| 引用本文: | 闫立冰,冯健洧,熊嘉伟,申宗,冯海浩,吕宪勇.基于双动态规划和MPC算法的商用车路径规划[J].控制理论与应用,2025,42(8):1505~1514.[点击复制] |
| YAN Li-bing,FENG Jian-wei,XIONG Jia-wei,SHEN Zong,FENG Hai-hao,LV Xian-yong.Commercial vehicle route planning based on dual dynamic programming and MPC algorithm[J].Control Theory & Applications,2025,42(8):1505~1514.[点击复制] |
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| 基于双动态规划和MPC算法的商用车路径规划 |
| Commercial vehicle route planning based on dual dynamic programming and MPC algorithm |
| 摘要点击 1638 全文点击 182 投稿时间：2024-01-19 修订日期：2025-08-05 |
| 查看全文 查看/发表评论 下载PDF阅读器 HTML |
| DOI编号 10.7641/CTA.2024.40048 |
| 2025,42(8):1505-1514 |
| 中文关键词 路径规划 动态规划 模型预测控制 燃油经济性 |
| 英文关键词 path planning dynamic programming model predictive control fuel economy |
| 基金项目 |
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| 中文摘要 |
| 随着“碳达峰、碳中和”世纪目标的提出,以商用车、乘用车为代表的能源消耗行业开始进行新一轮的技术
革命,随着自动驾驶、智能网联技术的发展,融合道路信息的智能驾驶技术正在飞速发展.通过合理地规划车辆速
度, 减少车辆不必要的制动与换挡,减少交通信号灯处的等待时间,可以提高车辆的燃油经济性.本文旨在开发具
有高效性、经济性等优势的商用车路径规划算法,提出了一种双动态规划+模型预测控制(MPC)的控制架构,结合前
方道路上的红绿灯、限速、坡度等信息对车速、车辆位置进行规划,将车辆通行时间以及燃油消耗拆分求解,使其耦
合性减少,保证车辆能够在快速通过前方道路的基础上,进一步提高燃油经济性.同时考虑到车辆跟踪规划路径时
存在偏差,通过MPC对车辆的实际位置进行闭环,在考虑加速度限值的情况下,使车辆完成对规划路径的跟踪,最
终实现车辆的节能降耗.本文通过Simulink+GT-SUITE平台联合仿真验证了所提出的控制策略应用于商用车路径
规划的优越性,与单层动态规划的方案相比,本方案可以省油2.13%. |
| 英文摘要 |
| Withthe proposal of the century goal of “carbon peak and carbon neutrality”, the energy consumption industry
represented by commercial vehicles and passenger vehicles has begun a new round of technological revolution. With the
development of autonomous driving and intelligent network technology, intelligent driving technology that integrates road
information is developing rapidly. By reasonably planning vehicle speed, reducing unnecessary braking and shifting of
vehicles, and reducing waiting time at traffic lights, the fuel economy of vehicles can be improved. This article aims
to develop a commercial vehicle route planning algorithm with advantages such as high efficiency and economy, and
proposes a control architecture based on two-layer dynamic programming + model predictive control (MPC). It combines
information such as traffic lights, speed limits, and slopes on the road ahead to plan the vehicle speed and position, and
splits the vehicle travel time and fuel consumption to reduce coupling, ensuring that the vehicle can further improve fuel
economy while quickly passing through the road ahead. At the same time, considering the deviation in the planned path
of vehicle tracking, the actual position of the vehicle is closed-looped through MPC, and the acceleration limit is taken
into account to enable the vehicle to complete the tracking of the planned path, ultimately achieving energy conservation
and consumption reduction for the vehicle. This article verifies the superiority of the proposed control strategy applied to
commercial vehicle path planning through joint simulation using the Simulink+GT-SUITE platform. Compared with the
single-layer dynamic programming scheme, this scheme can save 2.13% fuel. |
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