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Research Article | Open Access

Micro-simulation insights into the safety and operational benefits of autonomous vehicles

Nalin Kumar Sekar1Vinayak Malaghan2Digvijay S. Pawar3( )
School of Mechanical Engineering, Vellore Institute of Technology, Vellore 632014, India
Department of Civil, Structural, and Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin 2, Ireland
Department of Civil Engineering, Indian Institute of Technology Hyderabad, Kandi 502285, India
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Abstract

Several past studies showed that Autonomous Vehicles (AVs) can reduce crash risk, stop-and-go traffic, and travel time. To analyze the safety benefits of AVs, most of the researchers proposed algorithms and simulation-based techniques. However, these studies have not assessed the safety benefits of AVs for different vehicle types under heterogeneous conditions. With this opportunity, this study focuses on the benefits of AVs in terms of safety for different penetration rates under heterogeneous conditions. This study considered three driving logics during peak hour conditions to assess the performance of AVs in terms of safety. In VISSIM, default driving behavior models for AVs were adopted to consider cautious and all-knowing driving logic and the third driving logic (Atkins) was modeled in VISSIM using parameters adopted from the previous studies. To this end, using VISSIM, the travel time output results were obtained. Also, using Surrogate Safety Assessment Model (SSAM), conflicts were extracted from output trajectory files (VISSIM). The results suggest that “cautious driving logic” reduced travel time and crash risk significantly when compared to the other two driving logics during peak hour conditions. Furthermore, the statistical analysis clearly demonstrated that “cautious driving logic” differs significantly from the other two driving logics. When Market Penetration Rates (MPR) were 50% or greater, the “cautious driving logic” significantly outperforms the other two driving logics. The results highlight that adopting “cautious driving logic” at an expressway may significantly increase safety at higher AV penetration rates (above 50%).

References

[1]

Abdel-Aty, M., Wu, Y., Saad, M., Rahman, M. S., 2020. Safety and operational impact of connected vehicles’ lane configuration on freeway facilities with managed lanes. Accid Anal Prev, 144, 105616.

[2]
Almobayedh, H. B., 2019. Simulation of the impact of connected and automated vehicles at a signalized intersection. Ph.D. Dissertation. Dayton, Ohio, USA: University of Dayton.
[3]

Arvin, R., Khattak, A. J., Kamrani, M., Rio-Torres, J., 2021. Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections. J Intell Transp Syst, 25, 170–187.

[4]
Atkins, W. S., 2016. Research on the impacts of connected and autonomous vehicles (CAVs) on traffic flow. Stage 2: Traffic modelling and analysis technical report. SO13994/3.
[5]

Bansal, P., Kockelman, K. M., 2017. Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies. Transp Res A, 95, 49–63.

[6]
Curto, S., Severino, A., Trubia, S., Arena, F., Puleo, L., 2021. The effects of autonomous vehicles on safety. In: AIP Conference Proceedings, 110013.
[7]

Deluka Tibljaš, A., Giuffrè, T., Surdonja, S., Trubia, S., 2018. Introduction of autonomous vehicles: Round abouts design and safety performance evaluation. Sustainability, 10, 1060.

[8]

Fagnant, D. J., Kockelman, K., 2015. Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Transp Res A, 77, 167–181.

[9]
FMVSS, N., 2016. Vehicle-To-Vehicle Communication Technology For Light Vehicles. FMVSS No. 150. https://www.iihs.org/media/716de1d2-7e8c-48bf-947e-7cfd20bd1259/w5q4PA/RegulatoryComments/comment_2017-04-10.pdf
[10]
Fyfe, M., Sayed, T., 2017. Safety evaluation of connected vehicles for a cumulative travel time adaptive signal control microsimulation using the surrogate safety assessment model. In: Transportation Research Board 96th Annual Meeting, 17, 01651.
[11]

Genders, W., Razavi, S. N., 2016. Impact of connected vehicle on work zone network safety through dynamic route guidance. J Comput Civ Eng, 30, 04015020.

[12]
Gettman, D., Pu, L., Sayed, T., Shelby, S. G., 2008. Surrogate safety assessment model and validation: Final report. FHWA-HRT-08-051.
[13]

Ghosh, T., Roy, S. K., Gangopadhyay, S., 2020. Assessment of multilane highway capacity through simulation process by considering the effect of behavior of driver of a vehicle. J Inst Eng India Ser A, 101, 589–596.

[14]
Google Maps, 2022. Selected stretch on outer ring road. Sourced from Google Maps. URL: https://www.google.com/maps/@17.4734522,78.3630423,11.72z?entry=ttu
[15]

Guériau, M., Cugurullo, F., Acheampong, R. A., Dusparic, I., 2020. Shared autonomous mobility on demand: A learning-based approach and its performance in the presence of traffic congestion. IEEE Intell. Transp. Syst. Mag, 12, 208-218.

[16]

Hayes, B., 2011. Leave the driving to it. Amer Scientist, 99, 362.

[17]

Hoogendoorn, R., van Arerm, B., Hoogendoom, S., 2014. Automated driving, traffic flow efficiency, and human factors. Transportation Research Record, 2422, 113–120.

[18]
Hyderabad Metropolitan Development Authority (HMDA), 2012. https://www.hmda.gov.in
[19]
Jin, Q., Wu, G., Boriboonsomsin, K., Barth, M., 2014. Platoon-based multi-agent intersection management for connected vehicle. In: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 1462–1467.
[20]

Khashayarfard, M., Nassiri, H., 2021. Studying the simultaneous effect of autonomous vehicles and distracted driving on safety at unsignalized intersections. J Adv Transp, 2021, 1-16.

