Vehicle-based interactive management with multi-agent approach

Under the energy crisis and global warming, mass transportation becomes more important than before. The disadvantages of mass transportation, plus the high flexibility and efficiency of taxi and with the revolution of technology, electric-taxi is the better transportation choice for metropolis. On t...

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Detalles Bibliográficos
Autores: Chen, Yee Ming, Wang, Bo-Yuan
Tipo de recurso: artículo
Fecha de publicación:2009
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099/8238
Acceso en línea:https://hdl.handle.net/2099/8238
Access Level:acceso abierto
Palabra clave:Local transit
Taxicabs
Electric vehicles
Dial-a-ride
Multiagent
Dispatch
Transport públic
Taxis
Vehicles elèctrics
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions::Modelització de transports i logística
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Desenvolupament sostenible::Mobilitat sostenible
Descripción
Sumario:Under the energy crisis and global warming, mass transportation becomes more important than before. The disadvantages of mass transportation, plus the high flexibility and efficiency of taxi and with the revolution of technology, electric-taxi is the better transportation choice for metropolis. On the other hand, among the many taxi service types, dial-a-ride (DAR) service system is the better way for passenger and taxi. However the electricity replenishing of electric-taxi is the biggest shortage and constraint for DAR operation system. In order to more effectively manage the electric-taxi DAR operation system and the lots of disadvantages of physical system and observe the behaviors and interactions of simulation system, multi-agent simulation technique is the most suitable simulation technique. Finally, we use virtual data as the input of simulation system and analyze the simulation result. We successfully obtain two performance measures: average waiting time and service rate. Result shows the average waiting time is only 3.93 seconds and the service rate (total transport passenger number / total passenger number) is 37.073%. So these two performance measures can support us to make management decisions. The multiagent oriented model put forward in this article is the subject of an application intended in the long term to supervise the user information system of an urban transport network.