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Research on the Safety of the Left Hard Shoulder in a Multi-Lane Highway Based on Safety Performance Function

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  • Penghui Zhao

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Jianxiao Ma

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Chubo Xu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Chuwei Zhao

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Zifan Ni

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

Abstract

The left hard shoulder plays an important role in the event of an emergency on the inside of a multi-lane highway, but past studies have not been able to clarify the criteria for its installation or quantify the safety impact of its installation on the left side. In order to study the influence of the left hard shoulder on the safety of vehicles traveling on multi-lane highways, based on past studies that only studied the situation of four-lane highways, this paper firstly constructs a multi-lane highway simulation model under different numbers of lanes based on the VISSIM traffic simulation and uses Surrogate Safety Assessment Model (SSAM) to study the conflict characteristics of multi-lane highway vehicles under different numbers of lanes. Based on the above findings, this paper introduces the Safety Performance Function (SPF) to construct a multi-lane freeway accident prediction model, calibrates the model by adding the indexes affected by the left side hard shoulder to the basic prediction mode, and uses the historical accident data of the Badou-Shihu section of the Guangdong Northern Second Ring Highway as the basis to study the differences in accident rates of the investigated section before and after setting the left hard shoulder. The study showed that the average Time to Collision (TTC) increased by 57.2%, Maximum Deceleration (MaxD) increased by 19.2%, and Delta Speed (DeltaS) increased by 15.3% after setting hard shoulders on the left side of multi-lane freeways, and traffic conflicts on multi-lane freeways were significantly reduced, and safety was improved considerably. In addition, the rear-end conflict rate decreased by 0.17%, 0.75%, and 4.6% after setting hard shoulders on the left side of one-way three, four, and five lanes, respectively, indicating that hard shoulders on the left side are the most effective in improving the safety of one-way five-lane freeways. The accident prediction results show that within the reasonable setting range of the left hard shoulder width (0~4 m), the accident rate decreases by about 1.5% for every 0.5 m increase if only the influence of the left hard shoulder width is considered. Without considering other factors, increasing the width of the hard shoulder on the left side can reduce the number of accidents. This indicates a significant safety improvement for a one-way five-lane highway after setting the hard shoulder on the left side, and the conclusion is consistent with the simulation results. In this paper, based on past research, the research object is extended to one-way three-, four-, and five-lane highways. The findings of this paper can help the road authorities develop specifications for installing hard shoulders on the left side of multi-lane freeways and adopt strategies to improve the traffic safety level of multi-lane freeways. In addition, the models and methods used in this paper can also help build a framework for future intelligent networked vehicle avoidance systems and promote the development of intelligent networked technologies.

Suggested Citation

  • Penghui Zhao & Jianxiao Ma & Chubo Xu & Chuwei Zhao & Zifan Ni, 2022. "Research on the Safety of the Left Hard Shoulder in a Multi-Lane Highway Based on Safety Performance Function," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15114-:d:973236
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    References listed on IDEAS

    as
    1. Gao, Lu & Lu, Pan & Ren, Yihao, 2021. "A deep learning approach for imbalanced crash data in predicting highway-rail grade crossings accidents," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Shuo Liu & Junhua Wang & Ting Fu, 2016. "Effects of Lane Width, Lane Position and Edge Shoulder Width on Driving Behavior in Underground Urban Expressways: A Driving Simulator Study," IJERPH, MDPI, vol. 13(10), pages 1-14, October.
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    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.

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