基于云控的卡车编队分布式协同换道控制  

Cloud-controlled distributed cooperative lane-changing controlfor truck platooning

作　　者：王江锋[1] 满忠运 梁欢欢 唐风敏 冷卫杰 WANG Jiangfeng;MAN Zhongyun;LIANG Huanhuan;TANG Fengmin;LENG Weijie(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,P.R.China;National Innovation Center of Intelligent and Connected Vehicles,Beijing 100029,P.R.China)

机构地区：[1]北京交通大学交通运输学院,北京100044 [2]国家智能网联汽车创新中心,北京100029

出　　处：《重庆邮电大学学报(自然科学版)》2025年第2期174-184,共11页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

基　　金：国家重点研发计划项目(T24B05300090);河北省省级科技计划项目(236Z0802G)。

摘　　要：针对混合交通流和云控环境下的卡车编队换道问题,提出编队整体式和先解编后组编的分布式协同换道策略,设计了基于滑模变结构的编队车间距稳定控制算法。使用NS-3和SUMO搭建云控仿真平台,通过模拟前车异常静止这一典型风险场景进行实验验证。针对低、中、高3种流量,采取分布式换道策略使得风险区范围内整体交通流的平均速度比整体式换道策略分别提高5.1、6.9、9.3百分点,加速度波动幅度分别减小42.8、46.7、45.3百分点。敏感性分析显示,换道决策区长度的增加有助于提升整体交通流的通行效率和平顺性。For the problem of cooperative lane-changing in mixed traffic flow and cloud-controlled environments for truck platoons,this study proposes an overall platoon lane-changing strategy and a distributed lane-changing strategy of first disassembling and then forming,and also designs a vehicle spacing stability control algorithm based on sliding mode variable structure.A cloud-controlled simulation platform is built using NS-3 and SUMO,and experiments are conducted to validate the strategies by simulating a typical risk scenario where the lead vehicle abnormally comes to a halt.The effectiveness analysis shows that the cloud-controlled truck platoon lane-changing strategies effectively improve the throughput efficiency and smoothness of the overall traffic flow.Compared with the overall lane-changing strategy,the distributed lane-changing strategy demonstrates superior lane-changing performance.For low,medium,and high traffic volumes,adopting the distributed lane-changing strategy increases the average speed of the overall traffic flow within the risk zone by 5.1,6.9,and 9.3 percentage point,respectively,and reduces the acceleration fluctuation amplitude of the overall traffic flow by 42.8,46.7,and 45.3 percentage point,respectively.Sensitivity analysis indicates that increasing the length of the lane-changing decision area helps to enhance the throughput efficiency and smoothness of the overall traffic flow.

关 键 词：卡车编队 高速公路 车路云协同 协同换道 混合交通流 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] U491[自动化与计算机技术—计算机科学与技术]