Carsharing Demand Estimation

Worldwide carsharing has grown significantly in recent years. The traditional round-trip model is no longer the only carsharing model offered. It is now being accompanied by more flexible options such as one-way station-based, free-floating and peer-to-peer carsharing. Moreover, it has become important to have tools that can estimate both the spatial and temporal demand for carsharing services, providing operators with a good instrument for planning their services. The work presented in this paper makes use of the multiagent simulation tool (MATSIM) to investigate the effects of supply on the demand of the existing round-trip service in the Zurich area of Switzerland. Additionally, the results provide guidance for the possible optimization of the carsharing service. Also presented is an implementation of a one-way station-based model as a part of the MATSIM framework as well as an investigation of the potentials of one-way carsharing service in the study area. Results show that there is still untapped potential of round-trip carsharing, but that service might need optimization. Furthermore, because of greater convenience, one-way carsharing would generate slightly less than three times more trips compared with the round-trip option.

[1]  António Pais Antunes,et al.  Optimization Approach to Depot Location and Trip Selection in One-Way Carsharing Systems , 2012 .

[2]  Kentaro Uesugi,et al.  Optimization of Vehicle Assignment for Car Sharing System , 2007, KES.

[3]  Simone Weikl,et al.  Relocation strategies and algorithms for free-floating Car Sharing Systems , 2013, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[4]  Susan Shaheen,et al.  Carsharing and Personal Vehicle Services: Worldwide Market Developments and Emerging Trends , 2013 .

[5]  Francesco Ciari,et al.  Modeling Station-Based and Free-Floating Carsharing Demand , 2014 .

[6]  Kay W. Axhausen,et al.  Estimation of Carsharing Demand Using an Activity-Based Microsimulation Approach: Model Discussion and Some Results , 2013 .

[7]  Aaron Golub,et al.  City CarShare , 2007 .

[8]  Katherine Kortum,et al.  Driving Smart: Carsharing Mode Splits and Trip Frequencies , 2014 .

[9]  S. Shaheen,et al.  Personal vehicle sharing services in North America , 2012 .

[10]  Ahmed M. El-Geneidy,et al.  Understanding the Factors Affecting Vehicle Usage and Availability in Carsharing Networks: A Case Study of Communauto Carsharing System from Montréal, Canada , 2013 .

[11]  Klaus Bogenberger,et al.  Analyzing External Factors on the Spatial and Temporal Demand of Car Sharing Systems , 2014 .

[12]  Clayton Lane,et al.  PhillyCarShare : First-year social and mobility impacts of carsharing in philadelphia, pennsylvania , 2005 .

[13]  Scott Le Vine,et al.  Strategies for personal mobility: A study of consumer acceptance of subscription drive-it-yourself car services , 2011 .

[14]  Nicolas Lefebvre,et al.  MATSim-T , 2009, Multi-Agent Systems for Traffic and Transportation Engineering.

[15]  Tal Raviv,et al.  Parking reservation policies in one-way vehicle sharing systems , 2014 .

[16]  Gonçalo Homem de Almeida Correia,et al.  Carsharing systems demand estimation and defined operations: a literature review , 2013, European Journal of Transport and Infrastructure Research.

[17]  Francesco Ciari,et al.  Sharing as a key to rethink urban mobility , 2012 .

[18]  Qiang Meng,et al.  A decision support system for vehicle relocation operations in carsharing systems , 2009 .