Comparative conflict analysis of human-driven and autonomous vehicles at signalized intersections

Year 2024, Volume: 13 Issue: 4, 180 - 190, 31.12.2024

Mustafa Albdairi , Ali Almusawi , Syed Shah Sultan Mohiuddin Qadri

https://doi.org/10.18245/ijaet.1523772

Abstract

Integrating autonomous vehicles (AVs) into urban traffic systems presents both opportunities and challenges, especially at signalized intersections. This study offers a comparative conflict analysis of human-driven vehicles and AVs at a busy four-legged signalized intersection in Balgat, Ankara, Turkey. Using PTV VISSIM for detailed traffic simulation, the research assesses the effects of various AV driving styles - cautious, normal, aggressive, and a mix of all three - at different penetration rates (25% to 100%), alongside standard human-driven vehicle scenarios. The Surrogate Safety Assessment Model (SSAM) is employed to analyze safety implications both before and after intersection design calibration. The findings demonstrate notable differences in conflict points between human-driven and AV scenarios. Before calibration, cautious AV behaviors result in higher conflict points due to increased queuing, while aggressive behaviors reduce conflicts through more efficient traffic flow. Human-driven vehicles exhibit varied conflict levels based on driver behavior. After calibration, significant improvements are observed across all scenarios, with aggressive AVs achieving the greatest reduction in conflict points. This study highlights the potential for AVs to improve intersection safety and efficiency when appropriate design calibration measures are implemented.

Keywords

Autonomous Vehicles, Signalized Intersections, Traffic Simulation, Conflict Analysis, Intersection Design Calibration

References

• A. Karbasi and S. O’Hern, “Investigating the impact of connected and automated vehicles on signalized and unsignalized intersections safety in mixed traffic,” Future Transportation, vol. 2, no. 1, pp. 24-40, 2022.
• Albdairi, Mustafa, Ali Almusawi, and Syed Shah Sultan Mohiuddin Qadri, “Impact of Autonomous Vehicle Driving Behaviors on Signalized Intersection Performance: A Review,” Usak University Journal of Engineering Sciences, vol. 7, no. 1, pp. 14-26, June 2024.
• W. Do, N. Saunier, and L. Miranda-Moreno, “Safety benefits of automated speed advisory systems at signalized intersections,” Transportation Research Record, vol. 2677, no. 3, pp. 551-564, 2023.
• A. I. Mahbub, V.-A. Le, and A. A. Malikopoulos, “Safety-Aware and Data-Driven Predictive Control for Connected Automated Vehicles at a Mixed Traffic Signalized Intersection,” IFAC-Papers online, vol. 55, no. 24, pp. 51-56, 2022.
• G. Bathla et al., “Autonomous vehicles and intelligent automation: Applications, challenges, and opportunities,” Mobile Information Systems, vol. 2022, no. 1, p. 7632892, 2022.
• M. Khayatian et al., “A survey on intersection management of connected autonomous vehicles,” ACM Transactions on Cyber-Physical Systems, vol. 4, no. 4, pp. 1-27, 2020.
• E. Namazi, J. Li, and C. Lu, “Intelligent intersection management systems considering autonomous vehicles: A systematic literature review,” IEEE Access, vol. 7, pp. 91946-91965, 2019.
• E. F. Ozioko, J. Kunkel, and F. Stahl, “Road intersection coordination scheme for mixed traffic (human-driven and driverless vehicles): A systematic review,” in Science and Information Conference, Springer, pp. 67-94, 2022.
• S. K. Jayaraman et al., “Pedestrian trust in automated vehicles: Role of traffic signal and AV driving behavior,” Frontiers in Robotics and AI, vol. 6, p. 117, 2019.
• I. R. Khan, Interaction Between Autonomous Vehicles and Other Road Users—A Simulation Study. The University of Alabama in Huntsville, 2023.
• M. Martínez‐Díaz, F. Soriguera, and I. Pérez, “Autonomous driving: a bird's eye view,” IET Intelligent Transport Systems, vol. 13, no. 4, pp. 563-579, 2019.
• J. Wang, Y. V. Pant, L. Zhao, M. Antkiewicz, and K. Czarnecki, “Enhancing safety in mixed traffic: Learning-based modeling and efficient control of autonomous and human-driven vehicles,” IEEE Transactions on Intelligent Transportation Systems, 2024.
• H. Sadid and C. Antoniou, "A simulation-based impact assessment of autonomous vehicles in urban networks," IET Intelligent Transport Systems, 2024. doi: 10.1049/itr2.12537.
• S. Kim, M.-J. Cho, and Y. Lee, “Exploration of traffic accident-based pilot zones for autonomous vehicle safety validation,” Electronics, 2024. doi: 10.3390/electronics13173390.
• Federal Highway Administration, “Surrogate Safety Assessment Model (SSAM) User Manual,” U.S. Department of Transportation, Publication No. FHWA-HRT-08-050, 2008. Available at: https://highways.dot.gov/sites/fhwa.dot.gov/files/FHWA-HRT-08-050.pdf.
• A. Osman, “Evaluation of the Impact of Automated Driven Vehicles on Traffic Performance at Four-leg Signalized Intersections,” Linköping University, Department of Science and Technology, Communications and Transport Systems, Linköping University, Faculty of Science & Engineering, 2023.
• Almusawi, A., & Albdairi, M. “The Impact of Increasing Traffic Volume on Autonomous Vehicles in Roundabout,” Akıllı Ulaşım Sistemleri Ve Uygulamaları Dergisi, 2024.
• A. Almusawi, M. Albdairi, and S.S.S.M. Qadri, "Integrating Autonomous Vehicles (AVs) into Urban Traffic: Simulating Driving and Signal Control," Applied Sciences, vol. 14, no. 19, pp. 8851, Oct. 2024. doi: https://doi.org/10.3390/app14198851.