Abstract
In order to capture spatiotemporal distribution pattern of passenger flow under networked condition, it is necessary to analyze route choice behavior of urban rail transit passengers. First, angular cost value and comfort index are defined to reflect the influence of network structures, route directions and in-vehicle congestion on passengers’ route choice behavior respectively; Then, two route choice models are proposed respectively for peak and off-peak hours, in which new variables including angular cost value, comfort index and personal characteristics, as well as level of service variables (i.e. in-vehicle travel time, number of transfers and transfer time etc. , which are usually found in the base model) are considered. Finally, the models are calibrated with the surveyed data from Guangzhou Metro and compared with each other. The results show that the new variables significantly improve models’ explanatory and predictive abilities on route choice behavior of urban rail transit passengers.
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