IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i2p382-d197359.html
   My bibliography  Save this article

Practical Road-Resistance Functions for Expressway Work Zones in Occupied Lane Conditions

Author

Listed:
  • Chi Zhang

    (Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an 710064, China
    China Communications Construction First Highway Consultants Co., Ltd., Xi’an 710064, China)

  • Jihan Qin

    (Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an 710064, China)

  • Min Zhang

    (Traffic Engineering Research Institute, School of Highway, Chang’an University, Xi’an 710064, China)

  • Hong Zhang

    (Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an 710064, China)

  • Yudi Hou

    (Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an 710064, China)

Abstract

In order to create a practical road-resistance function for work zones under different lane occupation conditions, the expected speed of vehicles was calibrated in the work zone simulation model based on measured data, and simulation models were constructed for the closed half lane and the closed inside lane under different rates of trucks. Based on the statistical theory, the influence of significance of traffic volume and truck ratios for road resistance was analyzed, and a suitable truck ratio was found for the work zone. By using the optimal nonlinear fitting theory, the practical road-resistance function for work zones under different lane occupation conditions was constructed. The results showed that the road resistance is significantly affected by the traffic volume and rate of trucks. Under the same truck ratio, the road resistance linearly increases slowly when the traffic volume is less than the critical traffic volume and rapid increases irregularly when it is greater than the critical traffic volume. Under the same traffic load, the road resistance of the work zone increases with the increase in the rate of trucks, and the difference is not obvious when the traffic volume is less than the critical traffic volume, and increases gradually when it is greater than the critical traffic volume. Through the goodness of fit test and the homogeneity of variance test, the road-resistance function constructed in this paper has high goodness of fit. The practical road-resistance functions constructed in this study could be used to guide the diversion of the rebuilt/expanded highway to ensure traffic safety. Further, the study provides a theoretical basis for the construction of intelligent highway work zones.

Suggested Citation

  • Chi Zhang & Jihan Qin & Min Zhang & Hong Zhang & Yudi Hou, 2019. "Practical Road-Resistance Functions for Expressway Work Zones in Occupied Lane Conditions," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:2:p:382-:d:197359
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/2/382/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/2/382/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li Li & Dong Zhang, 2018. "Merging Vehicles and Lane Speed-Flow Relationship in a Work Zone," Sustainability, MDPI, vol. 10(7), pages 1-13, June.
    2. Heinz Spiess, 1990. "Technical Note—Conical Volume-Delay Functions," Transportation Science, INFORMS, vol. 24(2), pages 153-158, May.
    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. Yangyang Wu & Suren Chen, 2023. "Transportation Resilience Modeling and Bridge Reconstruction Planning Based on Time-Evolving Travel Demand during Post-Earthquake Recovery Period," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    2. Yang Shao & Zhongbin Luo & Huan Wu & Xueyan Han & Binghong Pan & Shangru Liu & Christian G. Claudel, 2020. "Evaluation of Two Improved Schemes at Non-Aligned Intersections Affected by a Work Zone with an Entropy Method," Sustainability, MDPI, vol. 12(14), pages 1-24, July.
    3. Hoang-Tung, Nguyen & Viet Hung, Do & Kato, Hironori & Binh, Phan Le, 2021. "Modeling ceiling price for build-operate-transfer road projects in developing countries," Economics of Transportation, Elsevier, vol. 28(C).

    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. Li, Qiaoru & Zhang, Zhe & Li, Kun & Chen, Liang & Wei, Zhenlin & Zhang, Jingchun, 2020. "Evolutionary dynamics of traveling behavior in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Guillaume Monchambert, 2023. "Pricing of myopic multi-sided platforms: theory and application to carpooling," Working Papers halshs-03980205, HAL.
    3. Abdullah Alshehri & Mahmoud Owais & Jayadev Gyani & Mishal H. Aljarbou & Saleh Alsulamy, 2023. "Residual Neural Networks for Origin–Destination Trip Matrix Estimation from Traffic Sensor Information," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    4. Yong Liang & Mengshi Lu & Zuo‐Jun Max Shen & Runyu Tang, 2021. "Data Center Network Design for Internet‐Related Services and Cloud Computing," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2077-2101, July.
    5. Owais, Mahmoud & Moussa, Ghada S. & Hussain, Khaled F., 2019. "Sensor location model for O/D estimation: Multi-criteria meta-heuristics approach," Operations Research Perspectives, Elsevier, vol. 6(C).
    6. Bawan Mahmood & Jalil Kianfar, 2019. "Driver Behavior Models for Heavy Vehicles and Passenger Cars at a Work Zone," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    7. Xu, Junxiang & Zhang, Jin & Guo, Jingni, 2021. "Contribution to the field of traffic assignment: A boundedly rational user equilibrium model with uncertain supply and demand," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    8. Beziat, Adrien & Koning, Martin & Toilier, Florence, 2017. "Marginal congestion costs in the case of multi-class traffic: A macroscopic assessment for the Paris Region," Transport Policy, Elsevier, vol. 60(C), pages 87-98.
    9. Moshtagh, Mehrdad & Fathali, Jafar & Smith, J. MacGregor, 2018. "The Stochastic Queue Core problem, evacuation networks, and state-dependent queues," European Journal of Operational Research, Elsevier, vol. 269(2), pages 730-748.
    10. Ouassim Manout & Patrick Bonnel & François Pacull, 2021. "Spatial Aggregation Issues in Traffic Assignment Models," Networks and Spatial Economics, Springer, vol. 21(1), pages 1-29, March.
    11. Chen, Zhichao & Zheng, Changjiang & Tao, Tongtong & Wang, Yanyan, 2024. "Reliability analysis of urban road traffic network under targeted attack strategies considering traffic congestion diffusion," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    12. Temelcan, Gizem & Kocken, Hale Gonce & Albayrak, Inci, 2021. "Fuzzy modelling of static system optimum traffic assignment problem having multi origin-destination pair," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    13. Hou, Guangyang & Chen, Suren & Bao, Yulong, 2022. "Development of travel time functions for disrupted urban arterials with microscopic traffic simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    14. Preda Pichayapan & Manop Kaewmoracharoen & Thanatchaporn Peansara & Patcharapan Nanthavisit, 2020. "Urban School Area Road Safety Improvement and Assessment with a 3D Piano-Keyboard-Styled Pedestrian Crossing Approach: A Case Study of Chiang Mai University Demonstration School," Sustainability, MDPI, vol. 12(16), pages 1-14, August.

    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:11:y:2019:i:2:p:382-:d:197359. 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.