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A Stochastic Geometry Framework for Enhancing Communication Efficiency and Road Safety in Connected and Autonomous Vehicles
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Cheng Cheng
IET Intelligent Transport Systems, Volume: 20, Issue: 1
Swansea University Author:
Cheng Cheng
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© 2026 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License.
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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...
| Published in: | IET Intelligent Transport Systems |
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| ISSN: | 1751-956X 1751-9578 |
| Published: |
Institution of Engineering and Technology (IET)
2026
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71608 |
| 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 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. |
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| Keywords: |
automated driving & intelligent vehicles; connected and autonomous vehicles; spatial coverage; stochastic geometry; V2X communications; vehicle automation and connectivity; interference |
| College: |
Faculty of Science and Engineering |
| Funders: |
UKRI EPSRC Grant funded Doctoral Training Centre at Swansea University; UKRI EPSRC Grant EP/W020408/1 |
| Issue: |
1 |