考虑参数摄动的智能汽车动态侧向避障鲁棒控制策略
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云南省科技计划基础研究资助项目(202101AT070108)。


Robust control strategy for dynamic lateral obstacle avoidance of intelligent vehicle considering parameter perturbation
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    摘要:

    汽车加速度和速度因交通环境障碍物实时动态变化,智能汽车避障实时参考轨迹不光滑变化;参数摄动,车速实时变化和采集信号干扰,将造成智能汽车动态侧向避障精准控制困难。为此,提出考虑参数摄动的智能汽车动态侧向避障鲁棒控制策略。该控制策略分为动态轨迹规划层和动态轨迹跟踪层;动态轨迹规划层依据障碍物汽车加速度和速度动态变化,采用基于避障极限位置的动态轨迹规划算法,以规划能够保证智能汽车侧向安全避障的实时参考轨迹;动态轨迹跟踪层设计了考虑了质量、转动惯量和前后侧偏刚度参数摄动的鲁棒控制器,以实现实时动态参考轨迹精准跟踪。最后,利用Matlab/Simulink和Trucksim软件联合仿真,进行所提控制策略仿真验证。仿真结果表明:动态轨迹规划层能够依据障碍物汽车加速度和速度实时变化,实时规划了安全侧向避障动态参考轨迹;轨迹跟踪层克服了质量、转动惯量、前后侧偏刚度参数摄动,以及实时参考轨迹不光滑动态变化,平滑良好地跟踪了侧向避障实时参考轨迹。因此,所提控制策略实现了智能汽车安全动态侧向避障,同时确保了避障过程汽车横摆稳定性。

    Abstract:

    The dynamic change of velocity and acceleration of obstacle vehicle under the actual dynamic traffic environmental can cause the unsmooth change of the real-time reference trajectory of lateral obstacle for intelligent vehicle. To overcome the poor control effect of the controller caused by the unsmooth trajectory, parameter perturbation and signal disturb, the robust control strategy for dynamic lateral obstacle avoidance of intelligent vehicles considering parameter perturbation was presented. The strategy includes dynamic trajectory planning and dynamic trajectory tracking. In the dynamic trajectory planning, according to dynamic change of acceleration and velocity of obstacle vehicle, the dynamic trajectory planning algorithm based on obstacle avoidance limit position was proposed to plan real-time reference trajectory which can ensure lateral safety of obstacle avoidance for intelligent vehicles. In the dynamic trajectory tracking, with consideration of the perturbation of mass, moment of inertia and front and rear lateral stiffness parameters, a robust controller considering parameter perturbation was designed to accurately track real-time reference trajectory of lateral obstacle avoidance. Finally, the proposed dynamic lateral obstacle avoidance control strategy was validated by combining Matlab/Simulink with Trucksim. The simulation results indicate that according to the real-time change of acceleration and speed of obstacle vehicle, the real-time safety reference trajectory of lateral obstacle avoidance can be achieved in the dynamic trajectory planning. The real-time reference trajectory of lateral obstacle avoidance can be smoothly,stably and well tracked in the dynamic trajectory tracking. Therefore, the proposed control strategy realizes the dynamic lateral obstacle avoidance of intelligent vehicles while ensuring the vehicle yaw stability during the whole process of obstacle avoidance.

