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A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles

Anjum Mohd Aslam, Aditya Bhardwaj Orcid Logo, Cheng Cheng Orcid Logo

IET Intelligent Transport Systems, Volume: 20, Issue: 1

Swansea University Author: Cheng Cheng Orcid Logo

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DOI (Published version): 10.1049/itr2.70190

Abstract

Connected and autonomous vehicles (CAVs) are critical to the advancement of intelligent transportation systems (ITS) and the realisation of completely autonomous driving. CAVs' sophisticated technologies enable the seamless transmission of essential information in real-time, promoting greater r...

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Published in: IET Intelligent Transport Systems
ISSN: 1751-956X 1751-9578
Published: Institution of Engineering and Technology (IET) 2026
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URI: https://cronfa.swan.ac.uk/Record/cronfa71608
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spelling 2026-04-14T15:59:23.7488307 v2 71608 2026-03-11 A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles 11ddf61c123b99e59b00fa1479367582 0000-0003-0371-9646 Cheng Cheng Cheng Cheng true false 2026-03-11 MACS Connected and autonomous vehicles (CAVs) are critical to the advancement of intelligent transportation systems (ITS) and the realisation of completely autonomous driving. CAVs' sophisticated technologies enable the seamless transmission of essential information in real-time, promoting greater road safety and efficient transportation networks. However, due to the complex and time-sensitive nature of information transmission between vehicles and infrastructure units, developing reliable and efficient wireless communication networks for CAVs poses major challenges. It is critical to effectively deploy connected and autonomous driving technologies to ensure seamless and reliable communication between CAVs and the surrounding infrastructure. In this paper, we designed an effective mathematical approach for evaluating the performance of vehicular communication networks based on stochastic geometry principles. The architecture of a dynamic CAVs scenario is illustrated by modelling the spatial layout of pathways with the Poisson line process (PLP) and the positioning of CAVs and infrastructure units on each path with the Poisson point process (PPP). By deriving expressions for key metrics such as signal-to-interference-plus-noise ratio (SINR), spatial coverage, and link success probability under Nakagami-m fading, the framework offers deep insights into the reliability and efficiency of vehicle-to-everything (V2X) communications. The simulation results give valuable insights for designing and implementing CAVS, with stochastic geometry leading to improved overall CAVs performance. Journal Article IET Intelligent Transport Systems 20 1 Institution of Engineering and Technology (IET) 1751-956X 1751-9578 automated driving &amp; intelligent vehicles; connected and autonomous vehicles; spatial coverage; stochastic geometry; V2X communications; vehicle automation and connectivity; interference 1 12 2026 2026-12-01 10.1049/itr2.70190 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University SU Library paid the OA fee (TA Institutional Deal) UKRI EPSRC Grant funded Doctoral Training Centre at Swansea University; UKRI EPSRC Grant EP/W020408/1 2026-04-14T15:59:23.7488307 2026-03-11T09:43:10.3747781 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Anjum Mohd Aslam 1 Aditya Bhardwaj 0000-0003-2488-0092 2 Cheng Cheng 0000-0003-0371-9646 3 71608__36508__c2ff4dcbac694a009210d18b750d3721.pdf 71608.VoR.pdf 2026-04-14T15:56:51.1121006 Output 2573426 application/pdf Version of Record true © 2026 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
spellingShingle A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
Cheng Cheng
title_short A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
title_full A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
title_fullStr A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
title_full_unstemmed A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
title_sort A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
author_id_str_mv 11ddf61c123b99e59b00fa1479367582
author_id_fullname_str_mv 11ddf61c123b99e59b00fa1479367582_***_Cheng Cheng
author Cheng Cheng
author2 Anjum Mohd Aslam
Aditya Bhardwaj
Cheng Cheng
format Journal article
container_title IET Intelligent Transport Systems
container_volume 20
container_issue 1
publishDate 2026
institution Swansea University
issn 1751-956X
1751-9578
doi_str_mv 10.1049/itr2.70190
publisher Institution of Engineering and Technology (IET)
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description Connected and autonomous vehicles (CAVs) are critical to the advancement of intelligent transportation systems (ITS) and the realisation of completely autonomous driving. CAVs' sophisticated technologies enable the seamless transmission of essential information in real-time, promoting greater road safety and efficient transportation networks. However, due to the complex and time-sensitive nature of information transmission between vehicles and infrastructure units, developing reliable and efficient wireless communication networks for CAVs poses major challenges. It is critical to effectively deploy connected and autonomous driving technologies to ensure seamless and reliable communication between CAVs and the surrounding infrastructure. In this paper, we designed an effective mathematical approach for evaluating the performance of vehicular communication networks based on stochastic geometry principles. The architecture of a dynamic CAVs scenario is illustrated by modelling the spatial layout of pathways with the Poisson line process (PLP) and the positioning of CAVs and infrastructure units on each path with the Poisson point process (PPP). By deriving expressions for key metrics such as signal-to-interference-plus-noise ratio (SINR), spatial coverage, and link success probability under Nakagami-m fading, the framework offers deep insights into the reliability and efficiency of vehicle-to-everything (V2X) communications. The simulation results give valuable insights for designing and implementing CAVS, with stochastic geometry leading to improved overall CAVs performance.
published_date 2026-12-01T07:39:53Z
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score 11.102298

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