Abstract
The uptake of Electric Vehicles (EVs) is rapidly changing the landscape of urban mobility services. Transportation Network Companies (TNCs) have been following this trend by increasing the number of EVs in their fleets. Recently, major TNCs have explored the prospect of establishing privately owned charging facilities that will enable faster and more economic charging. Given the scale and complexity of TNC operations, such decisions need to consider both the requirements of TNCs and local planning regulations. Therefore, an optimisation approach is presented to model the placement of CSs with the objective of minimising the empty time travelled to the nearest CS for recharging as well as the installation cost. An agent based simulation model has been set in the area of Chicago to derive the recharging spots of the TNC vehicles, and in turn derive the charging demand. A mathematical formulation for the resulting optimisation problem is provided alongside a genetic algorithm that can produce solutions for large problem instances. Our results refer to a representative set of the total data for Chicago and indicate that nearly 180 CSs need to be installed to handle the demand of a TNC fleet of 3000 vehicles.
Highlights
Mobility as a Service (MaaS) platforms such as Demand Responsive Traffic (DRT), car-sharing and ride-sharing platforms have increasingly become popular around the world as remedial measures to reduce traffic congestion
Their introduction has coincided with the increasing uptake of Electric Vehicles (EVs) which are more environmentally friendly compared to vehicles with conventional combustion engines [3,4,5,6]
In this paper we made an empirical study for the placement of charging stations dedicated to Transportation Network Companies (TNCs) EVs
Summary
Mobility as a Service (MaaS) platforms such as Demand Responsive Traffic (DRT), car-sharing and ride-sharing platforms have increasingly become popular around the world as remedial measures to reduce traffic congestion. These schemes have introduced major shifts in the interaction between travellers, transport infrastructure, and public transport schemes. Several initiatives that promote the use of MaaS schemes to reduce private usage already exist [1,2] Their introduction has coincided with the increasing uptake of Electric Vehicles (EVs) which are more environmentally friendly compared to vehicles with conventional combustion engines [3,4,5,6]. Charging speeds and battery capacities, which are matters of particular concern for fleet operators have been improving recently [8]
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