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Development of Performance Measurement Models for Two-Lane Roads under Vehicular Platooning Using Conjugate Bayesian Analysis

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  • Hossein Samadi

    (Faculty of Civil Engineering, Shahrood University of Technology, Shahrood 36199-95161, Iran)

  • Iman Aghayan

    (Faculty of Civil Engineering, Shahrood University of Technology, Shahrood 36199-95161, Iran
    Institute for Physical Infrastructure and Transportation (IPIT), University of Wisconsin–Milwaukee, Milwaukee, WI 53201, USA)

  • Khaled Shaaban

    (Department of Engineering, Utah Valley University, Orem, UT 84058, USA)

  • Farhad Hadadi

    (Faculty of Civil Engineering, Shahrood University of Technology, Shahrood 36199-95161, Iran)

Abstract

Vehicular platooning is one of the most challenging issues affecting the level of service (LOS) of two-lane roads. This phenomenon has been involved with variables governing performance measures. Thus, to improve the quality of these roads and predict a comprehensive model for future plans under this phenomenon, the present study aimed to evaluate the effect of vehicular platooning variables on performance measures and then identify the critical headways of vehicular platooning associated with the vehicle-gap-acceptance behavior. Multiple linear regression (MLR) and Bayesian linear regression (BLR) models were used to develop performance measurement models that are based on conjugate Bayesian analysis. The vehicular platooning was formed in the threshold of a time headway of 2.4 s. According to a comparative evaluation of the developed models, the best predictive model was found between the traffic flow and the number of followers per capacity (NFPC). In addition, the BLR model showed a higher accuracy rate in predicting NFPC compared with the MLR model due to low errors and high prediction performance. Thus, NFPC was introduced as a surrogate performance measure, which had a premier capability to predict the LOS for unsaturated and saturated traffic conditions compared with the two performance measures from the Highway Capacity Manual (2010), including percent time spent following and average travel speed.

Suggested Citation

  • Hossein Samadi & Iman Aghayan & Khaled Shaaban & Farhad Hadadi, 2023. "Development of Performance Measurement Models for Two-Lane Roads under Vehicular Platooning Using Conjugate Bayesian Analysis," Sustainability, MDPI, vol. 15(5), pages 1-26, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4037-:d:1077409
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    References listed on IDEAS

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    1. Shiomi, Yasuhiro & Yoshii, Toshio & Kitamura, Ryuichi, 2011. "Platoon-based traffic flow model for estimating breakdown probability at single-lane expressway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1314-1330.
    2. Al-Kaisy, Ahmed & Jafari, Amirhossein & Washburn, Scott & Lutinnen, Tapio & Dowling, Richard, 2018. "Performance measures on two-lane highways: Survey of practice," Research in Transportation Economics, Elsevier, vol. 71(C), pages 61-67.
    3. Rezaei, Danial & Aghayan, Iman & Hadadi, Farhad, 2021. "Studying perturbations and wave propagations by lane closures on traffic characteristics based on a dynamic approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    4. Zhu, Liling & Tang, Yandong & Yang, Da, 2021. "Cellular automata-based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    5. Bhoopalam, Anirudh Kishore & Agatz, Niels & Zuidwijk, Rob, 2018. "Planning of truck platoons: A literature review and directions for future research," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 212-228.
    6. Raffaele Mauro & Andrea Pompigna, 2022. "A Statistically Based Model for the Characterization of Vehicle Interactions and Vehicle Platoons Formation on Two-Lane Roads," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    7. Harim Jeong & Sangmin Park & Sungho Park & Hyonbae Cho & Ilsoo Yun, 2020. "Study on the Selection of Sections Applicable to Truck Platooning in the Expressway Network," Sustainability, MDPI, vol. 12(19), pages 1-13, September.
    8. Torkashvand, Mojtaba Bahrami & Aghayan, Iman & Qin, Xiao & Hadadi, Farhad, 2022. "An extended dynamic probabilistic risk approach based on a surrogate safety measure for rear-end collisions on two-lane roads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    9. Ciro Caliendo & Maurizio Guida & Fabio Postiglione & Isidoro Russo, 2022. "A Bayesian bivariate hierarchical model with correlated parameters for the analysis of road crashes in Italian tunnels," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 109-131, March.
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