Simulation Study of Fully Automated Vehicles With Self-Parking Capabilities in Texas Estimates a Reduction in Conflict Points by 7 to 45 Percent with Penetration Rates of 25 and 75 Percent, Along With Increase in Parking Capacity.

A Simulation Study Using a Campus Network in El Paso Reveals Parking Safety and Capacity Improvements Stemming from Introduction of Self-Parking, Fully Automated Vehicles.

Date Posted
03/31/2023
Identifier
2023-B01734
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The Future of Parking: Safety Benefits and Challenges

Summary Information

With the rise of emerging Fully Automated Vehicle (FAV) technologies, including self-driving and self-parking features, parking experiences are expected to improve in the future. To this end, this study explored parking facility design and operational change recommendations to improve parking safety in the presence of self-parking features. The study identified potential design changes and different self-parking penetration scenarios to improve safety and parking capacity using the University of Texas at El Paso (UTEP) campus as a case study. 

METHODOLOGY

The study examined three parking options (on-street, off-street, and parking garage) by selecting one facility on the UTEP campus for each. Initially, three scenarios were considered for each option with different FAV market penetrations (zero, 25 and 75 percent) without any design improvements. The off-street and parking garage options were further evaluated with two additional scenarios, featuring a multi-row layout for more parking spaces. These two additional scenarios were then modified for the on-street parking option in which FAVs were designed to park outside the UTEP campus, while non-FAVs remained inside the campus, as FAVs were anticipated to drop off their users and park at a designated parking facility. The study developed a total of 15 scenarios, including existing conditions. 

Microscopic traffic simulation software was used to assess the scenarios in terms of conflicts for vehicles and pedestrians and exposure for pedestrians. The Surrogate Safety Assessment Model (SSAM) developed by the Federal Highway Administration was used to identify and analyze vehicle-to-vehicle conflicts using vehicle trajectory data output from the simulation model. For pedestrian-vehicle conflicts, the study utilized the relative pedestrian-vehicle exposure, defined as the number of vehicles expected to come in contact with pedestrians at a particular parking facility. Pedestrian-vehicle exposure incorporated walking time of a driver from their parked car to the exit of the parking facility, and the rate at which vehicles were expected to enter the shared facility.

FINDINGS

  • The results suggested that, compared to the base scenarios, FAVs could reduce the number of vehicle-to-vehicle conflict points by 8 to 45 percent for on-street parking with the FAV penetration rates of 25 percent and 75 percent, respectively.
  • For off-street parking, the results suggested that, compared to the base scenarios, FAVs could reduce the number of conflict points by 7 to 44 percent with the FAV penetration rates of 25 percent and 75 percent, respectively.
  • For parking garages, the results indicated that, compared to the base scenarios, FAVs could reduce the number of conflict points by 7 to 45 percent with the FAV penetration rates of 25 percent and 75 percent, respectively.
  • Parking capacity increase was calculated to be between 9 and 20 percent for off-street parking and parking garages with the FAV penetration rates of 25 percent and 75 percent, respectively.
  • The study also found that recommended layout changes for off-street parking could reduce pedestrian-vehicle exposure by 32 to 72 percent with FAV penetration rates of 25 percent and 75 percent, respectively.
  • For parking garages, the reduction in pedestrian-vehicle exposure ranged from 14 to 46 percent with the recommended layout changes with the FAV penetration rates of 25 percent and 75 percent, respectively. 
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