[21]
Leela, K. S. S., Krishna, P. V., Chandram, M., 2018. Outer ring road traffic analysis and prediction. In: National Conference On Trends In Science, Engineering & Technology by Matrusri Engineering College & IJCRT, 322–326.
[22]

Letter, C., Elefteriadou, L., 2017. Efficient control of fully automated connected vehicles at freeway merge segments. Transp Res C, 80, 190–205.

[23]

Li, Z., Chitturi, M. V., Zheng, D., Bill, A. R., Noyce, D. A., 2013. Modeling reservation-based autonomous intersection control in VISSIM. Transportation Research Record, 2381, 81–90.

[24]

Malaghan, V., Pawar, D. S., 2022. A short-term naturalistic driving study on predicting comfort thresholds for horizontal curves on two-lane rural highways. J Transp Eng A, 148, 04022045.

[25]
Ministry of Road Transport and Highways (MORTH), 2020. Road accidents in India 2020. https://morth.nic.in/road-accident-in-india
[26]

Mirheli, A., Hajibabai, L., Hajbabaie, A., 2018. Development of a signal-head-free intersection control logic in a fully connected and autonomous vehicle environment. Transp Res C, 92, 412–425.

[27]
Mohebifard, R., Hajbabaie, A., 2020. Effects of automated vehicles on traffic operations at round abouts. In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 1–6.
[28]

Morando, M. M., Tian, Q., Truong, L. T., Vu, H. L., 2018. Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures. J Adv Transp, 2018, 1–11.

[29]

Mousavi, S. M., Osman, O. A., Lord, D., Dixon, K. K., Dadashova, B., 2021. Investigating the safety and operational benefits of mixed traffic environments with different automated vehicle market penetration rates in the proximity of a driveway on an urban arterial. Accid Anal Prev, 152, 105982.

[30]

Papadoulis, A., Quddus, M., Imprialou, M., 2019. Evaluating the safety impact of connected and autonomous vehicles on motorways. Accid Anal Prev, 124, 12–22.

[31]

Park, H., Smith, B. L., 2012. Investigating benefits of IntelliDrive in freeway operations: Lane changing advisory case study. J Transp Eng, 138, 1113–1122.

[32]

Rahman, M. H., Abdel-Aty, M., Wu, Y., 2021. A multi-vehicle communication system to assess the safety and mobility of connected and automated vehicles. Transp Res C, 124, 102887.

[33]

Rahman, M. S., Abdel-Aty, M., Lee, J., Rahman, M. H., 2019. Safety benefits of arterials’ crash risk under connected and automated vehicles. Transp Res C, 100, 354–371.

[34]

Severino, A., Pappalardo, G., Curto, S., Trubia, S., Olayode, I. O., 2021. Safety evaluation of flower round about considering autonomous vehicles operation. Sustainability, 13, 10120.

[35]

Silberg, G., Wallace, R., Matuszak, G., Plessers, J., Brower, C., Subramanian, D., 2012. Self-driving cars: The next revolution. White paper, KPMG LLP & Center of Automotive Research, 9(2), 132–146.

[36]
Singh, S., 2015. Critical reasons for crashes investigated in the national motor vehicle crash causation survey. No. DOT HS 812 115.
[37]

Sinha, A., Chand, S., Wijayaratna, K. P., Virdi, N., Dixit, V., 2020. Comprehensive safety assessment in mixed fleets with connected and automated vehicles: A crash severity and rate evaluation of conventional vehicles. Accid Anal Prev, 142, 105567.

[38]
Sukennik, P., PTV Group, 2018. D. 25 Micro-Simulation Guide for Automated Vehicles.
[39]

Tajalli, M., Hajbabaie, A., 2018. Distributed optimization and coordination algorithms for dynamic speed optimization of connected and autonomous vehicles in urban street networks. Transp Res C, 95, 497–515.

[40]

Virdi, N., Grzybowska, H., Waller, S. T., Dixit, V., 2019. A safety assessment of mixed fleets with connected and autonomous vehicles using the surrogate safety assessment module. Accid Anal Prev, 131, 95–111.

[41]
VISSIM, 2018. PTV VISSIM 10 User Manual. https://usermanual.wiki/Document/Vissim20102020Manual.1098038624.pdf
[42]

Wan, N., Vahidi, A., Luckow, A., 2016. Optimal speed advisory for connected vehicles in arterial roads and the impact on mixed traffic. Transp Res C, 69, 548–563.

[43]
World Health Organization (WHO), 2018. Global status report on road safety 2018. Geneva: World Health Organization, 2018.
[44]

Yue, L., Abdel-Aty, M., Wu, Y., Wang, L., 2018. Assessment of the safety benefits of vehicles’ advanced driver assistance, connectivity and low level automation systems. Accid Anal Prev, 117, 55–64.

[45]

Zhang, H., Hou, N., Zhang, J., Li, X., Huang, Y., 2021. Evaluating the safety impact of connected and autonomous vehicles with lane management on freeway crash hotspots using the surrogate safety assessment model. J Adv Transp, 2021, 1–14.

Journal of Intelligent and Connected Vehicles
Pages 202-210
Cite this article:
Sekar NK, Malaghan V, Pawar DS. Micro-simulation insights into the safety and operational benefits of autonomous vehicles. Journal of Intelligent and Connected Vehicles, 2023, 6(4): 202-210. https://doi.org/10.26599/JICV.2023.9210007

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Received: 14 February 2023
Revised: 12 April 2023
Accepted: 06 May 2023
Published: 30 December 2023
© The author(s) 2023.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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