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Handling Occlusions in Automated Driving Using a Multiaccess Edge Computing Server-Based Environment Model From Infrastructure Sensors

Michael Buchholz, Johannes Müller, Martin Herrmann, Jan Strohbeck, Benjamin Völz, Matthias Maier, Jonas Paczia, Oliver Stein, Hubert Rehborn, Rüdiger-Walter Henn

2021IEEE Intelligent Transportation Systems Magazine44 citationsDOIOpen Access PDF

Abstract

Sensors in an automated vehicle (AV) can encounter occlusions caused by other traffic, buildings, and vegetation, especially in urban areas. Information from infrastructure sensors sent via vehicle-to-anything communication can help. We have developed and prototypically implemented an infrastructure environment model generated from infrastructure sensors on a multi-access edge computing server on an LTE/5G mobile network. This extends an AV’s field of view and is integrated into the vehicle’s motion planning schemes. In this article, after a description of our approach, we present and discuss real-world results from a pilot site at a public junction that were obtained using prototype AVs.

Topics & Concepts

Enhanced Data Rates for GSM EvolutionComputer scienceField (mathematics)Real-time computingComputer networkServerEdge computingUbiquitous computingTelecommunicationsHuman–computer interactionMathematicsPure mathematicsAutonomous Vehicle Technology and SafetyVehicular Ad Hoc Networks (VANETs)Context-Aware Activity Recognition Systems
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