Reference : Towards a Framework to Evaluate Cooperative Perception for Connected Vehicles
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/48765
Towards a Framework to Evaluate Cooperative Perception for Connected Vehicles
English
Hawlader, Faisal mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PI Engel >]
Frank, Raphaël mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SEDAN >]
Nov-2021
Proceedings of the 13th IEEE Vehicular Networking Conference 2021
Yes
International
[en] Connected and Automated Vehicle ; Cooperative Perception ; V2X
[en] Over the past few years, Connected and Autonomous Vehicles (CAVs) have gained significant research attention. With the recent deployment of 5G networks in many metropolitan areas, new cooperative driving concepts are emerging. One of those is cooperative perception, where vehicles exchange sensory information via a V2X network to maximize their awareness horizon without the need for additional and potentially expensive sensors. The idea is to distribute the processing of the sensor information to find the best trade-off between data transmission and processing time. To experimentally evaluate the performance of cooperative perception schemes is time-consuming and costly due to the expensive hardware it involves. To the best of our knowledge there is to date no open- source simulation framework that allows to transfer realistic sensor data between multiple simulated vehicles via a V2X network. In this work-in-progress paper, we address this issue by proposing an extension of the well-known CARLA open- source simulator for automated driving research. We implement a basic communication channel on top of the existing client-server architecture of CARLA and show how sensor information can be exchanged. Transferring realistic sensor information between multiple vehicles opens up a wide range of experiments to test and evaluate novel approaches to collaborative driving in simulation.
Researchers
http://hdl.handle.net/10993/48765

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