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汽车安全与节能学报

汽车安全与节能学报 ›› 2023, Vol. 14 ›› Issue (3): 319-328.DOI: 10.3969/j.issn.1674-8484.2023.03.007

• 智能驾驶与智慧交通 • 上一篇    下一篇

面向非结构化道路场景的车辆全局速度规划

李涵1(), 余贵珍1, 周彬1,*(), 张煜笛2, 张叶婧3, 欧阳东哲4, 田江涛4   

  1. 1.北京航空航天大学 交通科学与工程学院, 特种车辆无人运输技术工业和信息化部重点实验室，北京 100083，中国
    2.公安部道路交通安全研究中心, 北京 100062，中国
    3.中国联合网络通信有限公司研究院，北京 100062，中国
    4.国能北电胜利能源有限公司, 锡林浩特 026000，中国
  • 收稿日期:2023-01-19 修回日期:2023-03-28 出版日期:2023-06-30 发布日期:2023-07-11
  • 通讯作者: *周彬 (1987—)，男(汉)，山东，讲师。E-mail：binzhou@buaa.edu.cn。
  • 作者简介:李涵 (1996—)，男(汉)，河南，博士研究生。E-mail：leehan@buaa.edu.cn。
  • 基金资助:
    国家重点研发计划(2020YFB1600302)

Vehicle global speed planning for unstructured roads scenario

LI Han1(), YU Guizhen1, ZHOU Bin1,*(), ZHANG Yudi2, OUYANG Dongzhe3, TIAN Jiangtao4   

  1. 1. School of Traffic Science and Engineering, Beihang University, Beijing 100083, China
    2. Research Institute for Road safety of the Ministry of public security, Beijing 100062, China
    3. Research Institute of China United Network Communications Co., Ltd, Beijing 100062, China
    4. Guoneng Nortel Shengli Energy Co., Ltd, Xilin Gol 026000, China
  • Received:2023-01-19 Revised:2023-03-28 Online:2023-06-30 Published:2023-07-11

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摘要：

为实现智能网联车辆在复杂非结构化道路场景下行驶速度规划，该文提出了一种基于分段匀加速模型的车辆全局速度规划方法。以驾驶安全平稳性为原则分析车辆动力学特性，计算侧翻与侧滑临界车速作为非结构道路上各路径点的极限行驶速度；设计分段匀加速模型建立全局速度规划问题，构建考虑效率、平稳性及能耗的综合损失函数，考虑非结构化道路的坡度曲率连续变化，设计车辆速度、加速度及加加速度变量边界来约束决策变量；结合重型电动车辆制动能量回收功能，针对性提出非结构化道路场景下电动车辆速度规划模型，并通过仿真对方法进行验证。结果表明：主车的加速度范围稳定在-1.0~1.0 m/s2，加加速度范围稳定在-0.5~0.8 m/s3；相比于基于动态规划的速度规划，所提出的速度规划算法保证车辆行驶平稳性的同时，减少了车辆控制输入, 0.8 s的计算时间可满足无人驾驶车载设备实时计算需求；将提出的算法应用于无人矿卡实车，车辆行驶平稳，最大加加速度不超过0.45 m/s3。

关键词: 非结构化道路, 速度规划, 无人驾驶, 运动规划

Abstract:

Based on a segmented uniform acceleration model, a global velocity planning method was proposed to achieve intelligent connected vehicle navigation in complex and unstructured road scenarios. By analyzing the vehicle’s dynamic characteristics with driving safety and smoothness as the principles, the critical speeds for rollover and sideslip were calculated as the maximum traveling speeds for each path point on unstructured roads. The global velocity planning problem was formulated using a segmented uniform acceleration model, taking into account efficiency, smoothness and energy consumption through a comprehensive loss function. The model considered the continuous variation of slope curvature on unstructured roads and designs variable bounds for vehicle velocity, acceleration, and jerk to constrain the decision variables. By integrating the regenerative braking function of heavy-duty electric vehicles, a specific velocity planning model for electric vehicles in unstructured road scenarios was proposed, and the method was validated through simulations. The results show that the acceleration range of the ego vehicle is stable within -1.0―1.0 m/s2, and the jerk range is stable at -0.5―0.8 m/s3. Compared with the speed planning based on dynamic programming, the proposed speed planning algorithm not only ensures the stability of the vehicle but also reduces the vehicle control inputs. The proposed method has been applied to the autonomous trucks which travel smoothly, the maximum jerk of the truck does not exceed 0.45 m/s3, which shows the stability of the truck.

Key words: unstructured road, speed planning, autonomous driving, motion planning

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