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.
Urban Transit Coordination Using an Artificial Transportation System
IEEE Transactions on Intelligent Transportation Systems ; 12 , 2 ; 374-383
2011-06-01
1098431 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Urban Transit Coordination Using an Artificial Transportation System
Online Contents | 2011
|Coordination Evaluation Model of Metropolitan Rail Transit and Urban Transportation System
Springer Verlag | 2018
|Transportation-Getting around town: automatic urban transit
Tema Archiv | 1976
|Urban transportation, rapid transit and surface lines
Engineering Index Backfile | 1925
|Coordination of Public Transit and School Bus Transportation
British Library Conference Proceedings | 1998
|