2019 · 15 citations · 7 references
EngineeringAutomotive EngineeringAutonomous SystemsAutonomous VehiclesVehicle DynamicsVehicle Safety EngineeringIntelligent Transportation SystemsRoad SafetyTraffic EngineeringTraffic Flow ManagementTraffic Flow TheoryTraffic SafetyDriver BehaviorLane Change DynamicsLane-changing ModelsMicroscopic Traffic ModelingSpeedTraffic Flow ModelingTraffic SimulationTraffic Simulation Modeling
Autonomous vehicles will bring tremendous benefits to society. However, it is expected to take a considerable period of time for their spread, and during the transition period, autonomous and manually-driven vehicles will share the same roads. Under such situations, the driving behavior of autonomous vehicles will influence manual drivers, for example, manually-driven vehicles may be stuck behind the autonomous vehicles and overtake them frequently if autonomous vehicles drive slowly for safety. In this paper, we investigate how the traffic flow and driving stress vary with autonomous vehicles by microscopic traffic simulation. We develop a microscopic traffic simulator that can reproduce traffic flow with autonomous vehicles and manually-driven vehicles. The behavior of these vehicles can be modeled by the combination of Intelligent-Driver Model (IDM) and Lane change Model with Relaxation and Synchronization (LMRS). These models can express various driver characteristics through simulation parameters such as driving speed and distance between vehicles (net distance), and we are able to create realistic scenarios like overtaking autonomous vehicles by manually-driven vehicles with faster speed than the legal speed. From the simulation results, we found that there is a desirable combination of speed and time headway that achieves both smooth traffic and less stress of drivers with a given percentage of autonomous vehicles.
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SUMO - Simulation of Urban MObility An Overview
Michael Behrisch, Laura Bieker, Jakob Erdmann et al. · elib (German Aerospace Center) · 2011 · 1.2K citations · Full text