A Repositioning Method for Shared Autonomous Vehicles Operation

摘要: Abstract Shared fully-automated, or autonomous, mobility (SAVs) is anticipated to be the likely choice for future urban travel. SAVs boast many operational benefits but will add congestion in form of unoccupied miles. The fleet’s success further depends on service measures like wait times pickup trips. Agent-based simulation tools have closely looked at SAV operations typically lack integration between supply and demand sides when simulating a population scale. This paper focuses impact relocation traveler using novel algorithm repositioning. POLARIS, an agent-based tool, used case study Bloomington, Illinois quantify allowing On average, were lower with repositioning all adequate fleet sizes. available more uniformly across region’s zones, proportional trip-making different day. In addition, enable higher share demands served. Finally, increase empty miles from may justified trips being served, overall improvement times.