摘要
为改善智能网联环境下匝道合流区通行安全与效率问题,提出了一种近邻匝道交通耦合自组织方法,通过建立主线车流间隙与匝道车辆速度优化匹配模型,以实现对主线最外侧车道总体车头间距的优化调整,在保证汇入安全的前提下提升了近邻匝道内的车辆通行效率;选取重庆市内环快速路上东环立交附近2个近邻匝道为研究原型,利用在线地图结合无人机航拍以及定点摄像等数据采集方式对试验路段进行实地调查;在智能网联环境下,分别运用协同自适应巡航控制(CACC)和交通耦合自组织方法(TCS),采用Python、SUMO和TraCI对试验路段车辆运行情况进行联合仿真。研究结果表明:相较于CACC,TCS的换道次数从65.52次降至52.64次,下降了19.87%,有效缓解了近邻匝道内的交通冲突;平均延误从24.53 s降至14.39 s,下降了70.38%,其中平峰期降低了77.71%,高峰期只降低了34.50%,相较于高峰期,在平峰期的运行效率提升较大;时间占有率从18.70%降至8.63%,下降了53.86%,不同车道间的时间占有率之差降低至6.00%,即车辆在不同车道上的分布更平均;平均速度从78.31 km·h^(-1)上升至80.78 km·h^(-1),提升了3.06%,有效缓解了合流区和分流区附近的减速情况。
A self-organizing method for traffic coupling between adjacent ramps was proposed to improve traffic safety and efficiency in on-ramp merging areas in intelligent and connected environments.By establishing an optimal matching model between the mainline traffic flow gap and on-ramp vehicle speed,the overall headway of the outermost lane of the mainline was optimized and adjusted.On the premise of ensuring the safe merging of on-ramp vehicles,the traffic efficiency of vehicles between adjacent ramps was improved.Two adjacent ramps near the Donghuan overpass on the inner ring expressway in Chongqing were selected as the research prototype.Online map combined with drone aerial photography,fixed-point photography,and other data acquisition methods were used to conduct field investigations on the testing sections.In intelligent and connected environments,cooperative adaptive cruise control(CACC)and traffic coupling self-organizing(TCS)method were applied respectively,and Python,SUMO,and TraCI were used for co-simulation of vehicle operation on the test road.Research results show that compared with CACC,the lane changing number in TCS decreases by 19.87%from 65.52 to 52.64,which effectively alleviates the traffic conflict between adjacent ramps.The average delay decreases by 70.38%from 24.53 s to 14.39 s.To be specific,the average delay decreases by 77.71%in the off-peak period and 34.50%in the peak period,respectively.Compared with the peak period,the efficiency in the off-peak period is greatly improved.The time occupancy decreases by 53.86%from 18.70%to 8.63%.The time occupancy difference between different lanes decreases to 6.00%,that is,vehicles are more evenly distributed across different lanes.The average speed increases by 3.06%from 78.31 km·h^(-1)to 80.78 km·h^(-1),which effectively alleviates the deceleration near the on-ramp merging and off-ramp diverging areas.2 tabs,9 figs,31 refs.
作者
马庆禄
王欣宇
张书
段学锋
MA Qing-lu;WANG Xin-yu;ZHANG Shu;DUAN Xue-feng(College of Traffic and Transportation,Chongqing Jiaotong University,Chongqing 40o074,China;Chongqing Key Laboratory of Intelligent Integrated Three-Dimensional Transportation,Chongqing Jiaotong University,Chongqing 40oo74,China;Ningxia Jiaotou Expressway Management Co.,Ltd.,Yinchuan 750000,Ningxia,China)
出处
《交通运输工程学报》
EI
CSCD
北大核心
2024年第2期207-220,共14页
Journal of Traffic and Transportation Engineering
基金
国家自然科学基金项目(52072054)
重庆市技术创新与应用发展专项(CSTB2022TIAD-STX0003)
宁夏回族自治区交通运输厅科技项目(NJGF(2020)0301)
重庆交通大学研究生科研创新项目(CYB23256)。
关键词
交通控制
通行效率
自组织方法
近邻匝道
智能网联
平均交通延误
traffic control
traffic efficiency
self-organizing method
adjacent ramp
intelligent and connected
average traffic delay
