基于DQP-LMPC的智能车超车换道动态路径规划

doi:10.3901/JME.2024.10.171

摘要/Abstract

摘要： 为实现智能汽车安全舒适且高效的超车换道路径，针对双向双车道，提出一种基于双五次多项式和线性时变模型预测控制(Double quintic polynomial-linear time-varying model predictive control, DQP-LMPC) 结合的超车换道动态路径规划模型。首先，基于五次多项式进行初次规划并进行改进研究，考虑对向车道来车，建立双五次多项式进行超车换道路径规划；其次，基于车网联的条件下，获取本车道前车和对向车道前车的位置和速度等信息，分析计算换道决策安全区间，保证整个超车换道过程的安全性；最后，基于二自由度车辆模型建立线性时变模型预测控制器对模型进行路径跟踪控制。仿真结果表明，在前方静止障碍物及无对向来车、前方动态障碍物及无对向来车和前方动态障碍物及有对向车道来车三个工况下，使用横向加速度、横摆角速度、侧倾角加速度以及横向纵向间距等为指标进行评价，最终得到的规划算法可以成功地规划出安全高效及舒适的超车换道路径，表明创建的模型具有一定的应用价值。

关键词: 智能驾驶, 路径规划, 动态规划, 超车换道, 双五次多项式

Abstract: In order to realize a safe, comfortable and efficient overtaking lane changing path for intelligent vehicles, a dynamic path planning model for overtaking lane changing is proposed based on the combination of double quintic polynomial and linear time-varying model predictive control for two-way dual lanes. First of all, based on the quintic polynomial for the initial planning and improvement research, considering the coming traffic lane, the establishment of double quintic polynomial for overtaking lane change path planning; Secondly, based on the condition of vehicle network connection, the position and speed information of the vehicle in front of the lane and the vehicle in front of the opposite lane are obtained, and the safety interval of lane changing decision is analyzed and calculated to ensure the safety of the whole process of overtaking and lane changing. Finally, based on the two-degree-of-freedom vehicle model, a linear time-varying model prediction controller is established to control the path tracking of the model. The simulation results show that, under the three working conditions of stationary obstacle in front and non-opposing vehicle, dynamic obstacle in front, non-opposing vehicle and dynamic obstacle in front and incoming vehicle in opposite lane, lateral acceleration, yaw velocity, side angle acceleration and transverse and longitudinal spacing are used as indicators for evaluation. The final planning algorithm can successfully plan the safe, efficient and comfortable path of overtaking and lane changing, which indicates that the model has certain application value.

Key words: intelligent driving, path planning, dynamic programming, passing lane change, double quintic polynomial

中图分类号:

U461

胡林, 杨冬兆, 张新, 章杰, 廖家才. 基于DQP-LMPC的智能车超车换道动态路径规划[J]. 机械工程学报, 2024, 60(10): 171-181.

HU Lin, YANG Dongzhao, ZHANG Xin, ZHANG Jie, LIAO Jiacai. Dynamic Path Planning of Intelligent Vehicle Overtaking Lane Change Based on DQP-LMPC[J]. Journal of Mechanical Engineering, 2024, 60(10): 171-181.

