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Title: Shared automated vehicle fleet operations for first-mile last-mile transit connections with dynamic pooling

Journal Article · · Computers, Environment and Urban Systems
 [1];  [1]; ORCiD logo [2]
  1. Univ. of Texas, Austin, TX (United States)
  2. Transportation Data Analytics National Renewable Energy Laboratory, Golden, CO (United States)

Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM connections, as a mode that provides flexibility in access/egress decisions and is well coordinated with train station schedules. To achieve this objective, a novel dynamic pooling algorithm was introduced to match SAVs with riders while coordinating the riders' arrival times at the light-rail station to a known train schedule. Microsimulations of SAVs and travelers throughout two central Austin neighborhoods show how larger service areas, higher levels of SAV demand, and longer arrival times between successive trains require larger SAV fleet sizes and higher SAV utilization rates to deliver close traveler wait times. Four-person SAVs appear to perform similar to 6-seat SAVs but will cost less to provide. Using a dynamic pooling algorithm tightly coordinated with train arrivals (every 15 min) delivers 87% of travelers to their stations in time to catch the next train, whereas uncoordinated assignments deliver just 58% of travelers in time.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation and Fuels. Vehicle Technologies Office (VTO); USDOE
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1837994
Alternate ID(s):
OSTI ID: 1832070
Report Number(s):
NREL/JA-5400-80487; MainId:42690; UUID:bc25317f-dae5-4aed-b76a-c17a2c08c61f; MainAdminID:63522
Journal Information:
Computers, Environment and Urban Systems, Vol. 92; ISSN 0198-9715
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Figures / Tables (9)