IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p13858-d952782.html
   My bibliography  Save this article

Injury Severity Analysis of Rear-End Crashes at Signalized Intersections

Author

Listed:
  • Mostafa Sharafeldin

    (Wyoming Technology Transfer Center (WYT2/LTAP), Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY 82071, USA)

  • Ahmed Farid

    (Department of Civil and Environmental Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA)

  • Khaled Ksaibati

    (Wyoming Technology Transfer Center (WYT2/LTAP), Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY 82071, USA)

Abstract

Signalized intersections are common hotspots for rear-end crashes, causing severe injuries and property damage. Despite recent attempts to determine the contributing causes to injury severity in this crash type, the frequency of severe rear-end crashes is still significant. Therefore, exploring commonly omitted potential risk factors is essential to proper detection of contributing factors to these crashes and planning appropriate countermeasures. This research incorporated the examination of intersection crash data in Wyoming to examine injury severity risk factors in this crash type. The study examined a set of potential roadway, driver, crash, and environmental risk factors, including pavement surface friction, which is a commonly omitted factor in relevant studies. A random-parameters ordinal probit model was developed for the analysis. The findings demonstrated that two crash attributes (motorcycle involvement and improper seat belt use), three driver’s attributes (driver’s condition, age, and gender), and two environmental and roadway characteristics (road condition and pavement friction) impacted the injury severity of rear-end crashes at signalized intersections.

Suggested Citation

  • Mostafa Sharafeldin & Ahmed Farid & Khaled Ksaibati, 2022. "Injury Severity Analysis of Rear-End Crashes at Signalized Intersections," Sustainability, MDPI, vol. 14(21), pages 1-14, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13858-:d:952782
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/13858/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/21/13858/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mostafa Sharafeldin & Omar Albatayneh & Ahmed Farid & Khaled Ksaibati, 2022. "A Bayesian Approach to Examine the Impact of Pavement Friction on Intersection Safety," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    2. Maria Rella Riccardi & Filomena Mauriello & Sobhan Sarkar & Francesco Galante & Antonella Scarano & Alfonso Montella, 2022. "Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain," Sustainability, MDPI, vol. 14(6), pages 1-44, March.
    3. Sarrias, Mauricio, 2016. "Discrete Choice Models with Random Parameters in R: The Rchoice Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i10).
    4. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    5. Feng Chen & Mingtao Song & Xiaoxiang Ma, 2019. "Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model," IJERPH, MDPI, vol. 16(14), pages 1-12, July.
    Full references (including those not matched with items on IDEAS)

    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. Mostafa Sharafeldin & Ahmed Farid & Khaled Ksaibati, 2022. "A Random Parameters Approach to Investigate Injury Severity of Two-Vehicle Crashes at Intersections," Sustainability, MDPI, vol. 14(21), pages 1-13, October.
    2. Xiaojun Shao & Xiaoxiang Ma & Feng Chen & Mingtao Song & Xiaodong Pan & Kesi You, 2020. "A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions," IJERPH, MDPI, vol. 17(2), pages 1-18, January.
    3. Liu, Qiang & Homma, Riken & Iki, Kazuhisa, 2020. "Evaluating cyclists’ perception of satisfaction using 360° videos," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 205-213.
    4. Faisal, Asif & Yigitcanlar, Tan & Paz, Alexander, 2023. "Understanding driverless car adoption: Random parameters ordered probit model for Brisbane, Melbourne and Sydney," Journal of Transport Geography, Elsevier, vol. 110(C).
    5. Haorong Peng & Xiaoxiang Ma & Feng Chen, 2020. "Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis," IJERPH, MDPI, vol. 17(17), pages 1-16, August.
    6. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    7. An, Wookhyun & Alarcón, Silverio, 2021. "Rural tourism preferences in Spain: Best-worst choices," Annals of Tourism Research, Elsevier, vol. 89(C).
    8. Bhat, Chandra R. & Sardesai, Rupali, 2006. "The impact of stop-making and travel time reliability on commute mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 709-730, November.
    9. Weiss, Adam & Habib, Khandker Nurul, 2017. "Examining the difference between park and ride and kiss and ride station choices using a spatially weighted error correlation (SWEC) discrete choice model," Journal of Transport Geography, Elsevier, vol. 59(C), pages 111-119.
    10. Faulques, Martin & Bonnet, Jean & Bourdin, Sébastien & Juge, Marine & Pigeon, Jonas & Richard, Charlotte, 2022. "Generational effect and territorial distributive justice, the two main drivers for willingness to pay for renewable energies," Energy Policy, Elsevier, vol. 168(C).
    11. Barbour, Natalia & Menon, Nikhil & Zhang, Yu & Mannering, Fred, 2019. "Shared automated vehicles: A statistical analysis of consumer use likelihoods and concerns," Transport Policy, Elsevier, vol. 80(C), pages 86-93.
    12. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    13. Dubey, Subodh & Sharma, Ishant & Mishra, Sabyasachee & Cats, Oded & Bansal, Prateek, 2022. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 63-95.
    14. Zhuanglin Ma & Mingjie Luo & Steven I-Jy Chien & Dawei Hu & Xue Zhao, 2020. "Analyzing drivers’ perceived service quality of variable message signs (VMS)," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-19, October.
    15. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    16. Afaq Khattak & Hamad Almujibah & Ahmed Elamary & Caroline Mongina Matara, 2022. "Interpretable Dynamic Ensemble Selection Approach for the Prediction of Road Traffic Injury Severity: A Case Study of Pakistan’s National Highway N-5," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    17. Ke Wang & Xin Ye, 2021. "Development of alternative stochastic frontier models for estimating time-space prism vertices," Transportation, Springer, vol. 48(2), pages 773-807, April.
    18. Zheng Chen & Huiying Wen & Qiang Zhu & Sheng Zhao, 2023. "Severity Analysis of Multi-Truck Crashes on Mountain Freeways Using a Mixed Logit Model," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    19. Stefan Hochguertel & Henry Ohlsson, 2009. "Compensatory inter vivos gifts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 993-1023.
    20. Anoek Castelein & Dennis Fok & Richard Paap, 2020. "A multinomial and rank-ordered logit model with inter- and intra-individual heteroscedasticity," Tinbergen Institute Discussion Papers 20-069/III, Tinbergen Institute.

    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:21:p:13858-:d:952782. 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.