Passenger route choice model and algorithm in the urban rail transit network
Abstract: There are several
routes between some OD pairs in the urban rail transit network. In order to
carry out the fare allocating, operators use some models to estimate which
route the passengers choose, but there are some errors between estimation
results and actual choices results. The aim of this study is analyzing the
passenger route choice behavior in detail based on passenger classification and
improving the models to make the results more in line with the actual
situations.
Design/methodology/approach: In this paper, the passengers were divided
into familiar type and strange type. Firstly passenger integrated travel
impedance functions of two types were established respectively, after that a
multi-route distribution model was used to get the initial route assignment
results, then a ratio correction method was used to correct the results taking
into account the transfer times, crowd and demand for seats. Finally, a case
study for the Beijing local rail transit network is shown.
Findings: The numerical example showed that it is logical to take
passenger classification and the model and algorithm is effective, the final
route choice results are more comprehensive and realistic.
Originality/value: The paper offers an improved model and algorithm based
on passenger classification for passenger route choice in the urban rail
transit network.
Author: Ke Qiao, Peng Zhao,
Zhi-peng Qin
Journal Code: jptindustrigg130042