Carsharing demand estimation and fleet simulation with EV adoption

Abstract Carsharing helps mitigate transportation congestion, parking demand, as well as the environmental, and social transportation challenges in cities. Besides providing vehicle access to lower income households, it lowers emissions and reduces vehicle miles traveled (VMT) as well as the number of vehicles registered. Despite these benefits, carsharing systems have been slow to develop in China. Little is known about carsharing demand in China's context, and subsequent system design parameters. This paper explores potential carsharing demand, fleet size, and economic performance in Beijing. To determine these, carsharing mode split is estimated by a stated preference choice modeling exercise. Adequate fleet size is estimated through a Monte Carlo simulation that includes factors such as vehicle types (electric or gasoline vehicle), charger types for electric vehicles (level 2 or level 3 chargers) that influence charging time, arrival rates, travel distance, and travel time based on the time intervals (peak or non-peak hours). In addition, this study estimates the payback period to recover sunk costs. Results indicate that the carsharing mode split ranges from 9% to 32% and an electric vehicle fleet with level 2 chargers is more appropriate for carsharing in Beijing.

[1]  Foo Tuan Seik.  Vehicle ownership restraints and car sharing in Singapore , 2000 .

[2]  A. Maitra,et al.  Evaluation of the impact of plug-in electric vehicle loading on distribution system operations , 2009, 2009 IEEE Power & Energy Society General Meeting.

[3]  Victoria Nerenberg,et al.  Evaluation Results of San Francisco Bay Area Station-Car Demonstration , 1999 .

[4]  Megan S. Ryerson,et al.  Better Pen-and-Paper Surveys for Transportation Research in Developing Countries , 2014 .

[5]  D. Dissanayake,et al.  Investigating household vehicle ownership, mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region , 2010 .

[6]  Khandker Nurul Habib,et al.  Synopsis of Users’ Behaviour of a Carsharing Program: A Case Study in Toronto , 2012 .

[7]  D. McFadden,et al.  AN APPLICATION OF DIAGNOSTIC TESTS FOR THE INDEPENDENCE FROM IRRELEVANT ALTERNATIVES PROPERTY OF THE MULTINOMIAL LOGIT MODEL , 1977 .

[8]  Anjali Awasthi,et al.  Evaluation of carsharing network's growth strategies through discrete event simulation , 2012, Expert Syst. Appl..

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

[10]  D. Sperling,et al.  Carsharing in Europe and North American: Past, Present, and Future , 1998 .

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

[12]  Susan Shaheen,et al.  Peer-to-Peer Carsharing , 2014 .

[13]  Ron S. Kenett,et al.  Statistics for Business and Economics. , 1988 .

[14]  Karina Funk,et al.  ELECTRIC VERSUS CONVENTIONAL VEHICLES: SOCIAL COSTS AND BENEFITS IN FRANCE , 1999 .

[15]  Kevin Morrow,et al.  Plug-in Hybrid Electric Vehicle Charging Infrastructure Review , 2008 .

[16]  D. Hensher,et al.  Stated Choice Methods: Analysis and Applications , 2000 .

[17]  Christopher R. Cherry,et al.  One-way and round-trip carsharing: A stated preference experiment in Beijing , 2017 .

[18]  Ryuichi Kitamura,et al.  A dynamic model system of household car ownership, trip generation, and modal split: model development and simulation experiment , 2009 .

[19]  Jessica ter Schure,et al.  Car-Sharing: Where and How It Succeeds , 2005 .

[20]  John Byrne,et al.  Assessing the Potential Extent of Carsharing , 2005 .

[21]  M. Barth,et al.  Carsharing and Station Cars in Asia , 2006 .

[22]  Clayton Lane.  PhillyCarShare , 2005 .

[23]  Elliot Martin,et al.  Carsharing Parking Policy , 2010 .

[24]  Hewu Wang,et al.  Levelized costs of conventional and battery electric vehicles in china: Beijing experiences , 2015, Mitigation and Adaptation Strategies for Global Change.

[25]  F. Creutzig,et al.  Climate change mitigation and co-benefits of feasible transport demand policies in Beijing , 2009 .

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

[27]  Lee D. Han,et al.  Electric bike sharing: simulation of user demand and system availability , 2014 .

[28]  R. Hampshire,et al.  Peer-to-Peer Carsharing , 2011 .

[29]  Matthew Barth,et al.  Simulation model performance analysis of a multiple station shared vehicle system , 1999 .

[30]  D. McFadden.  Conditional logit analysis of qualitative choice behavior , 1972 .

[31]  Susan Shaheen,et al.  Policy Considerations for Carsharing and Station Cars: Monitoring Growth, Trends, and Overall Impacts , 2004 .