IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12946-d938201.html
   My bibliography  Save this article

Estimation of Appropriate Acceleration Lane Length for Safe and Efficient Truck Platooning Operation on Freeway Merge Areas

Author

Listed:
  • Tanvir Uddin Chowdhury

    (Department of Civil Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada)

  • Peter Y. Park

    (Department of Civil Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada)

  • Kevin Gingerich

    (Department of Civil Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada)

Abstract

The length of an acceleration lane is one of the dominant freeway geometric design parameters. This length requires new analyses to anticipate the needs of heavy commercial vehicle (HCV) platooning. We evaluated the safety and operational impact of HCV platooning on acceleration lane length for a freeway ramp in Ontario, Canada. This study modified the 2018 AASHTO’s acceleration lane length estimation analytical model. Furthermore, this study used a VISSIM micro-simulation model and surrogated safety assessment model (SSAM) to examine the safety and operational impact on the real-world circumstances of HCV platooning at 0.6 s and 1.2 s headways and different market penetration rates of 0%, 5%, and 10%. The results suggest a minimum acceleration lane length of 600 m for platooned HCVs, which is inadequate compared to American and Canadian design guidelines. An extended acceleration lane length (600 m) will improve safety by reducing conflict by 19.2% and operational performance by reducing 3.9% of 85th percentile merging time for the operation of 5% HCV platooning with 0.6 s headway compared with 350 m acceleration lane length. This study suggests 5% of traffic containing two HCV platoons with 0.6 s headway may be reasonable for operation during certain hours of the day under existing conditions.

Suggested Citation

  • Tanvir Uddin Chowdhury & Peter Y. Park & Kevin Gingerich, 2022. "Estimation of Appropriate Acceleration Lane Length for Safe and Efficient Truck Platooning Operation on Freeway Merge Areas," Sustainability, MDPI, vol. 14(19), pages 1-25, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12946-:d:938201
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12946/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/19/12946/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
    2. Shladover, Steven & Lu, Xiao-Yun & Yang, Shiyan & Ramezani, Hani & Spring, John & Nowakowski, Christopher & Nelson, David, 2018. "Cooperative Adaptive Cruise Control (CACC) For Partially Automated Truck Platooning:Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt260060w4, Institute of Transportation Studies, UC Berkeley.
    3. Zabat, Michael & Stabile, Nick & Farascaroli, Stefano & Browand, Frederick, 1995. "The Aerodynamic Performance Of Platoons: A Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8ph187fw, Institute of Transportation Studies, UC Berkeley.
    4. Browand, Fred & McArthur, John & Radovich, Charles, 2004. "Fuel Saving Achieved in the Field Test of Two Tandem Trucks," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt29v570mm, Institute of Transportation Studies, UC Berkeley.
    5. Simard, Richard & L'Ecuyer, Pierre, 2011. "Computing the Two-Sided Kolmogorov-Smirnov Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i11).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuriy Royko & Yevhen Fornalchyk & Eugeniusz Koda & Ivan Kernytskyy & Oleh Hrytsun & Romana Bura & Piotr Osinski & Anna Markiewicz & Tomasz Wierzbicki & Ruslan Barabash & Ruslan Humenuyk & Pavlo Polyan, 2023. "Public Transport Prioritization and Descriptive Criteria-Based Urban Sections Classification on Arterial Streets," Sustainability, MDPI, vol. 15(3), pages 1-15, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sloot Henrik, 2022. "Implementing Markovian models for extendible Marshall–Olkin distributions," Dependence Modeling, De Gruyter, vol. 10(1), pages 308-343, January.
    2. Abdolmaleki, Mojtaba & Shahabi, Mehrdad & Yin, Yafeng & Masoud, Neda, 2021. "Itinerary planning for cooperative truck platooning," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 91-110.
    3. Song-Hee Kim & Ward Whitt, 2014. "Are Call Center and Hospital Arrivals Well Modeled by Nonhomogeneous Poisson Processes?," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 464-480, July.
    4. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    5. Fernández de Marcos Giménez de los Galanes, Alberto & García Portugués, Eduardo, 2022. "Data-driven stabilizations of goodness-of-fit tests," DES - Working Papers. Statistics and Econometrics. WS 35324, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Władysław Marek Hamiga & Wojciech Bronisław Ciesielka, 2022. "Numerical Analysis of Aeroacoustic Phenomena Generated by Heterogeneous Column of Vehicles," Energies, MDPI, vol. 15(13), pages 1-37, June.
    7. Tatjana Miljkovic & Saleem Shaik & Dragan Miljkovic, 2017. "Redefining standards for body mass index of the US population based on BRFSS data using mixtures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 197-211, January.
    8. Talwar, Manish & Talwar, Shalini & Kaur, Puneet & Tripathy, Naliniprava & Dhir, Amandeep, 2021. "Has financial attitude impacted the trading activity of retail investors during the COVID-19 pandemic?," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    9. Barua, Limon & Zou, Bo & Choobchian, Pooria, 2023. "Maximizing truck platooning participation with preferences," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    10. Jos'e Miguel Flores-Contr'o, 2024. "The Gerber-Shiu Expected Discounted Penalty Function: An Application to Poverty Trapping," Papers 2402.11715, arXiv.org.
    11. Shladover, Steven & Barth, Matthew J & Zhang, Wei-Bin, 2011. "Engaging the International Community: Research on Intelligent Transportation Systems (ITS) Applications to Improve Environmental Performance," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4fn6f906, Institute of Transportation Studies, UC Berkeley.
    12. Steland, Ansgar, 2020. "Testing and estimating change-points in the covariance matrix of a high-dimensional time series," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    13. Erik Karger & Marvin Jagals & Frederik Ahlemann, 2021. "Blockchain for Smart Mobility—Literature Review and Future Research Agenda," Sustainability, MDPI, vol. 13(23), pages 1-32, November.
    14. Haramoto, Hiroshi & Matsumoto, Makoto, 2019. "Checking the quality of approximation of p-values in statistical tests for random number generators by using a three-level test," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 161(C), pages 66-75.
    15. Pi, Dawei & Xue, Pengyu & Wang, Weihua & Xie, Boyuan & Wang, Hongliang & Wang, Xianhui & Yin, Guodong, 2023. "Automotive platoon energy-saving: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    16. 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.
    17. Li, Penghua & Zhang, Zijian & Grosu, Radu & Deng, Zhongwei & Hou, Jie & Rong, Yujun & Wu, Rui, 2022. "An end-to-end neural network framework for state-of-health estimation and remaining useful life prediction of electric vehicle lithium batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    18. Enrique Garcia Tejeda, 2022. "La concentracion espacial de los reportes de disparos al 911 en la Ciudad de Mexico: ¿Comportamiento racional en el uso de armas durante la pandemia Covid-19?," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 3(5), pages 69-93.
    19. Carvalho, Luis, 2015. "An Improved Evaluation of Kolmogorovs Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(c03).
    20. Guillaume Coqueret, 2016. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02088097, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12946-:d:938201. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.