Research On The Optimization Of Traffic Organization In The Upstream Area Of Toll Station Based On The Multi-Agent Cellular Automata Model

With the application of automobile intelligent technology and the development of automobile electronic technology,the number of motor vehicles in all parts of the world continues to rise as a blowout growth,which leads to problems such as traffic jams,conflicts,and disorder on the highway.These problems need to be solved urgently.However,in the current research on traffic organization in the upstream area of toll station,there is still no suitable algorithm to solve the problem of low robustness of trajectory data,and the application scenarios are limited.The exploration and mining of traffic conflicts need to be further expanded,and the integration of research related to traffic organization optimization and emerging technologies needs to be further developed.Based on the previous research,the paper defines the research scope of the upstream area of toll station,and clarifies the significance of the toll signs to the road section division.Then,based on the YSKT algorithm framework,the vehicle trajectory data extraction in the upstream area of the toll station is carried out,and the effective rate reaches 95.90%.At the same time,based on the extracted 196,893 vehicle trajectory data,the traffic flow in the upstream area of the toll station with different vehicles and different lanes was analyzed from four aspects: macro characteristics,speed characteristics,lane changing characteristics,and time characteristics.Secondly,combined with cellular automata and multi-agent technology,the MACA model of expressway toll plaza is innovatively constructed.Among them,the road segment Agent-CA matrix segmentation modeling idea can be widely used in the establishment of MACA models of various complex traffic scenarios.The vehicle Agent-CA model and the driver DACAM model are integrated into the module information such as turn signal Agent and brake light Agent.According to the driver’s driving preferences and behavioral decisions,further optimize the lane-changing rules and lane-changing conditions of traditional cellular automata traffic scenarios from the algorithm level.The toll sign Agent-CA model is an important hub for communication and interaction in the MACA model through segmented signal transmission.Finally,taking the typical hybrid main line toll station-Huai’an toll station as an example,the simulation parameters of the MACA model are determined and the model reliability is verified.The results show that the error rates of CATF,average speed of main road and average speed of diversion area are 0.90%,0.43% and 0.50%,which shows that the model has high accuracy and stability.Then,the traffic organization in the upstream area of the expressway toll station under different conditions is analyzed,and the MACA model simulation under 9 different conditions is designed by using the orthogonal test method.Through these analytical tests,the optimization is carried out from the perspectives of the number and layout of MTC and ETC lanes,the speed limit in the upstream area of the toll station,and the layout of the toll station signs.The optimal combination of traffic organization in the upstream area of the toll station is obtained.