参考文献

[1] 胡林，钟远兴，黄晶，等. 考虑信号交叉口延时的最优车辆路径规划算法[J]. 汽车工程，2018，40(10):1223-1229，1253. HU Lin，ZHONG Yuanxing，HUANG Jing，et al. Optimal path programming algorithm with consideration of signalized intersection delay[J]. Automotive Engineering，2018，40(10):1223-1229，1253.
[2] HU Lin，ZHONG Yuanxing，HAO Wei，et al. Optimal route algorithm considering traffic light and energy consumption[J]. IEEE Access，2018，6:59695-59704.
[3] HUANG Guanhao，MA Qinglu. Research on path planning algorithm of autonomous vehicles based on improved RRT algorithm[J]. International Journal of Intelligent Transportation Systems Research，2022，20(1):170-180.
[4] 张家旭，王晨，赵健. 基于改进人工势场法的汽车弯道超车路径规划与跟踪控制[J]. 汽车工程，2021，43(4):546-552. ZHANG Jiaxu，WANG Chen，ZHAO Jian. Path planning and tracking control for vehicle overtaking on curve based on modified artificial potential field method[J]. Automotive Engineering，2021，43(4):546-552.
[5] WU Ping，GAO Feng，LI Keqiang. Humanlike decision and motion planning for expressway lane changing based on artificial potential field[J]. IEEE Access，2022，10:4359-4373.
[6] CHEN Yimin，LU Chao，CHU Wenbo. A cooperative driving strategy based on velocity prediction for connected vehicles with robust path-following control[J]. IEEE Internet of Things Journal，2020，7(5):3822-3832.
[7] 熊明强，谯杰，夏芹. 基于改进LSTM-NN的安全性自动驾驶换道轨迹规划模型[J]. 汽车工程学报，2021，11(6):419-426. XIONG Mingqiang，QIAO Jie，XIA Qin. A lane-changing trajectory planning model for automated vehicles based on improved safety-sensitive LSTM-NN[J]. Chinese Journal of Automotive Engineering，2021，11(6):419-426.
[8] YANG Da，ZHENG Shiyu，WEN Cheng，et al. A dynamic lane-changing trajectory planning model for automated vehicles[J]. Transportation Research，2018，95:228-247.
[9] 刘志强，王一凡，吴雪刚，等. 基于线性路径跟踪控制的换道避撞控制策略研究[J]. 中国公路学报，2019，32(6):86-95. LIU Zhiqiang，WANG Yifan，WU Xuegang，et al. Collision a voidance by lane changing based on linear path-following control[J]. China Journal of Highway and Transport，2019，32(6):86-95.
[10] 杨威，郑玲，李以农. 基于高斯混合模型的个性化自动驾驶决策控制研究[J]. 机械工程学报，2022，58(16):280-289. YANG Wei，ZHENG Ling，LI Yinong. Personalized automated driving decision based on the gaussian mixture model[J]. Journal of Mechanical Engineering，2022，58(16):280-289.
[11] PAE D，KIM G，KANG T，et al. Path planning based on obstacle-dependent gaussian model predictive control for autonomous driving[J]. Applied Sciences，2021，11(8):3703.
[12] 贾寒冰，刘鹏，张雷，等. 基于规则与机器学习融合的换道决策建模方法研究[J]. 机械工程学报，2022，58(4):212-221. JIA Hanbing，LIU Peng，ZHANG Lei，et al. Lane-changing decision model development by combining rules abstract and machine learning technique[J]. Journal of Mechanical Engineering，2022，58(4):212-221.
[13] WANG W，QIE T，YANG C，et al. An intelligent lane-changing behavior prediction and decision-making strategy for an autonomous vehicle[J]. IEEE Transactions on Industrial Electronics，2022，69(3):2927-2937.
[14] YAO Jun，CHEN Guoying，GAO Zhenhai. Target vehicle selection algorithm for adaptive cruise control based on lane-changing intention of preceding vehicle[J]. Chinese Journal of Mechanical Engineering，2021，34(5):406-423.
[15] LÜ Xiaoxing，LI Weihua，WANG Jianfeng. Safety-field-based path planning algorithm of lane changing for autonomous vehicles[J]. International Journal of Control，Automation and Systems，2022，20(2):564-576.
[16] 郭应时，苏彦奇，付锐，等. 换道操作对智能车辆乘客舒适性的影响研究[J]. 中国公路学报，2022，35(5):221-230. GUO Yingshi，SU Yanqi，FU Rui，et al. Influence of lane-changing maneuvers on passenger comfort of intelligent vehicles[J]. China Journal of Highway and Transport，2022，35(5):221-230.
[17] ZHANG Bo，ZHANG Jianwei，LIU Yang，et al. Planning flexible and smooth paths for lane-changing manoeuvres of autonomous vehicles[J]. IET Intelligent Transport Systems，2021，15(2):200-212.
