Optimizing charging station locations for urban taxi providers

Recently, electric vehicles are gaining importance which helps to reduce dependency on oil, increases energy efficiency of transportation, reduces carbon emissions and noise, and avoids tail pipe emissions. Because of short daily driving distances, high mileage, and intermediate waiting time, fossil-fuelled taxi vehicles are ideal candidates for being replaced by battery electric vehicles (BEVs). Moreover, taxi BEVs would increase visibility of electric mobility and therefore encourage others to purchase an electric vehicle. Prior to replacing conventional taxis with BEVs, a suitable charging infrastructure has to be established. This infrastructure consists of a sufficiently dense network of charging stations taking into account the lower driving ranges of BEVs.

[1]  Lai Tu,et al.  Understanding operational and charging patterns of Electric Vehicle taxis using GPS records , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[2]  Yajing Gao,et al.  Optimal Planning of Charging Station for Phased Electric Vehicle , 2013 .

[3]  Keechoo Choi,et al.  Shared-Taxi Operations with Electric Vehicles , 2012 .

[4]  Kit Po Wong,et al.  Traffic-Constrained Multiobjective Planning of Electric-Vehicle Charging Stations , 2013, IEEE Transactions on Power Delivery.

[5]  Claudio Casetti,et al.  Optimal deployment of charging stations for electric vehicular networks , 2012, UrbaNe '12.

[6]  Hao Wang,et al.  Operations of a Taxi Fleet for Advance Reservations Using Electric Vehicles and Charging Stations , 2013 .

[7]  Suzanna Long,et al.  Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions , 2012 .

[8]  Markus Litzlbauer,et al.  Zukünftige Energienetze mit Elektromobilität – Überblick der Projektziele , 2012 .

[9]  Mark S. Daskin,et al.  Network and Discrete Location: Models, Algorithms and Applications , 1995 .

[10]  Hannes Koller,et al.  Utilizing mobility data to facilitate the introduction of E-Taxis in Vienna: Feasibility study of a decision support system for the introduction of battery electric vehicles as Taxis , 2014, 2014 International Conference on Connected Vehicles and Expo (ICCVE).

[11]  Céline Robardet,et al.  Characterizing the speed and paths of shared bicycles in Lyon , 2010, ArXiv.

[12]  Hua Cai,et al.  Siting public electric vehicle charging stations in Beijing using big-data informed travel patterns of the taxi fleet , 2014 .

[13]  Richard L. Church,et al.  The maximal covering location problem , 1974 .

[14]  S Latham,et al.  A reference book of driving cycles for use in the measurement of road vehicle emissions , 2009 .

[15]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[16]  Ruth Dalton,et al.  Hybrid-OD matrix based simulation approach to identify e-charging hotspots in transport network , 2014, 2014 IEEE Transportation Electrification Conference and Expo (ITEC).

[17]  Hong Liu,et al.  The planning of electric vehicle charging station based on Grid partition method , 2011, 2011 International Conference on Electrical and Control Engineering.

[18]  Kara M. Kockelman,et al.  THE ELECTRIC VEHICLE CHARGING STATION LOCATION PROBLEM: A PARKING-BASED ASSIGNMENT METHOD FOR SEATTLE , 2013 .

[19]  Yu Nie,et al.  A corridor-centric approach to planning electric vehicle charging infrastructure , 2013 .

[20]  Matthew Andrews,et al.  Modeling and Optimization for Electric Vehicle Charging Infrastructure , 2012 .

[21]  Melitta Dragaschnig,et al.  Novel road classifications for large scale traffic networks , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[22]  Mark S. Daskin,et al.  Strategic facility location: A review , 1998, Eur. J. Oper. Res..

[23]  Fang He,et al.  Optimal deployment of public charging stations for plug-in hybrid electric vehicles , 2013 .