Integration of Microsimulation and Optimized Autonomous Intersection Management
2018-12
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Integration of Microsimulation and Optimized Autonomous Intersection Management
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2018-12
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Autonomous intersection management (AIM) is a type of intersection control for autonomous vehicles which eliminates the need for a traffic signal by using vehicle-to-infrastructure communication. Vehicles communicate information to an intersection manager which determines vehicle ordering and spacing such that vehicles can pass safely through the intersection. Reservation-based AIM, which give vehicles space-time path reservations through an intersection, has the potential to greatly increase the capacity of intersections by allowing an intersection controller to optimize all vehicle paths. A mixed-integer linear program is proposed which gives more flexibility in optimizing vehicle acceleration. This model was integrated with the microsimulation software Aimsun and scenarios were simulated which included fluctuating vehicle demands, altering vehicle speeds, and modifying spacing between vehicles. The results indicate that the model proposed in this study can reduce delay and increase average speed experienced by vehicles compared to the existing reservation-based intersection control formulations and conventional signal controls.
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University of Minnesota M.S. thesis. December 2018. Major: Civil Engineering. Advisor: Michael Levin. 1 computer file (PDF); ix, 84 pages.
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Olsson, Jack. (2018). Integration of Microsimulation and Optimized Autonomous Intersection Management. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/202077.
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