IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7188-d1133014.html
   My bibliography  Save this article

Analysis of Injury Severity of Work Zone Truck-Involved Crashes in South Carolina for Interstates and Non-Interstates

Author

Listed:
  • Mahyar Madarshahian

    (Department of Civil and Environmental Engineering, University of Nebraska-Lincoln, 2200 Vine St, Suite 262, Lincoln, NE 68583, USA
    These authors contributed equally to this work.)

  • Aditya Balaram

    (Department of Management Science, University of South Carolina, 1014 Greene St, Columbia, SC 29208, USA
    These authors contributed equally to this work.)

  • Fahim Ahmed

    (Department of Civil and Environmental Engineering, University of South Carolina, 300 Main St, Columbia, SC 29208, USA
    These authors contributed equally to this work.)

  • Nathan Huynh

    (Department of Civil and Environmental Engineering, University of Nebraska-Lincoln, 2200 Vine St, Suite 262, Lincoln, NE 68583, USA
    These authors contributed equally to this work.)

  • Chowdhury K. A. Siddiqui

    (South Carolina Department of Transportation, 955 Park St, Columbia, SC 29208, USA
    These authors contributed equally to this work.)

  • Mark Ferguson

    (Department of Management Science, University of South Carolina, 1014 Greene St, Columbia, SC 29208, USA)

Abstract

This study investigates factors contributing to the injury severity of truck-involved work zones crashes in South Carolina (SC). The outcome of interest is injury or property damage only crashes, and the explanatory factors examined include the occupant, vehicle, collision, roadway, temporal, and environmental characteristics. Two mixed (random parameter) logit models are developed, one for non-interstates with speed limits less than 60 miles per hour (mph) and one for interstates with speed limits greater than or equal to 60 mph, using South Carolina statewide truck-involved work zone crash data from 2014 to 2020. Results of log-likelihood ratio tests indicate that separate speed models are warranted. The factors that were found to contribute to injury at the 90% confidence level in both models (interstate and non-interstate) are (1) dark lighting conditions, (2) female (at-fault) drivers, and (3) driving too fast for roadway conditions. Significant factors that apply only to non-interstates are SC or US primary roadways, activity area of the work zone, at-fault drivers under 35, sideswipe collision, presence of workers in the work zone, and collision with fixed objects. Significant factors that apply only to interstates are three or more vehicles, rear-end collision, location before the first work zone sign, and weekdays.

Suggested Citation

  • Mahyar Madarshahian & Aditya Balaram & Fahim Ahmed & Nathan Huynh & Chowdhury K. A. Siddiqui & Mark Ferguson, 2023. "Analysis of Injury Severity of Work Zone Truck-Involved Crashes in South Carolina for Interstates and Non-Interstates," Sustainability, MDPI, vol. 15(9), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7188-:d:1133014
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7188/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/9/7188/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Shengdi Chen & Shiwen Zhang & Yingying Xing & Jian Lu, 2020. "Identifying the Factors Contributing to the Severity of Truck-Involved Crashes in Shanghai River-Crossing Tunnel," IJERPH, MDPI, vol. 17(9), pages 1-15, May.
    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. Al-Baraa Abdulrahman Al-Mekhlafi & Ahmad Shahrul Nizam Isha & Nicholas Chileshe & Mohammed Abdulrab & Anwar Ameen Hezam Saeed & Ahmed Farouk Kineber, 2021. "Modelling the Relationship between the Nature of Work Factors and Driving Performance Mediating by Role of Fatigue," IJERPH, MDPI, vol. 18(13), pages 1-17, June.
    2. 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.
    3. Chenming Jiang & Junliang He & Shengxue Zhu & Wenbo Zhang & Gen Li & Weikun Xu, 2023. "Injury-Based Surrogate Resilience Measure: Assessing the Post-Crash Traffic Resilience of the Urban Roadway Tunnels," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    4. Yubing Zheng & Yang Ma & Nan Li & Jianchuan Cheng, 2019. "Personality and Behavioral Predictors of Cyclist Involvement in Crash-Related Conditions," IJERPH, MDPI, vol. 16(24), pages 1-19, December.
    5. Seung-Hoon Park & Min-Kyung Bae, 2020. "Exploring the Determinants of the Severity of Pedestrian Injuries by Pedestrian Age: A Case Study of Daegu Metropolitan City, South Korea," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    6. Khaled Assi & Syed Masiur Rahman & Umer Mansoor & Nedal Ratrout, 2020. "Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol," IJERPH, MDPI, vol. 17(15), pages 1-17, July.
    7. Yun Xiao, 2020. "Analysis of the influencing factors of the unsafe driving behaviors of online car-hailing drivers in china," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-13, April.
    8. Jinhua Tan & Li Gong & Xuqian Qin, 2019. "Effect of Imitation Phenomenon on Two-Lane Traffic Safety in Fog Weather," IJERPH, MDPI, vol. 16(19), pages 1-15, October.
    9. Zijun Liang & Yun Xiao, 2020. "Analysis of factors influencing expressway speeding behavior in China," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-13, September.
    10. Huiying Wen & Yingxin Du & Zheng Chen & Sheng Zhao, 2022. "Analysis of Factors Contributing to the Injury Severity of Overloaded-Truck-Related Crashes on Mountainous Highways in China," IJERPH, MDPI, vol. 19(7), pages 1-17, April.
    11. Hong Tan & Fuquan Zhao & Han Hao & Zongwei Liu & Amer Ahmad Amer & Hassan Babiker, 2020. "Automatic Emergency Braking (AEB) System Impact on Fatality and Injury Reduction in China," IJERPH, MDPI, vol. 17(3), pages 1-13, February.
    12. Liqing Li & Haifeng Ding, 2022. "The Relationship between Internet Use and Population Health: A Cross-Sectional Survey in China," IJERPH, MDPI, vol. 19(3), pages 1-17, January.
    13. Shuaiming Chen & Haipeng Shao & Ximing Ji, 2021. "Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Kanghyun Kim & Jungyeol Hong, 2023. "Severity Predictions for Intercity Bus Crashes on Highway Using a Random Parameter Ordered Probit Model," Sustainability, MDPI, vol. 15(17), pages 1-15, August.
    19. Sheng Dong & Afaq Khattak & Irfan Ullah & Jibiao Zhou & Arshad Hussain, 2022. "Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations," IJERPH, MDPI, vol. 19(5), pages 1-23, March.
    20. Milad Delavary Foroutaghe & Abolfazl Mohammadzadeh Moghaddam & Vahid Fakoor, 2020. "Impact of law enforcement and increased traffic fines policy on road traffic fatality, injuries and offenses in Iran: Interrupted time series analysis," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-13, April.

    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:15:y:2023:i:9:p:7188-:d:1133014. 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.