Quentin K. Wan

A Mixed Integer Formulation for Multiple-Route Transit Network Design

We consider the design of multiple transit lines in a network and present a mixed integer formulation for this multiple-route transit network design problem (MRTNDP). With the introduction of node labels, the formulation can exploit the route structure and hence attains efficiency in obtaining a cost minimizing transit network design.

MULTIMODAL TRANSIT SERVICES WITH HETEROGENEOUS TRAVELERS

Public transit systems play a pivotal role in serving the transportation needs of many major cities. In Hong Kong, for example, more than 90% of the 11 million daily trips are provided by public transit services. The planning and design of these services, therefore, are important welfare considerations. The situation is particularly intriguing if these services are to be provided by the private sector whose primary objective is not to ensure welfare gains or an efficient utilization of the road space but to maximize profit. Analyses are of significant interest and potential application to many transit-oriented cities. In metropolitan areas in which multi- or intermodal trips are common, modeling the multimodal route-choice characteristics of heterogeneous travelers and the strategic interactions among the many private firms are important issues. In this study, mode-choice models were integrated in a network of competing transit operators. A novel network structure, designated as the state-augmented multimodal (SAM) network, was developed via a state augmentation approach. With this SAM network, the effect of fare competition and regulations on social welfare as well as on profitability of the companies could be examined. A case study of the ground transportation system connecting the Hong Kong International Airport with the city’s downtown was conducted.

Bus Tolling for Urban Transit System Management

For transit services operated by competitive private companies, as in Hong Kong, the objectives of the companies are not to minimize the total traveler and/or infrastructure costs, but to optimize their profits. Other than engaging in a Bertrand Game, companies may also compete via their service frequencies. As evident in Hong Kong, the intense competition has led to a very visible phenomenon - companies putting more and more buses on major (profitable) corridors, leading to significant increases in congestion. This study aims to analyze externality pricing through bus tolling to manage the congestion caused by them. The result shows that bus tolling can be a promising tool.

Discrete Choice Modeling with Partially Missing Information from a Revealed Preference Survey

Survey data, collected to calibrate discrete choice models, are often primarily missing information on some attributes. Ways to fill in missing data are needed in order to apply standard calibration procedures; however, this may result in seriously biased estimates. In this paper, we propose a calibration approach that takes advantage of the information of the observed attributes as well as to infer the missing data statistics. In doing so, we show in a simulated dataset that the calibration can produce a fairly good estimate and it correctly accounts for tendency of bias between users and non-users.

ON BUS TOLLING TO REGULATE THE URBAN TRANSIT SYSTEM

For transit services operated by competitive public companies, as in Hong Kong, the objectives of the companies are not to minimize the total traveler and/or infrastructure construction costs, but to optimize their profits. Other than engaging in a Bertrand Game, companies may also compete via their service frequencies. As evident in Hong Kong, the intense competition has led to a very visible phenomenon-companies putting more and more buses on major (profitable) corridors, leading to significant increases in congestion on them. This study aims to analyze such externality pricing through bus tolling. The result shows that bus tolling can be a promising congestion management tool.