[18] LIANG Yixiao，LI Yinong，KHAJEPOUR A，et al. A novel combined decision and control scheme for autonomous vehicle in structured road based on adaptive model predictive control[J]. IEEE Transactions on Intelligent Transportation Systems，2022，23(9):16083-16097.
[19] DIXIT S，MONTANARO U，DIANATI M，et al. Trajectory planning for autonomous high-speed overtaking in structured environments using robust MPC[J]. IEEE Transactions on Intelligent Transportation Systems，2020，21(6):2310-2323.
[20] 王慧然，王其东，陈无畏，等. 基于车辆行驶安全边界的换道控制[J]. 机械工程学报，2020，56(18):143-153. WANG Huiran，WANG Qidong，CHEN Wuwei，et al. Lane change control based on vehicle driving safe boundary[J]. Journal of Mechanical Engineering，2020，56(18):143-153.
[21] 王莹，卫翀，马路. 基于二次规划的智能车辆动态换道轨迹规划研究[J]. 中国公路学报，2021，34(7):79-94. WANG Ying，WEI Chong，MA Lu，et al. Dynamic lane-changing trajectory planning model for intelligent vehicle based on quadratic programming[J]. China Journal of Highway and Transport，2021，34(7):79-94.
[22] 阳鑫，唐小林，杨凯，等. 极限工况下无人驾驶车辆运动规划策略研究[J]. 机械工程学报，2022，58(22):349-359. YANG Xin，TANG Xiaolin，YANG Kai，et al. Research on the motion planning strategy for autonomous vehicles in extreme conditions[J]. Journal of Mechanical Engineering，2022，58(22):349-359.
[23] 吴西涛，魏超，翟建坤，等. 考虑横摆稳定性的无人车轨迹跟踪控制优化研究[J]. 机械工程学报，2022，58(6):130-142. WU Xitao，WEI Chao，ZHAI Jiankun，et al. Study on the optimization of autonomous vehicle on path-following considering yaw stability[J]. Journal of Mechanical Engineering，2022，58(6):130-142.
[24] FAN J Y，LIANG J，TULA A K. A lane changing time point and path tracking framework for autonomous ground vehicle[J]. IET Intelligent Transport Systems，2022，16(7):860-874.
[25] 黄晶，蓟仲勋，彭晓燕，等. 考虑驾驶人风格的换道轨迹规划与控制[J]. 中国公路学报，2019，32(6):226-239，247. HUANG Jing，JI Zhongxun，PENG Xiaoyan，et al. Driving style adaptive lane-changing trajectory planning and control[J]. China Journal of Highway and Transport，2019，32(6):226-239，247.
[26] HUANG Jing，CHEN Yimin，PENG Xiaoyan，et al. Study on the driving style adaptive vehicle longitudinal control strategy[J]. IEEE/CAA Journal of Automatica Sinica，2020，7(4):1107-1115.
[27] WU Jiabin，CHEN Xiaohua，BIE Yiming，et al. A co-evolutionary lane-changing trajectory planning method for automated vehicles based on the instantaneous risk identification[J]. Accident Analysis and Prevention，2023，180:106907.
[28] ZHENG Ling，ZENG Pengyun，YANG Wei，et al. Bézier curve-based trajectory planning for autonomous vehicles with collision avoidance[J]. IET Intelligent Transport Systems，2020，14(13):1882-1891.
[29] LI Hongluo，LUO Yutao，WU Jie. Collision-free path planning for intelligent vehicles based on bezier curve[J]. IEEE Access，2019，7:123334-123340.
[30] CHEN Long，QIN Dongfang，XU Xing，et al. A path and velocity planning method for lane changing collision avoidance of intelligent vehicle based on cubic 3-D Bezier curve[J]. Advances in Engineering Software，2019，132:65-73.
[31] 牛国臣，李文帅，魏洪旭. 基于双五次多项式的智能汽车换道轨迹规划[J]. 汽车工程，2021，43(7):978-986，1004. NIU Guochen，LI Wenshuai，WEI Hongxu. Intelligent vehicle lane changing trajectory planning based on double quintic polynomials[J]. Automotive Engineering，2021，43(7):978-986，1004.
[32] DING Yang，ZHUANG Weihao，WANG Liangmo，et al. Safe and optimal lane-change path planning for automated driving[J]. Journal of Automobile Engineering，2021，235(4):1070-1083.
[33] 胡林，周登辉，黄晶，等. 考虑信号灯和能耗的电动车最优路径规划[J]. 汽车工程，2021，43(5):641-649，666. HU Lin，ZHOU Denghui，HUANG Jing，et al. Optimal path planning for electric vehicle with consideration of traffic light and energy consumption[J]. Automotive Engineering，2021，43(5):641-649，666.
[34] 龚建伟，姜岩，徐威. 无人驾驶车辆模型预测控制[M]. 2版. 北京:北京理工大学出版社，2020. GONG Jianwei，JIANG Yan，XU Wei. Autonomous vehicle model predictive control[M]. 2nd ed. Beijing:Beijing Institute of Technology Press，2020.
[35] DENG Chengzhi，QIAN Yubin，DONG Honglei，et al. Lane change trajectory planning based on quadratic programming in rainy weather[J]. World Electric Vehicle Journal，2023，14(9):252.