System modeling of demand responsive transportation services: Evaluating cost efficiency of service and coordinated taxi usage

Abstract This paper presents a continuum approximation model for the operating cost of demand responsive transit (DRT) systems in large urban networks. Applications of the proposed model shed light on ways demand and characteristics of the DRT system affect major components of cost: fleet, vehicle hours, and vehicle miles traveled. Verifying the relationship with empirical data, results show an accurate approximation of the operating cost for the paratransit system in New Jersey. Furthermore, we develop a systematic approach for evaluating the efficiency of policy implementations for DRTs. Finally, the circumstances where coordinated taxis could be a cost reduction strategy are identified.

[1]  Miguel A. Figliozzi,et al.  Planning Approximations to the Average Length of Vehicle Routing Problems with Varying Customer Demands and Routing Constraints , 2008 .

[2]  Gilbert Laporte,et al.  A concise guide to the Traveling Salesman Problem , 2010, J. Oper. Res. Soc..

[3]  Vikash V. Gayah,et al.  The potential of parsimonious models for understanding large scale transportation systems and answering big picture questions , 2012, EURO J. Transp. Logist..

[4]  Eric J. Gonzales,et al.  The generators of paratransit trips by persons with disabilities , 2014 .

[5]  Carlos F. Daganzo,et al.  An approximate analytic model of many-to-many demand responsive transportation systems , 1978 .

[6]  Luca Quadrifoglio,et al.  Evaluation of Zoning Design with Transfers for Paratransit Services , 2012 .

[7]  Leen Stougie,et al.  On-line single-server dial-a-ride problems , 2001, Theor. Comput. Sci..

[8]  Liping Fu,et al.  Performance Metrics and Data Mining for Assessing Schedule Qualities in Paratransit , 2008 .

[9]  Paul Schonfeld,et al.  Statistical and machine learning approach for planning dial-a-ride systems , 2016 .

[10]  Marco Diana The importance of information flows temporal attributes for the efficient scheduling of dynamic demand responsive transport services , 2006 .

[11]  Mohamadreza Banihashemi,et al.  HEURISTIC APPROACHES FOR SOLVING LARGE-SCALE BUS TRANSIT VEHICLE SCHEDULING PROBLEM WITH ROUTE TIME CONSTRAINTS , 2002 .

[12]  Eric J. Gonzales,et al.  Demand responsive transit systems with time-dependent demand: User equilibrium, system optimum, and management strategy , 2016 .

[13]  Gilbert Laporte,et al.  A Tabu Search Heuristic for the Static Multi-Vehicle Dial-a-Ride Problem , 2002 .

[14]  Michal Jakob,et al.  Market Mechanism Design for Profitable On-Demand Transport Services , 2015, ArXiv.

[15]  Carlos F. Daganzo,et al.  The Distance Traveled to Visit N Points with a Maximum of C Stops per Vehicle: An Analytic Model and an Application , 1984, Transp. Sci..

[16]  Liping Fu Analytical Model for Paratransit Capacity and Quality-of-Service Analysis , 2003 .

[17]  Miguel A. Figliozzi,et al.  Planning Approximations to Average Length of Vehicle Routing Problems with Time Window Constraints , 2009 .

[18]  Liping Fu,et al.  Improving Paratransit Scheduling by Accounting for Dynamic and Stochastic Variations in Travel Time , 1999 .

[19]  Liping Fu,et al.  Quantifying Technical Efficiency of Paratransit Systems by Data Envelopment Analysis Method , 2007 .

[20]  Liping Fu,et al.  Fleet Size and Mix Optimization for Paratransit Services , 2004 .

[21]  Paul Schonfeld,et al.  Planning Dial-a-Ride Services , 2013 .

[22]  Nan Xia,et al.  A model for the fleet sizing of demand responsive transportation services with time windows , 2006 .

[23]  Martin W. P. Savelsbergh,et al.  The General Pickup and Delivery Problem , 1995, Transp. Sci..