Research On Coordinated Optimization Control Method Of Urban Off-ramp And Adjacent Intersection

The connected area of expressway off-ramp and adjacent intersection is one of the important traffic bottlenecks in urban roads,in which the queue overflows on off-ramps and arterial roads often affect the operation of expressway mainline and ground traffic.Therefore,it has important engineering application significance to establish an integrated and coordinated control method for the off-ramp and adjacent intersection.Firstly,starting from the analysis of the traffic operation characteristics of the off-ramp and adjacent intersection,this paper describes the main reasons of off-ramp congestion,analyzes the influences of the geometric structure of off-ramp and the traffic organization of study area,and focuses on the research of the lane-changing of weaving area and queuing at the intersection,which lay a solid foundation for traffic flow modeling.Secondly,the paper introduces the basic principle of CTM(cell transmission model)model and then the cell topological structure is constructed by introducing virtual cell of changing lanes.Based on the signal control characteristics of intersections and the lane changing characteristics of the connected areas,the model of turn lane and weaving area are constructed respectively.The paper finally designs the operational process of the regional traffic flow model.Moreover,aiming at solving the problem of expressway off-ramp congestion and queue overflows,this paper proposed a heuristic coordinated control method by integrating the traffic signal control of intersection and the mainline route diversion strategy.With the maximum queue length of the intersection as the constraint,according to the real-time queue status of the off-ramp,the signal control scheme of the intersection is made to alleviate the off-ramp congestion.When the off-ramp reaches the maximum queue length,the mainline route diversion strategy is designed and heuristic control rules are formulated to curb queue overflow.Furthermore,due to the model parameter calibration rely on subjective judgment and the control effect is not optimal in the heuristic control method,this paper established a coordinated optimization control method for off-ramp and adjacent intersection.The optimization goal is minimize the overall delay and maximum the traffic throughout of intersection and the constraints are the maximum queue length of off-ramp and intersection,cycle time and green time.Then we applied genetic algorithm to calculate the control parameters in real time to maximum the control effect while avoiding queue overflow at the off-ramp and intersection.Finally,taking the off-ramp of Minxiangyuan Road,Chengdong Avenue Expressway,Xuzhou,which is under construction,as a simulation object,this paper applied MATLAB software to establish a cellular network topology based on the traffic flow model of the offramp and adjacent intersection,designed and realized non-coordinated control method,heuristic coordinated control method and coordinated optimization control method,and analyzed and evaluated the application effect of each control method from evaluation indexes such as queue length,traffic throughout,and vehicle average delay.The simulation results show that compared with non-coordinated method,the heuristic coordinated control method: the queue length of off-ramp in low traffic hour is reduced by 16.7m,and the queue length at the east and west entrances of intersections are reduced by 10.7m and 19.8m,respectively,while the south and north entrance only increased by 4.8m and 5.4m;the queue length of off-ramp is reduced by 40.0m in peak hour and the queue length of deceleration lane is only 5.8m.Compared with the heuristic coordinated control method,the coordinated optimization control method: the queue length of off-ramp in low traffic hour is basically equal and the average vehicle delay is reduced by 29.2s;the queue length of off-ramp in peak hour is decreased by 36.9m and the traffic throughout of intersection and weaving area are respectively increased by 30 veh and 19veh;During the entire simulation period,the overall vehicle delay and average vehicle delay reduced by 5.7% and 3.5% respectively.