Impact analysis of cooperative perception on the performance of automated driving in unsignalized roundabouts

Front Robot AI. 2023 Aug 15:10:1164950. doi: 10.3389/frobt.2023.1164950. eCollection 2023.

Abstract

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.

Keywords: connected and automated vehicles; cooperative perception; mobile edge computing; motion planning; surrogate safety assessment model; vehicle-to-everything communication.