An Agent-based model to assess the impacts of introducing a shared-taxi system in Lisbon ( Portugal )

This paper presents a simulation procedure to assess the market potential for the implementation of a new shared taxi service in Lisbon (Portugal). The proposed shared taxi service has a new organisational design and pricing scheme which aims to use the capacity in traditional taxi services in a more efficient way. In this system a taxi acting in “sharing” mode offers lower prices to its clients, in exchange for them to accept sharing the vehicle with other persons who have compatible trips, (time and space) while also increasing the revenue for the operator. The paper proposes and tests an agent based simulation model in which a set of rules for space and time matching between the shared taxis and passengers is identified considering a maximum deviation from the original route and then presents an algorithm that considers the following different objectives: minimum cost per passenger.km, maximum revenue per vehicle.km, minimum passenger in-vehicle time, minimum vehicle idle time. An experiment for the city of Lisbon is presented with the objective of testing the proposed simulation conceptual model and to show the potential of sharing taxis for improving mobility management in urban areas. General Terms: Algorithms; Design; Performance

[1]  Iyad Rahwan,et al.  Multiagent self-organization for a taxi dispatch system , 2009, AAMAS 2009.

[2]  Vukan R Vuchic,et al.  Urban transit systems and technology , 2007 .

[3]  Der-Horng Lee,et al.  Towards An Automated Multiagent Taxi-Dispatch System , 2007, 2007 IEEE International Conference on Automation Science and Engineering.

[4]  G. Correia,et al.  Carpooling and carpool clubs: Clarifying concepts and assessing value enhancement possibilities through a Stated Preference web survey in Lisbon, Portugal , 2011 .

[5]  Adam J. Hodges,et al.  ‘Roping the Wild Jitney’: the jitney bus craze and the rise of urban autobus systems , 2006 .

[6]  Niels A. H. Agatz,et al.  The Value of Optimization in Dynamic Ride-Sharing: A Simulation Study in Metro Atlanta , 2010 .

[7]  Mustafa S. Canbolat,et al.  Fareplay: An examination of taxicab drivers' response to dispatch policy , 2010, Expert Syst. Appl..

[8]  José Manuel Viegas,et al.  A traffic analysis zone definition: a new methodology and algorithm , 2009 .

[9]  M. Kemp,et al.  Para-Transit: Neglected Options for Urban Mobility , 1974 .

[10]  Paul Cullen.  Taxi! Urban Economies and the Social and Transport Impacts of the Taxicab , 2011 .

[11]  Keechoo Choi,et al.  An agent-based simulation model for analyzing the impact of asymmetric passenger demand on taxi service , 2011 .

[12]  Richard Darbéra,et al.  Taxicab regulation and urban residents' use and perception of taxi services: a survey in eight cities , 2010 .

[13]  R. Jayakrishnan,et al.  Effect of Taxi Information System on Efficiency and Quality of Taxi Services , 2005 .

[14]  P. K. Chande,et al.  Taxi despatch: a fuzzy rule approach , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[15]  Der-Horng Lee,et al.  Taxi Dispatch System Based on Current Demands and Real-Time Traffic Conditions , 2003 .

[16]  Susan Shaheen,et al.  Carsharing and Partnership Management: An International Perspective , 1999 .

[17]  Ker-Tsung Lee,et al.  Planning and Design of a Taxipooling Dispatching System , 2005 .

[18]  Hao Wang,et al.  Microscopic Traffic Simulation Based Dispatch Modeling for Taxi Booking Service , 2011 .

[19]  Jorge A. Vanegas,et al.  Transportation system sustainability issues in high-, middle-, and low-income economies : Case studies from georgia (U.S.), South Korea, Colombia, and Ghana , 2006 .