In this paper, we study the design of a free floating car sharing system based on electric vehicles. We rely on data about millions of rentals of a free floating car sharing operator based on internal combustion engine cars that we recorded in four cities. We characterize the nature of rentals, highlighting the non-stationary, and highly dynamic nature of usage patterns. Building on this data, we develop a discrete-event trace-driven simulator to study the usage of a hypothetical electric car sharing system. We use it to study the charging station placement problem, modeling different return policies, car battery charge and discharge due to trips, and the stochastic behavior of customers for plugging a car to a pole. Our data-driven approach helps car sharing providers to gauge the impact of different design solutions. Our simulations show that it is preferred to place charging stations within popular parking areas where cars are parked for short time (e.g., downtown). By smartly placing charging stations in just 8% of city zones, no trip ends with a discharged battery, i.e., all trips are feasible. Customers shall collaborate by bringing the car to a charging station when the battery level goes below a minimum threshold. This may reroute the customer to a different destination zone than the desired one; however, this happens in less than 10% of all trips.
|Titolo:||Free Floating Electric Car Sharing: A Data Driven Approach for System Design|
|Data di pubblicazione:||2019|
|Digital Object Identifier (DOI):||10.1109/TITS.2019.2932809|
|Appare nelle tipologie:||1.1 Articolo in rivista|
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