Urban Transit Coordination Using an Artificial Transportation System

Authored by Lefei Li, Han Zhang, Xiaofang Wang, Wei Lu, Zongping Mu

Date Published: 2011-06

DOI: 10.1109/tits.2010.2060195

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

An urban transit system usually consists of several modes, including busses, streetcars, a subway, and light rail. Unfortunately, coordination among different modes remains a challenging problem. Difficulties arise when modifying the transit network structure on a strategic level or when synchronizing timetables on a tactical level. Traditional transit network design and timetabling intend to solve a network-optimization problem based on static origin-destination (OD) information, with passenger assignment as a subproblem. In this paper, we propose an artificial urban transit system (AUTS) based on agent-based modeling and simulation. With AUTS, which is a special type of artificial transportation system (ATS), we are able to dynamically model the passenger's behavior and route choice and use the system to predict transit demand on a simplified transit network. The AUTS has the following important potential applications: forecasting transit flow; setting key parameters for urban transit networks-such as service frequencies and the capacity of subway trains-evaluating alternative modifications to subway rail and bus routes; and predicting the impact of special/emergency events to the transit network. We create a demonstration system of the Beijing transit network and present its applications in experiments.

Tags

Agent-based modeling and simulation (ABMS) artificial transportation system (ATS) transit coordination urban transit network