The Impacts of Automated Vehicles on Center City Parking Demand
Michael Zhang and
Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis
The potential for automated vehicles (AVs) to reduce parking in city centers has generated much excitement among urban planners. AVs could drop-off (DO) and pick-up (PU) passengers in areas where parking costs are high: personal AVs could return home or park in less expensive locations, and shared AVs could serve other passengers. Reduced on-street and off-street parking present numerous opportunities for redevelopment that could improve the livability of cities, for example, more street and sidewalk space for pedestrian and bicycle travel. However, reduced demand for parking would be accompanied by increased demand for curbside DO/PU space with related movements to enter and exit the flow of traffic. This change could be particularly challenging for traffic flows in downtown urban areas during peak hours, where high volumes of DOs and PUs are likely to occur. Only limited research examines the travel effects of a shift from parking to DO/PU travel and the impact of changes in parking supply. This study uses a microscopic road traffic model with local travel activity data to simulate personal AV parking scenarios in San Francisco's downtown central business district. These scenarios vary (1) the demand for DO and PU travel versus parking, (2) the supply of on-street and off-street parking, and (3) the total demand for parking and DO/PU travel due to an increase in the cost of travel to the central business district. 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)
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