Robust Platoon Control of Mixed Autonomous and Human-Driven Vehicles for Obstacle Collision Avoidance:A Cooperative Sensing-Based Adaptive Model Predictive Control Approach  

作　　者：Daxin Tian Jianshan Zhou Xu Han Ping Lang 

机构地区：[1]State Key Laboratory of Intelligent Transportation Systems,Beihang University,Beijing 100191,China [2]Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&Safety Control,Beihang University,Beijing 100191,China [3]School of Transportation Science and Engineering,Beihang University,Beijing 100191,China [4]Zhongguancun Laboratory,Beijing 100094,China

出　　处：《Engineering》2024年第11期244-266,共23页工程（英文）

基　　金：supported by the National Key Research and the Development Program of China(2022YFC3803700);the National Natural Science Foundation of China(52202391 and U20A20155).

摘　　要：Obstacle detection and platoon control for mixed traffic flows,comprising human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs),face challenges from uncertain disturbances,such as sensor faults,inaccurate driver operations,and mismatched model errors.Furthermore,misleading sensing information or malicious attacks in vehicular wireless networks can jeopardize CAVs’perception and platoon safety.In this paper,we develop a two-dimensional robust control method for a mixed platoon,including a single leading CAV and multiple following HDVs that incorpo-rate robust information sensing and platoon control.To effectively detect and locate unknown obstacles ahead of the leading CAV,we propose a cooperative vehicle-infrastructure sensing scheme and integrate it with an adaptive model predictive control scheme for the leading CAV.This sensing scheme fuses information from multiple nodes while suppressing malicious data from attackers to enhance robustness and attack resilience in a distributed and adaptive manner.Additionally,we propose a distributed car-following control scheme with robustness to guarantee the following HDVs,considering uncertain disturbances.We also provide theoretical proof of the string stability under this control framework.Finally,extensive simulations are conducted to validate our approach.The simulation results demonstrate that our method can effectively filter out misleading sensing information from malicious attackers,significantly reduce the mean-square deviation in obstacle sensing,and approach the theoretical error lower bound.Moreover,the proposed control method successfully achieves obstacle avoidance for the mixed platoon while ensuring stability and robustness in the face of external attacks and uncertain disturbances.

关 键 词：Connected autonomous vehicle Mixed vehicle platoon Obstacle collision avoidance Cooperative sensing Adaptive model predictive control 

分 类 号：U495[交通运输工程—交通运输规划与管理]