A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks

Bottlenecks reduce both traffic safety and efficiency, resulting in congestion and collisions. The introduction of connected autonomous vehicles (CAVs) has had a significant impact on road networks and can improve traffic efficiency at bottlenecks. This paper proposes a microscopic traffic model to...

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Main Authors: Faryal Ali, Zawar Hussain Khan, Thomas Aaron Gulliver, Khurram Shehzad Khattak, Ahmed B. Altamimi
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/3/1214
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author Faryal Ali
Zawar Hussain Khan
Thomas Aaron Gulliver
Khurram Shehzad Khattak
Ahmed B. Altamimi
author_facet Faryal Ali
Zawar Hussain Khan
Thomas Aaron Gulliver
Khurram Shehzad Khattak
Ahmed B. Altamimi
author_sort Faryal Ali
collection DOAJ
description Bottlenecks reduce both traffic safety and efficiency, resulting in congestion and collisions. The introduction of connected autonomous vehicles (CAVs) has had a significant impact on road networks and can improve traffic efficiency at bottlenecks. This paper proposes a microscopic traffic model to investigate CAV behavior at bottlenecks and examine the effect of cyberattacks. The model is developed using data collected from a roadside sensor node. It is implemented in MATLAB using the Euler scheme to simulate a platoon of vehicles on a circular road of length <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn></mrow></semantics></math></inline-formula> km. The performance is compared with the intelligent driver (ID) model. The results obtained indicate that the road capacity with the proposed model is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1.4</mn></mrow></semantics></math></inline-formula> times higher than with the ID model. Further, the proposed model results in nearly constant speeds with small variations, which is realistic. Conversely, the ID model produces large speed variations that are unrealistic. In addition, the proposed model results in less acceleration and deceleration, which leads to lower vehicle emissions and pollution. The efficiency is better than with the ID model due to CAV communication and coordination, so queues dissipate faster. The traffic flow with the proposed model increases as the density decreases, which is consistent with traffic dynamics. It is also shown that the proposed model can characterize CAV behavior under cyberattacks that cause disruptions in the data. Thus, it can be employed for traffic control and forecasting when bottleneck conditions exist and there is malicious behavior.
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spelling doaj-art-6c76f22fe93b4c209d7aa3fe6fe7d8fd2025-08-20T02:48:09ZengMDPI AGApplied Sciences2076-34172025-01-01153121410.3390/app15031214A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of CyberattacksFaryal Ali0Zawar Hussain Khan1Thomas Aaron Gulliver2Khurram Shehzad Khattak3Ahmed B. Altamimi4Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, CanadaCollege of Computer Science and Engineering, University of Ha’il, Ha’il 55476, Saudi ArabiaDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 2Y2, CanadaDepartment of Computer System Engineering, University of Engineering and Technology, Peshawar 25000, PakistanCollege of Computer Science and Engineering, University of Ha’il, Ha’il 55476, Saudi ArabiaBottlenecks reduce both traffic safety and efficiency, resulting in congestion and collisions. The introduction of connected autonomous vehicles (CAVs) has had a significant impact on road networks and can improve traffic efficiency at bottlenecks. This paper proposes a microscopic traffic model to investigate CAV behavior at bottlenecks and examine the effect of cyberattacks. The model is developed using data collected from a roadside sensor node. It is implemented in MATLAB using the Euler scheme to simulate a platoon of vehicles on a circular road of length <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn></mrow></semantics></math></inline-formula> km. The performance is compared with the intelligent driver (ID) model. The results obtained indicate that the road capacity with the proposed model is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1.4</mn></mrow></semantics></math></inline-formula> times higher than with the ID model. Further, the proposed model results in nearly constant speeds with small variations, which is realistic. Conversely, the ID model produces large speed variations that are unrealistic. In addition, the proposed model results in less acceleration and deceleration, which leads to lower vehicle emissions and pollution. The efficiency is better than with the ID model due to CAV communication and coordination, so queues dissipate faster. The traffic flow with the proposed model increases as the density decreases, which is consistent with traffic dynamics. It is also shown that the proposed model can characterize CAV behavior under cyberattacks that cause disruptions in the data. Thus, it can be employed for traffic control and forecasting when bottleneck conditions exist and there is malicious behavior.https://www.mdpi.com/2076-3417/15/3/1214bottleneckconnected autonomous vehicle (CAV)traffic flowcyberattackintelligent driver modelmicroscopic traffic model
spellingShingle Faryal Ali
Zawar Hussain Khan
Thomas Aaron Gulliver
Khurram Shehzad Khattak
Ahmed B. Altamimi
A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks
Applied Sciences
bottleneck
connected autonomous vehicle (CAV)
traffic flow
cyberattack
intelligent driver model
microscopic traffic model
title A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks
title_full A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks
title_fullStr A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks
title_full_unstemmed A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks
title_short A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks
title_sort microscopic traffic model to investigate the effect of connected autonomous vehicles at bottlenecks and the impact of cyberattacks
topic bottleneck
connected autonomous vehicle (CAV)
traffic flow
cyberattack
intelligent driver model
microscopic traffic model
url https://www.mdpi.com/2076-3417/15/3/1214
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