Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments
Vehicles with driving automation are increasingly being developed for deployment across the world. However, the onboard sensing and perception capabilities of such automated or autonomous vehicles (AV) may not be sufficient to ensure safety under all scenarios and contexts. Infrastructure-augmented...
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sg-ntu-dr.10356-1528782023-07-18T15:37:06Z Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments Vijay, Roshan Cherian, Jim Riah, Rachid de Boer, Niels Choudhury, Apratim 2021 IEEE International Conference on Intelligent Transportation Systems (ITSC) Siemens Mobility Pte. Ltd. Centre of Excellence for Testing & Research of Autonomous Vehicles NTU (CETRAN) Energy Research Institute @ NTU (ERI@N) Engineering::Computer science and engineering::Computer applications::Computers in other systems V2X Sensor Placement Optimization Autonomous Vehicles Infrastructure Sensors Vehicles with driving automation are increasingly being developed for deployment across the world. However, the onboard sensing and perception capabilities of such automated or autonomous vehicles (AV) may not be sufficient to ensure safety under all scenarios and contexts. Infrastructure-augmented environment perception using roadside infrastructure sensors can be considered as an effective solution, at least for selected regions of interest such as urban road intersections or curved roads that present occlusions to the AV. However, they incur significant costs for procurement, installation and maintenance. Therefore these sensors must be placed strategically and optimally to yield maximum benefits in terms of the overall safety of road users. In this paper, we propose a novel methodology towards obtaining an optimal placement of V2X (Vehicle-to-everything) infrastructure sensors, which is particularly attractive to urban AV deployments, with various considerations including costs, coverage and redundancy. We combine the latest advances made in raycasting and linear optimization literature to deliver a tool for urban city planners, traffic analysts and AV deployment operators. Through experimental evaluation in representative environments, we demonstrate the benefits and practicality of our approach. Published version This work is supported by Siemens Mobility Pte. Ltd. 2023-07-17T06:53:05Z 2023-07-17T06:53:05Z 2021 Conference Paper Vijay, R., Cherian, J., Riah, R., de Boer, N. & Choudhury, A. (2021). Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments. 2021 IEEE International Conference on Intelligent Transportation Systems (ITSC), 2589-2595. https://dx.doi.org/10.1109/ITSC48978.2021.9564822 978-1-7281-9142-3 https://hdl.handle.net/10356/152878 10.1109/ITSC48978.2021.9564822 2110.01251 2589 2595 en © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ITSC48978.2021.9564822. application/pdf |
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Engineering::Computer science and engineering::Computer applications::Computers in other systems V2X Sensor Placement Optimization Autonomous Vehicles Infrastructure Sensors Vijay, Roshan Cherian, Jim Riah, Rachid de Boer, Niels Choudhury, Apratim Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
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Vehicles with driving automation are increasingly being developed for deployment across the world. However, the onboard sensing and perception capabilities of such automated or autonomous vehicles (AV) may not be sufficient to ensure safety under all scenarios and contexts. Infrastructure-augmented environment perception using roadside infrastructure sensors can be considered as an effective solution, at least for selected regions of interest such as urban road intersections or curved roads that present occlusions to the AV. However, they incur significant costs for procurement, installation and maintenance. Therefore these sensors must be placed strategically and optimally to yield maximum benefits in terms of the overall safety of road users. In this paper, we propose a novel methodology towards obtaining an optimal placement of V2X (Vehicle-to-everything) infrastructure sensors, which is particularly attractive to urban AV deployments, with various considerations including costs, coverage and redundancy. We combine the latest advances made in raycasting and linear optimization literature to deliver a tool for urban city planners, traffic analysts and AV deployment operators. Through experimental evaluation in representative environments, we demonstrate the benefits and practicality of our approach. |
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2021 IEEE International Conference on Intelligent Transportation Systems (ITSC) |
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2021 IEEE International Conference on Intelligent Transportation Systems (ITSC) Vijay, Roshan Cherian, Jim Riah, Rachid de Boer, Niels Choudhury, Apratim |
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Conference or Workshop Item |
author |
Vijay, Roshan Cherian, Jim Riah, Rachid de Boer, Niels Choudhury, Apratim |
author_sort |
Vijay, Roshan |
title |
Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
title_short |
Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
title_full |
Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
title_fullStr |
Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
title_full_unstemmed |
Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
title_sort |
optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments |
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2023 |
url |
https://hdl.handle.net/10356/152878 |
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1773551239205748736 |