Disaggregated spatiotemporal traffic assignment for road reservation service and supply-demand statistical analysis

Abstract

This paper develops a disaggregated spatiotemporal traffic assignment method with a system-optimal (SO) orientation and analyzes the supply-demand matching degree with four statistical indexes under the background of a road reservation system. Three key issues are addressed. Firstly, the paper illustrates the service process of a road reservation system. It is essential to know how the road reservation system works and the difference between it and other reservation systems. Secondly, a spatiotemporal discretization expression method based on the system-optimal traffic assignment (SOTA) model with predictive origin-destination demand for link travel time is put forward to make the supply space could be reserved, and the demand would not be mutually interfering. Thirdly, the study proposes a reverse feasible spatiotemporal route searching algorithm based on the expected arrival time to individually assign the applicants on the road network. This route searching algorithm does not use the network topology but the spatiotemporal discretized links. The departure time preference was considered in the feasible spatiotemporal route searching algorithm. Moreover, as the real demand distribution of the whole reservation area is not difficult to obtain after a period of updates, it is possible to analyze the supply-demand matching degree of the road network. Thus, four statistical indexes are proposed to assess the state variation of the road network. Simulation results verify the effectiveness and efficiency of the proposed method. The novel reverse feasible routes searching algorithm has a system-optimal trend with inputting the demand individually and an acceptable calculating efficiency. The method proposed by this paper could ensure a reliable road reservation service with accurate demand prediction. Considering the departure time preference would not bring extra burden to the road reservation system but provide more user-friendly service. Through the analysis, the supply-demand matching degree of the road network is significantly influenced by the cohesive capacity connection of the upstream and downstream links. This indicates the network structure and road attributes optimization should be considered in enhancing the road reservation service.