Traffic Flow Modeling And Analysis On Complex Weaving Area Of Mountain City Trunk Road Considering Vehicle Driving Behaviors

Restricted by terrain and road conditions,there are many lanes and flow directions in some of the main road interweaving areas,and the interweaving area is short,and the phenomenon of interweaving of vehicles changing lanes is more complicated.Studying the driving behavior of vehicles in the interweaving zone and effectively modeling is the key and foundation for proving the traffic operation mechanism in the interweaving zone.In order to explore the traffic operation characteristics of such complex interweaving areas,based on high-precision,full-sample vehicle micro-trajectory data,this paper proposes a refined cellular automaton car following model and lane-changing decision-making model in interweaving areas to capture and reproduce short distances more finely Actual vehicle behavior and traffic flow conditions in the multi-lane interweaving area.The content research is as follows:(1)Vehicle microscopic trajectory data extraction and analysis based on drone video.Because the behavior of vehicles in complex interweaving areas requires more fine-grained time and space scales,this paper extracts and analyzes traffic flow,lane density,bicycle speed,front spacing,acceleration,speed angle,etc.with a time scale of 0.1s and a space scale of 0.1m.Traffic flow information,extract and analyze vehicle lane changing behavior information such as the number of lane changes,location and direction.The results show that the complex lane-changing conditions,such as the congestion of lane-changing conditions,frequent lane-changing behavior,rapid acceleration and deceleration,and other abnormal behaviors increase,vehicle interference and conflict intensify,affect the safety and efficiency of traffic operation in the interweaving area,and easily form a traffic congestion bottleneck.(2)Partitioned car-following model based on refined cell size and time step.According to the differences in traffic and geometric characteristics of vehicles in the upstream and downstream and interweaving areas,the idea of zoning modeling is used to divide the research scope into several zonings with independently set variables and rules,and the cell size of the model is refined And update the time step to more realistically reflect the actual car following behavior characteristics.(3)Construct up-downstream free lane change model and double-layer lane change decision model in the interweaving influence area.In order to meticulously characterize the complex vehicle lane-changing behavior in the interweaving zone,considering the differences between the upstream and downstream and the interweaving zone lane-changing demand intensity and lane-changing constraints,in the upstream and downstream lane-changing models,the free lane-changing spacing conditions and Logistic lane-changing probability were established condition.In the lane-changing model of the interweaving influence zone,multi-step decision-making of lane-changing timing is carried out according to safety risks,and a double-layer lane-changing of the interweaving influence zone based on risk-type and mandatory-type 5 lane-changing spacing conditions and category 3 lane-changing probability conditions is established.Decision model.(4)Numerical simulation and analysis.Based on the measured data during the peak period of the four-kilometer interweaving area in Chongqing,the simulation and verification analysis of the unzoned lane change decision model,zoned multi-channel merge lane change model,zone zone lane change decision model(the model in this paper).This paper selects the complex interweaving area of typical mountain city trunk lines,analyzes the microscopic traffic operation characteristics,and constructs a fine-grained cellular automata behavior decision model based on zoning modeling.Verification shows that compared with the measured data,the model’s average lane flow error is 1.64%,the speed distribution average error is 4.14%,and the average number of lane changes is 11.85%.It shows that the model in this paper can better reflect the characteristics of traffic flow such as flow,density,speed distribution,etc.,describe the difference in vehicle demand and intensity at different locations,and describe the complex vehicle behavior in the multi-lane interweaving area.Capacity calculation and optimization management and control provide theoretical and methodological support.