Research On Time Impact Model Of Public Transportation Commuting Trip

Commuting trip is the critical subject of residents’ travel in the city. With the expanding of the city, the residents live farther from their workplaces and the travel time of their commuting trip is becoming longer and longer. As public transportation accounts for the highest percentage in commuting trip among all travel modes, its powerful advantage on solving commuting trip problem attracts more and more attentions. To study resident’s public transportation commuting trip and analyze the influence factors and feature of its travel time is very important to improve the efficiency of resident’s commuting trip.Firstly, this paper used traffic demand and supply theory to analyze the influence factors of public transportation commuting travel time from demand and supply aspect. According to the universality, this paper divided the influence factors into two parts: macro and micro. An influence factors set was established, which contains urban spatial layout, economic development level, traffic regulations, transportation costs, infrastructure conditions etc. The influence mechanism between influence factors and commuting travel time was also analyzed in the paper.Then, this paper explained the structural features of bus IC card data, metro AFC system data, bus GPS data, traffic zone data etc. On the basis of that, a method was put forward to extract public transportation commuting travel time. The method includes five phases: multi-source data correlation matching, extracting the trip’s structures, distinguishing the commuting trip, ascertaining the origin and destination of trip stages, and calculating travel time. For each phase, this paper constructed detailed processing rules and ascertained the discriminated threshold.Finally, this paper selected the location and public transportation infrastructure conditions as influence factors, and built an influence model of commuting travel time using SPSS. According to the traffic zone with or without metro network, the model was divided into two cases. Based on the model analysis, this paper expounded the significance of increasing public transportation network density and promoting the development of multi-center city to shorten residents’ commuting travel time. The results showed that in the traffic zone with metro network, the residents’ public transportation commuting travel time shorten 0.37 min when the density of bus network increases 1 km/km2, and the travel time shorten about 1.61 min when the density of metro network increases 1 km/km2; In the traffic zone without metro network, the residents’ public transportation commuting travel time shorten about 0.44 min when the density of metro network increases 1 km/km2.This study could provide targeted decision data support for making and implementing public transportation optimization plans, and it’s very significant to improve the condition of resident’s commuting trip.