
This paper reports the implementation and results of a simulation-based analysis of the impact of cloud/edge-enabled cooperative perception on the performance of automated driving in unsignalized roundabouts. This is achieved by comparing the performance of automated driving assisted by cooperative perception to that of a baseline system, where the automated vehicle relies only on its onboard sensing and perception for motion planning and control. The paper first provides the descriptions of the implemented simulation model, which integrates the SUMO road traffic generator and CARLA simulator. This includes descriptions of both the baseline and cooperative perception-assisted automated driving systems. We then define a set of relevant key performance indicators for traffic efficiency, safety, and ride comfort, as well as simulation scenarios to collect relevant data for our analysis. This is followed by the description of simulation scenarios, presentation of the results, and discussions of the insights learned from the results.
Robotics and AI, vehicle-to-everything communication, Artificial Intelligence, surrogate safety assessment model, Electronic computers. Computer science, TJ1-1570, connected and automated vehicles, mobile edge computing, Mechanical engineering and machinery, QA75.5-76.95, motion planning, cooperative perception, Computer Science Applications
Robotics and AI, vehicle-to-everything communication, Artificial Intelligence, surrogate safety assessment model, Electronic computers. Computer science, TJ1-1570, connected and automated vehicles, mobile edge computing, Mechanical engineering and machinery, QA75.5-76.95, motion planning, cooperative perception, Computer Science Applications
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