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Title: Automated Scenarios: Simulation of System-Level Travel Effects in the San Francisco Bay Area
Accession Number: 01697818
Record Type: Component
Abstract: In much in the same way that the automobile disrupted horse and cart transportation in the 20th century, automated vehicles hold the potential to disrupt the current system of transportation in the 21st century. Experts predict that vehicles could be fully automated by as early as 2025 or as late as 2035. Research is needed to help the public and private sector understand the potential system level travel effects of automated vehicle to develop policy mechanisms to maximize their benefits and minimize their costs. The authors explore the medium to long run effects of automated vehicles using the San Francisco Bay Area Metropolitan Transportation Commission’s activity-based travel demand model (MTC-ABM). The simulation is unique in that it articulates the size and direction of change on travel for a wide range of automated vehicles scenarios. It is also one of a handful of studies that includes the secondary travel effects (trip generation, destination choice, and mode choice) in its simulations of automated vehicles. Scenarios without pricing show an increase in daily vehicle miles of travel (VMT) (and thus an increase in greenhouse gases (GHG)) that ranges from 2% to 14%, reduced carpooling, transit, walk, and bike travel, and relatively large increases in peak period congestion. Road pricing policies could counteract negative impacts; however, incentives for carpooling may need to be increased to be effective given the travel time benefits of automated vehicles.
Supplemental Notes: This paper was sponsored by TRB committee ABE20 Standing Committee on Transportation Economics.
Report/Paper Numbers: 19-04616
Language: English
Corporate Authors: Transportation Research BoardAuthors: Rodier, Caroline JPourrahmani, ElhamJaller, MiguelFreedman, JoelPagination: 6p
Publication Date: 2019
Conference:
Transportation Research Board 98th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: References
TRT Terms: Identifier Terms: Uncontrolled Terms: Geographic Terms: Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment
Source Data: Transportation Research Board Annual Meeting 2019 Paper #19-04616
Files: TRIS, TRB, ATRI
Created Date: Dec 7 2018 9:38AM
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