum fuel consumption over varying terrain. Transportation Research, 1977, 11(4): 279-286 doi: 10.1016/0041-1647(77)90093-4 [20] Hooker J N. Optimal driving for single-vehicle fuel economy. Transportation Research, Part A: General, 1988, 22(3): 183-201 doi: 10.1016/0191-2607(88)90036-2 [21] Hellström E, Åslund J, Nielsen L. Design of a well-behaved algorithm for on-board look-ahead control. IFAC Proceedings of Volumes, 2008, 41(2): 3350-3355 doi: 10.3182/20080706-5-KR-1001.00569 [22] Van Mierlo J, Maggetto G, Van de Burgwal E, Gense R. Driving style and traffic measures-influence on vehicle emissions and fuel consumption. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2004, 218(1): 43-50 doi: 10.1243/095440704322829155 [23] Taniguchi M. Eco-driving and fuel economy of passenger cars. In: Proceedings of the Annual Meeting of IEE Japan. IEE, 2008. S215-S218 [24] Kamal M A S, Mukai M, Murata J, Kawabe T. Ecological driver assistance system using model-based anticipation of vehicle-road-traffic information. IET Intelligent Transport Systems, 2010, 4(4): 244-251 doi: 10.1049/iet-its.2009.0127 [25] 丁进良, 杨翠娥, 陈立鹏, 柴天佑.基于参考点预测的动态多目标优化算法.自动化学报, 2017, 43(2): 313-320 http://www.aas.net.cn/CN/abstract/abstract19009.shtmlDing Jin-Liang, Yang Cui-E, Chen Li-Peng, Chai Tian-You. Dynamic multi-objective optimization algorithm based on reference point prediction. Acta Automatica Sinica, 2017, 43(2): 313-320 http://www.aas.net.cn/CN/abstract/abstract19009.shtml [26] Kamal M A S, Mukai M, Murata J, Kawabe T. Ecological vehicle control on roads with up-down slopes. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(3): 783-794 doi: 10.1109/TITS.2011.2112648 [27] Kamal A S, Mukai M, Murata J, Kawabe T. Model predictive control of vehicles on urban roads for improved fuel economy. IEEE Transactions on Control Systems Technology, 2013, 21(3): 831-841 doi: 10.1109/TCST.2012.2198478 [28] Zhang B, Gao Z Y, Guo G. Fuel optimal vehicle control via traffic light prediction. In: Proceedings of the 36th Chinese Control Conference. Dalian, China: IEEE, 2017. 10004-10009 http://cpfd.cnki.com.cn/Article/CPFDTOTAL-KZLL201707007015.htm [29] Goeke D, Schneider M. Routing a mixed fleet of electric and conventional vehicles. European Journal of Operational Research, 2015, 245(1): 81-99 doi: 10.1016/j.ejor.2015.01.049