Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6936071 | Transportation Research Part C: Emerging Technologies | 2018 | 12 Pages |
Abstract
This study simulated performance characteristics of SAEV fleets serving travelers across the Austin, Texas 6-county region. The simulation works in sync with the agent-based simulator MATSim, with SAEV modeling as a new mode. Charging stations are placed, as needed, to serve all trips requested (under 75â¯km or 47 miles in length) over 30â¯days of initial model runs. Simulation of distinctive fleet sizes requiring different charge times and exhibiting different ranges, suggests that the number of station locations depends almost wholly on vehicle range. Reducing charge times does lower fleet response times (to trip requests), but increasing fleet size improves response times the most. Increasing range above 175â¯km (109 miles) does not appear to improve response times for this region and trips originating in the urban core are served the quickest. Unoccupied travel accounted for 19.6% of SAEV mileage on average, with driving to charging stations accounting for 31.5% of this empty-vehicle mileage. This study found that there appears to be a limit on how much response time can be improved through decreasing charge times or increasing vehicle range.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Benjamin Loeb, Kara M. Kockelman, Jun Liu,