Lane Work-Schedule of Toll Station Based on Queuing Theory and PSO-LSTM Model

Abstract

A reasonable lane work-schedule in each time period can not only guarantee the traffic efficiency of toll stations, but also reduce the operating cost of toll stations. This paper proposes a comprehensive solution for lane work plan. Firstly, the average queue length is selected as a good index for measuring the congestion of toll station. And then, based on the queuing theory, the service level of toll station is divided into four levels according to the relationship between the average queue length and traffic capacity. Secondly, based on the toll data, a toll station congestion prediction model is established with the Long Short-Term Memory model (LSTM) and the particle swarm optimization (PSO) algorithm. In this model, the average queue length, service time and traffic volume are selected as three inputs, the average queue length value of the next hour is the output. Thirdly, on the basis of meeting the secondary level service level of toll stations, the lane work-schedule model is established. Then, the number of lanes opened in each time period can be calculated by using this model and congestion prediction results. Fourthly, considering the two scenarios of weekday and weekend, the effectiveness of the methods proposed in this paper is analyzed and verified with the toll data of the Dongshe, Changfeng, and Linfen toll stations in Shanxi Province. Finally, based on operating costs analysis, the results show that the proposed solution could effectively realize the reasonable work-schedule of the toll station.