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2021 | OriginalPaper | Buchkapitel

AI-Based Traffic Queue Detection for IoV Safety Services in 5G Networks

verfasst von : Simone Grilli, Gianmarco Panza

Erschienen in: Intelligent Technologies for Internet of Vehicles

Verlag: Springer International Publishing

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Abstract

With the deployment of 5th Generation networks, characterized by a wider bandwidth and an increased computational capability, is now possible to develop more complex services that requires low latency, such as applications for public safety based on artificial intelligence. To this aim, it has been studied a possible use of the so-called Multi-access Edge Computing (MEC) enabled by 5G that reduces the latency thanks to computational resources located closer to the user. This allows to deploy an application that recognizes the formation of traffic queues on the highway through the analysis of video streams, to be used in the context of smart mobility. In order to do so, it is needed to detect the travelling vehicles and to track their movement to understand when a traffic jam is occurring. For the implementation, the Convolutional Neural Network (CNN) paradigm has been leveraged for the detection of the vehicles. Among the several alternatives compared, it has been chosen the third version of You Only Look Once (YOLO) for its trade-off between accuracy and real-time computation. Then, the detections tracked through the Simple Online and Realtime Tracking (SORT) algorithm are exploited to identify the direction of the traffic flows and then to calculate when the vehicles are slowing down or stopping, by either measuring the number of stationary vehicles or the travelling time of the vehicles within a region of interest. The service has been developed with the objective of being employed through the parallel computation offered by 5G MEC servers equipped with modern GPUs, in order to obtain real-time performances.

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Vorheriges Kapitel Intelligent Approaches for Fault-Tolerance in Radio Communication of Autonomous Vehicles

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Titel: AI-Based Traffic Queue Detection for IoV Safety Services in 5G Networks
verfasst von: Simone Grilli
Gianmarco Panza
Verlag: Springer International Publishing
Buch: Intelligent Technologies for Internet of Vehicles
Print ISBN: 978-3-030-76492-0

Electronic ISBN: 978-3-030-76493-7

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-76493-7_3

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