Designing and Managing Infrastructure for Shared Connected Electric Vehicles

Electric vehicles (EVs) generally lead to a reduction in greenhouse gas emissions and have the potential to reduce our dependency on fossil fuels and increase the penetration of renewable sources of energy. Further, new mobility services, like carsharing in general and free-float carsharing (FFCS) in particular, have the potential to reduce the need for car ownership and complement transit, ultimately reducing vehicle miles traveled. Electric free-float carsharing (eFFCS) is the amalgamation of the two concepts, which promotes emission-free mobility, while providing the flexibility of owning and operating the vehicle only between and during the points of travel. The pay-per-minute-use subscription model and features like park anywhere within service area make FFCS quite attractive for the environmental and economically conscious, ever-mobile, smartphone-savvy population of the 21st century. Presently, due to slow recharging times of electric vehicles compared to gasoline-fueled vehicles, a charging event represents a constraint on trips and requires staff labor to relocate the free-floating vehicle to a charging station. This relocation leads to a high operational expenditure and unreliable downtimes. This study aims to develop a demand model for an eFFCS service in the City of Seattle. The model consists of a destination model predicting end location given the start location, and a duration model predicting the dwell time after a trip at a particular location. This model can increase the feasibility of eFFCS by reducing the cost of relocation by optimally locating the charging stations near the areas of heavy usage and real-time control to minimize manual relocation.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Appendices; Figures; Maps; References; Tables;
  • Pagination: 35p

Subject/Index Terms

Filing Info

  • Accession Number: 01688528
  • Record Type: Publication
  • Contract Numbers: 69A3551747124
  • Files: UTC, NTL, TRIS, ATRI, USDOT
  • Created Date: Dec 17 2018 10:26AM