    参考文献
    [1] Wu J, Wang X Y, Li L, et al. Hierarchical control strategy with battery aging consideration for hybrid electric vehicle regenerative braking control. Energy, 2018, 145:301-312.
    [2] World Health Organization. Top 10 causes of death worldwide[EB/OL].(2015)[2021-05-21]. Available from:http://www.who.int/mediacentre/factsheets/fs310/en/.
    [3] He X, Yulong L, Lv C, et al. Emergency steering control of autonomous vehicle for collision avoidance and stabilisation[J]. Vehicle System Dynamics, 2018, 57(8):1163-1187.
    [4] Bevly D, Cao X L, Gordon M, et al. Lane change and merge maneuvers for connected and automated vehicles:a survey. IEEE Transactions on Intelligent Vehicles, 2016, 1(1):105-120.
    [5] He X K, Liu Y L, Lv C, et al. Emergency steering control of autonomous vehicle for collision avoidance and stabilisation. Vehicle System Dynamics, 2019, 57(8):1163-1187.
    [6] Gao Y Q, Lin T, Borrelli F, et al. Predictive control of autonomous ground vehicles with obstacle avoidance on slippery roads//Proceedings of ASME 2010 Dynamic Systems and Control Conference, September 12-15, 2010. Cambridge, Massachusetts, USA:IEEE, 2011:265-272.
    [7] Shim T, Adireddy G, Yuan H L. Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control. Proceedings of the Institution of Mechanical Engineers, Part D:Journal of Automobile Engineering, 2012, 226(6):767-778.
    [8] Shah J, Best M, Benmimoun A, et al. Autonomous rear-end collision avoidance using an electric power steering system. Proceedings of the Institution of Mechanical Engineers, Part D:Journal of Automobile Engineering, 2015, 229(12):1638-1655.
    [9] Cui Q J, Ding R J, Wu X J, et al. A new strategy for rear-end collision avoidance via autonomous steering and differential braking in highway driving. Vehicle System Dynamics, 2020, 58(6):955-986.
    [10] Erlien S M, Fujita S, Gerdes J C. Shared steering control using safe envelopes for obstacle avoidance and vehicle stability. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(2):441-451.
    [11] Ji J, Khajepour A, Melek W W, et al. Path planning and tracking for vehicle collision avoidance based on model predictive control with multiconstraints. IEEE Transactions on Vehicular Technology, 2017, 66(2):952-964.
    [12] Anderson S J, Peters S C, Pilutti T E, et al. An optimal-control-based framework for trajectory planning, threat assessment, and semi-autonomous control of passenger vehicles in hazard avoidance scenarios. International Journal of Vehicle Autonomous Systems, 2010, 8(2/3/4):190.
    [13] Gao Y Y, Gordon T, Lidberg M. Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm. Vehicle System Dynamics, 2019, 57(8):1224-1240.
    [14] 任玥, 郑玲, 张巍, 等. 基于模型预测控制的智能车辆主动避撞控制研究. 汽车工程, 2019, 41(4):404-410.Ren Y, Zheng L, Zhang W, et al. A study on active collision avoidance control of autonomous vehicles based on model predictive control. Automotive Engineering, 2019, 41(4):404-410.(in Chinese)
    [15] 王其东, 李印祥, 陈无畏, 等. 基于制动转向协同控制的智能车紧急避障研究. 汽车工程, 2019, 41(4):395-403, 425.Wang Q D, Li Y X, Chen W W, et al. A research on emergency obstacle avoidance of intelligent vehicle based on braking and steering coordinated control. Automotive Engineering, 2019, 41(4):395-403, 425.(in Chinese)
    [16] 廉宇峰. 电动汽车主动避撞系统状态估计与控制策略研究. 长春:吉林大学, 2015. Lian Y F. On the state estimation and control strategy of collision avoidance system for electric vehicle. Changchun:Jilin University, 2015. (in Chinese)
    [17] Hajiloo R, Abroshan M, Khajepour A, et al. Integrated steering and differential braking for emergency collision avoidance in autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(5):3167-3178.
    [18] Yang D, Zheng S Y, Wen C, et al. A dynamic lane-changing trajectory planning model for automated vehicles. Transportation Research Part C:Emerging Technologies, 2018, 95:2渲??渲朴椷渮攼敢牲椾湛朱??㈠ぇ?は??㈠え?㈠???????????椠湋??栮椠湒敯獢敵?t gain-scheduling automatic steering control of unmanned ground vehicles under velocity-varying motion. Vehicle System Dynamics, 2019, 57(4):595-616.
    [20] Sharp R, Valtetsiotis. Optimal preview car steering control. Vehicle System Dynamics, 2001, 35:101-117.
    [21] Hu C, Jing H, Wang R R, et al. Robust H output-feedback control for path following of autonomous ground vehicles. Mechanical Systems and Signal Processing, 2016, 70/71:414-427.
    [22] 聂枝根, 王万琼, 王超, 等. 中高速重型半挂车适时模式切换的集成控制策略. 交通运输工程学报, 2017, 17(6):135-149.Nie Z G, Wang W Q, Wang C, et al. Integrated control strategy of articulated heavy vehicle based on timely mode switching under medium/high speed conditions. Journal of Traffic and Transportation Engineering, 2017, 17(6):135-149.(in Chinese)
    [23] Jula H, Kosmatopoulos E B, Ioannou P A. Collision avoidance analysis for lane changing and merging. IEEE Transactions on Vehicular Technology, 2000, 49(6):2295-2308.
    [24] Kanaris A, Kosmatopoulos E B, Loannou P A. Strategies and spacing requirements for lane changing and merging in automated highway systems. IEEE Transactions on Vehicular Technology, 2001, 50(6):1568-1581.
    [25] Tamaddoni S H, Taheri S, Ahmadian M. Optimal preview game theory approach to vehicle stability controller design. Vehicle System Dynamics, 2011, 49(12):1967-1979.
    [26] Gu D W, Petkov P H, Konstantinov M M. Robust control design with Matlab. London:Springer, 2005.
    [27] Lian Y F, Wang X Y, Tian Y T, et al. Lateral collision avoidance robust control of electric vehicles combining a lane-changing model based on vehicle edge turning trajectory and a vehicle semi-uncertainty dynamic model. International Journal of Automotive Technology, 2018, 19(2):331-343.
    [28] 聂枝根, 王万琼, 赵伟强, 等. 基于轨迹预瞄的智能汽车变道动态轨迹规划与跟踪控制. 交通运输工程学报, 2020, 20(2):147-160.Nie Z G, Wang W Q, Zhao W Q, et al. Dynamic trajectory planning and tracking control for lane change of intelligent vehicle based on trajectory preview. Journal of Traffic and Transportatio???????????????????????????????????????????????
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聂枝根,沈澳,王万琼,王超.考虑参数摄动的智能汽车动态侧向避障鲁棒控制策略[J].重庆大学学报,2023,46(3):103-117.

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  • 收稿日期:2021-07-07
  • 在线发布日期: 2023-03-28
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