Research On Multi-objective Timing Optimization Of Urban Single Intersection Based On Wi-Fi Data Acquisition Equipment

With the development of the economy,the number of motor vehicles has increased significantly,and the urban transportation problem is becoming increasingly serious.The intersection is a bottleneck in the urban road network,so it is of great significance to optimize the signal timing of the intersection.Under this background,this thesis research the timing optimization of single point intersection based on Wi-Fi data acquisition equipment.First,considering the advantages of Wi-Fi data acquisition equipment for easy installation and maintenance,low price,and so on,a new single intersection traffic information detection scheme based on Wi-Fi data acquisition equipment is designed.Determine the hardware architecture design and layout principles of Wi-Fi data collection equipment,realize the collection of Wi-Fi data at single-point intersections,and then design the Wi-Fi data processing process,using k-means clustering,LSTM neural network prediction model and multiple linear regression analysis algorithms to obtain the space mean speed of the intersection road section,vehicle steering ratio and traffic flow,to achieve the detection and prediction of various types of traffic information at the intersection.Second,based on the detection scheme to predict the traffic flow with error disturbance Data,research the multi-objective timing optimization algorithm for single-point plane intersections,and take the average vehicle delay,average vehicle parking rate and intersection capacity as optimization objectives to establish a multi-objective timing optimization model that considers error disturbances,and apply NSGA-II algorithm to solute this model.Finally,taking the intersection of Weiyang Road and Fengchengwulu Road in Xi’an as an example and simulation object,Wi-Fi data acquisition equipment was deployed on the spot to verify the new single-point intersection traffic information detection scheme proposed in this paper.The SUMO simulation performs parameter calibration and selects the average vehicle delay,average queue length,capacity,the average fuel consumption of motor vehicles,the average parking rate of motor vehicles and noise as evaluation indicators.In SUMO simulation,the multi-objective timing optimization algorithm in this paper is compared with the original timing scheme and Webster timing scheme.The results show that the multi-objective timing scheme optimization algorithm is better than the original timing scheme and Webster timing scheme under different error disturbances of medium and high traffic demand.Under low traffic demand and different error disturbances,various indicators of the multi-objective timing optimization algorithm are close to the Webster timing scheme and superior to the original timing scheme,which fully verifies the effectiveness of the multi-objective timing optimization algorithm in this paper under different traffic demands and different error disturbances.