The Performance and Benefits of a Shared Autonomous Vehicles Based Dynamic Ridesharing System: An Agent-Based Simulation Approach
The recently introduced concept of Shared Autonomous Vehicle (SAV) system, a taxi system without drivers or a short-term rental car-sharing program with autonomous vehicles, presents great potential to promote ridesharing travel behavior. Given the reliability and flexibility provided by the SAV system, some hurdles in the current ridesharing programs, such as lack of flexibility to handle near term travel schedule changes, can be overcome. However, the existing studies regarding SAV system are limited to non-ridesharing (NR) systems. To fulfill this research gap, this study designed and applied an agent-based model to simulate the performance and estimate the potential benefits of an SAV system with dynamic ridesharing (DR-SAV). The modeled DR-SAV system will assign SAVs to serve vehicle-trips, with similar travel profile as in 2009 National Household Travel Survey (NHTS), in a 10*10 mile grid based city, for each one-minute time step. Two vehicle-trips may voluntarily participate into the ridesharing service, if both of them are willing to share rides with strangers and the additional delay time cost triggered by ridesharing can be offset by travel cost reductions. Preliminary results show that a DR-SAV system can provide more satisfactory level of service compared with an NR-SAV system, in terms of shorter trip delays, more reliable services (especially during peak hours), less Vehicle Miles Travelled (VMT) generation, and less trip costs. Additionally, the results also indicate that a DR-SAV system can be more environment-friendly in the long run.
-
Supplemental Notes:
- This paper was sponsored by TRB committee AP040 Automated Transit Systems. Alternate title: Performance and Benefits of Shared Autonomous Vehicle-Based Dynamic Ridesharing System: Agent-Based Simulation Approach.
-
Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Zhang, Wenwen
- Guhathakurta, Subhrajit
- Fang, Jinqi
- Zhang, Ge
-
Conference:
- Transportation Research Board 94th Annual Meeting
- Location: Washington DC, United States
- Date: 2015-1-11 to 2015-1-15
- Date: 2015
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 15p
- Monograph Title: TRB 94th Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Alternatives analysis; Benefits; Intelligent vehicles; Performance measurement; Ridesharing; Simulation; Taxi services; Vehicle fleets; Vehicle sharing
- Uncontrolled Terms: Agent based models
- Subject Areas: Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01553124
- Record Type: Publication
- Report/Paper Numbers: 15-2919
- Files: TRIS, TRB, ATRI
- Created Date: Feb 12 2015 9:10AM