01514295

Component

This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network – one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capturing the inherent variation in users' route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a data set from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared to 30% for the single class model.

This paper was sponsored by TRB committee AP025 Public Transportation Planning and Development. Alternate title: Multiclass Traffic Assignment Model for Predicting Transit Passenger Flows: Case Study of Beijing Subway Network.

01503729

14-0928

English

17p

2014

Transportation Research Board 93rd Annual Meeting

Digital/other

Figures; References; Tables

Case studies; Passenger traffic; Subways; Traffic assignment

Multiclass traffic assignment; Passenger flow

Beijing (China)

Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2014 Paper #14-0928

TRIS, TRB, ATRI

Jan 27 2014 2:23PM