North Carolina Department of Transportation
Research & Innovation Summit – 2021
Road Traffic Simulation with Autonomous Vehicles
Authors: Jinkun Lee, Coleman Ferrell, Matthew James Carroll, and Rui Wu
East Carolina University
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Abstract
Major vehicle manufacturers are shifting towards autonomous electrical vehicles from current Advanced Driver Assistance Systems (ADAS). The replacement of conventional vehicles by autonomous vehicles (AV) is predicted to result in either positive or negative impacts to the traffic network system and this change, represented by penetration rate, will be a transitional process. Agent-based traffic network models with different penetration rate will be useful at understanding the interaction between autonomous and conventional traffic as well as overall traffic network performance. Optimal parameter values for autonomous vehicle models will help the design of autonomous vehicle controller to minimize any negative impact to current traffic network.
We use SUMO, a traffic simulation platform that can incorporate millions of agents, to investigate mixed traffic network models.
