[1]李海青,李永福,郑太雄,等.复杂交通环境下智能车辆避障方法研究[J].智能系统学报,2023,18(6):1275-1286.[doi:10.11992/tis.202210033]
LI Haiqing,LI Yongfu,ZHENG Taixiong,et al.Obstacle avoidance method for intelligent vehicles in complex environments[J].CAAI Transactions on Intelligent Systems,2023,18(6):1275-1286.[doi:10.11992/tis.202210033]
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LI Haiqing,LI Yongfu,ZHENG Taixiong,et al.Obstacle avoidance method for intelligent vehicles in complex environments[J].CAAI Transactions on Intelligent Systems,2023,18(6):1275-1286.[doi:10.11992/tis.202210033]
复杂交通环境下智能车辆避障方法研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
18
期数:
2023年第6期
页码:
1275-1286
栏目:
学术论文—智能系统
出版日期:
2023-11-05
- Title:
- Obstacle avoidance method for intelligent vehicles in complex environments
- Keywords:
- intelligent vehicle; potential model; HMM; dynamic obstacle avoidance; path planning; tracking control; MPC; complex environments
- 分类号:
- TP27；U491.25
- 摘要:
- 为了提高智能车辆避障的安全性与舒适性，提出了一种基于改进势场模型与隐马尔可夫模型的避障方法。首先建立了考虑车辆特性、道路环境与行驶状态等因素的改进势场模型，预测碰撞风险的动态变化；其次利用隐马尔可夫模型进行避障方式决策，并在改进的势场模型中融入隐马尔可夫决策层，完成自车避障路径规划；然后利用模型预测控制方法对规划的避障路径进行实时跟踪，并在控制器中加入松弛因子与约束条件防止出现无最优解；最后应用联合仿真对提出的避障方法进行验证，结果表明，所提出的方法可在复杂交通环境下获得无碰撞的避障路径，实现动态避障的同时，提高了车辆的安全性与舒适性。
- Abstract:
- An obstacle avoidance method based on an improved potential field model and hidden Markov model (HMM) is proposed to enhance the safety and comfort of intelligent vehicles during obstacle avoidance. First, the method constructed an improved field model by considering typical elements of vehicle attributes, road environment, and driving states to predict the dynamic changes in collision risk. Further, HMM was used for obstacle avoidance decision making, and path planning was performed by incorporating HMM into the improved potential field model. Next, the model predictive control was used to track the planning paths in real time, and a relaxation factor and constraints were added to the controller to prevent the problem of unavailable optimal solutions. Finally, the cosimulations by CarSim and MATLAB/Simulink were conducted to verify the effectiveness of the proposed method. Results show that the proposed method can enhance driving safety and ride comfort while obtaining collision-free driving paths in various situations and realizing dynamic obstacle avoidance.
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- 相似文献/References:
-
[1]王星,赵海良,王志刚.基于邻域系统的智能车辆最优轨迹规划方法[J].智能系统学报,2019,14(5):1040.[doi:10.11992/tis.201805004]
WANG Xing,ZHAO Hailiang,WANG Zhigang.Optimal trajectory planning method of intelligent vehicles based on neighborhood system[J].CAAI Transactions on Intelligent Systems,2019,14():1040.[doi:10.11992/tis.201805004]
备注/Memo
收稿日期:2022-10-26。
基金项目:国家自然科学基金项目(62273067, U1964202); 国家重点研发计划项目(2018YFB1600500); 重庆市自然科学基金面上项目(cstc2020 jcyj-msxmX0915); 重庆市教委青年项目(KJQN202100644).
作者简介:李海青,讲师,博士,主要研究方向为智能网联汽车、智能控制。承担国家级、省部级科研项目3项,发表学术论文30余篇。;李永福,教授,博士,主要研究方向为智能网联汽车、智能交通系统。承担国家级、省部级科研项目20余项,发表学术论文100余篇;郑太雄,教授,博士,主要研究方向为车辆主动安全控制、多机器人协同控制。承担国家级、省部级等科研项目10余项,发表学术论文60余篇
通讯作者:李海青.E-mail:lihq@cqupt.edu.cn
更新日期/Last Update:
1900-01-01