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The Impacts of Automated Vehicles on Center City Parking Demand, Congestion, and Emissions

Huajun Chai, Caroline Rodier, Jeffery Song and Michael Zhang

Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis

Abstract: Parking has long been an urban planning challenge. Providing parking in city centers is land-intensive and expensive. Moreover, drivers searching for scarce parking can increase congestion, vehicle miles traveled (VMT), and greenhouse gas (GHG) emissions. Use of automated vehicles to drop off and pick up travelers could reduce the demand for parking, which could reduce VMT and associated emissions and allow urban spaces currently used for parking to be converted to more beneficial uses. However, automated vehicles could also have negative consequences. They could generate empty vehicle travel and more cross-traffic movements due to drop-offs and pick-ups which could increase congestion, VMT, and GHG emissions. Researchers at the University of California, Davis modeled the travel effects of changes in drop-off and pick-up activity and parking supply that might be triggered by widespread automated vehicle use in San Francisco’s city center. A primary goal of this research was to determine an optimal level of automated vehicle adoption that minimizes negative consequences. The researchers also modeled methods to control these negative consequences, including expanding drop-off and pick-up zones and imposing auto pricing policies to curb demand. This policy brief summarizes the findings from that research and provides policy implications. View the NCST Project Webpage

Keywords: Engineering; Social and Behavioral Sciences; Autonomous vehicles; Central business districts; City planning; Curb side parking; Exhaust gases; Parking demand; Traffic models; Travel behavior; Vehicle miles of travel (search for similar items in EconPapers)
Date: 2020-10-01
New Economics Papers: this item is included in nep-ene, nep-env, nep-tre and nep-ure
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