Optimization of VDOT Safety Service Patrols to Improve VDOT Response to Incidents ; Drivers in a Driverless Future: The Impact of Autonomous Vehicles on Paid Drivers

Rivero, Emilio, School of Engineering and Applied Science, University of Virginia
Norton, Peter, EN-Engineering and Society, University of Virginia
Porter, Michael, EN-Eng Sys and Environment, University of Virginia

What is the future of driving? Automated driving systems may displace human
drivers, with complex implications for employment, safety, sustainability, and social

How may traffic congestion be eased? Crashes exacerbate traffic delays, causing
productivity losses. The Virginia Department of Transportation (VDOT) operates a fleet
of Safety Service Patrols (SSPs) that assist emergency responders in scene clearance.
Managers of the SSP program seek to optimize scheduling of patrollers for safety and
congestion relief. The research team developed a genetic-algorithm-based route
scheduling algorithm that assigns SSP routes to minimize the total time vehicles are
stranded on I-95 in Virginia before an SSP vehicle arrives. The results indicate that a new
route schedule may reduce total response time approximately 20 percent.

Developers of autonomous vehicles (AVs) and employers of drivers are reacting
differently to autonomous vehicles (AVs) than professional drivers. Truckers, ride
sharing drivers, and public transport workers generally fear AVs will displace
employment; AV developers and employers, however, generally insist their jobs are safe.
Employers stand to benefit from the deployment of AVs at the expense of the drivers.

BS (Bachelor of Science)
Autonomous Vehicles, Transportation, Traffic Congestion, Paid Drivers, Optimization

School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: Michael Porter
STS Advisor: Peter Norton
Technical Team Members: Elizabeth Campbell, Emma Chamberlayne, Julie Gawrylowicz, Colin Hood, Allison Hudak, and Matthew Orlowsky

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