As smart connected vehicles become increasingly common and pave the way for the autonomous vehicles of the future, their ability to provide enhanced safety and assistance services has improved. One such service is the emergency transport of drivers in medical distress: as a positive solution of the distress is typically more likely after timely response, an autonomous vehicle could cut on emergency response times, and thus play a key role in saving the life of its driver. In this paper, we show how such an autonomous emergency transport service can be run from a wireless cellular network, and discuss the importance of having a human in the loop in order to expedite driving. We present a Monte-Carlo-based driver assessment system that the network can use when selecting the most suitable candidate to wirelessly tow an autonomous vehicle with an incapacitated driver. We show that this mechanism results in a selection policy that ensures better cohesion between the vehicles, thereby significantly improving service reliability by reducing the chances of disruptions by intervening traffic.

Copy-CAV: V2X-enabled wireless towing for emergency transport / C. Ayimba, V. Cislaghi, C. Quadri, P. Casari, V. Mancuso. - In: COMPUTER COMMUNICATIONS. - ISSN 0140-3664. - 205:(2023 May 01), pp. 87-96. [10.1016/j.comcom.2023.04.009]

Copy-CAV: V2X-enabled wireless towing for emergency transport

C. Quadri;
2023

Abstract

As smart connected vehicles become increasingly common and pave the way for the autonomous vehicles of the future, their ability to provide enhanced safety and assistance services has improved. One such service is the emergency transport of drivers in medical distress: as a positive solution of the distress is typically more likely after timely response, an autonomous vehicle could cut on emergency response times, and thus play a key role in saving the life of its driver. In this paper, we show how such an autonomous emergency transport service can be run from a wireless cellular network, and discuss the importance of having a human in the loop in order to expedite driving. We present a Monte-Carlo-based driver assessment system that the network can use when selecting the most suitable candidate to wirelessly tow an autonomous vehicle with an incapacitated driver. We show that this mechanism results in a selection policy that ensures better cohesion between the vehicles, thereby significantly improving service reliability by reducing the chances of disruptions by intervening traffic.
Connected autonomous vehicles; Emergency transport; MEC; Reinforcement learning; V2X
Settore INF/01 - Informatica
1-mag-2023
18-apr-2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/967660
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