IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14055-d956466.html
   My bibliography  Save this article

Quarterly Instability Analysis of Injury Severities in Truck Crashes

Author

Listed:
  • Fulu Wei

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Danping Dong

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Pan Liu

    (School of Transportation, Southeast University, Nanjing 211102, China)

  • Yongqing Guo

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Zhenyu Wang

    (Center for Urban Transportation Research, University of South Florida, Tampa, FL 33620, USA)

  • Qingyin Li

    (School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

Abstract

The impact of trucks on road traffic safety has been extensively studied, but the factors influencing truck crash injury severity have not yet been examined from the quarterly perspective. Crash data for Shandong Province in China for 10 years (2012–2021) were reviewed to investigate the transferability of the determinants of the severity of truck crash injuries in four quarters. Three injury severity levels were considered and a random parameters logit model (RPL) considering the heterogeneity of means and variances was constructed to assess the factors affecting the severity of crash injury. The significant variables were explored from the influencing factors of driver, vehicle, crash type, road, environment, and temporal characteristics. A likelihood ratio test was employed to assess the transferability of the crash model over four quarters, and we used marginal effects to analyze the stability of the influencing factors. The results indicated that there was instability among the four quarterly variables that had to be modeled separately. There were also some variables, such as heavy vehicle and multiple-vehicle crashes, that simultaneously affected the severity of truck crash injuries across the four quarters, but the degree of impact was different. The results could enable engineers and policy makers to better formulate management rules and propose appropriate measures according to quarterly changes.

Suggested Citation

  • Fulu Wei & Danping Dong & Pan Liu & Yongqing Guo & Zhenyu Wang & Qingyin Li, 2022. "Quarterly Instability Analysis of Injury Severities in Truck Crashes," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14055-:d:956466
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14055/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/14055/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ahmed Alkhoori, Fatima & Kumar Maghelal, Praveen, 2021. "Regulating the overloading of heavy commercial Vehicles: Assessment of land transport operators in Abu Dhabi," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 287-299.
    2. Castillo-Manzano, José I. & Castro-Nuño, Mercedes & Fageda, Xavier, 2016. "Exploring the relationship between truck load capacity and traffic accidents in the European Union," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 94-109.
    3. 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.
    4. Zhenggan Cai & Fulu Wei & Zhenyu Wang & Yongqing Guo & Long Chen & Xin Li, 2021. "Modeling of Low Visibility-Related Rural Single-Vehicle Crashes Considering Unobserved Heterogeneity and Spatial Correlation," Sustainability, MDPI, vol. 13(13), pages 1-24, July.
    5. Xiong, Yingge & Mannering, Fred L., 2013. "The heterogeneous effects of guardian supervision on adolescent driver-injury severities: A finite-mixture random-parameters approach," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 39-54.
    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. Buddhavarapu, Prasad & Scott, James G. & Prozzi, Jorge A., 2016. "Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 492-510.
    2. Behram Wali & Asad Khattak & Thomas Karnowski, 2020. "The relationship between driving volatility in time to collision and crash injury severity in a naturalistic driving environment," Papers 2010.04719, arXiv.org.
    3. Rajesh Paleti & Lacramioara Balan, 2019. "Misclassification in travel surveys and implications to choice modeling: application to household auto ownership decisions," Transportation, Springer, vol. 46(4), pages 1467-1485, August.
    4. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    5. Juan Guillermo Urzúa-Morales & Juan Pedro Sepulveda-Rojas & Miguel Alfaro & Guillermo Fuertes & Rodrigo Ternero & Manuel Vargas, 2020. "Logistic Modeling of the Last Mile: Case Study Santiago, Chile," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    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. 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.
    8. 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.
    9. 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.
    10. Jingjing Xu & Behram Wali & Xiaobing Li & Jiaqi Yang, 2019. "Injury Severity and Contributing Driver Actions in Passenger Vehicle–Truck Collisions," IJERPH, MDPI, vol. 16(19), pages 1-16, September.
    11. 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.
    12. 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.
    13. 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.
    14. Chen, Zhiwei & Li, Xiaopeng, 2021. "Unobserved heterogeneity in transportation equity analysis: Evidence from a bike-sharing system in southern Tampa," Journal of Transport Geography, Elsevier, vol. 91(C).
    15. Stefan Hochguertel & Henry Ohlsson, 2009. "Compensatory inter vivos gifts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 993-1023.
    16. 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.
    17. Richards, Timothy J. & Hamilton, Stephen F. & Yonezawa, Koichi, 2018. "Retail Market Power in a Shopping Basket Model of Supermarket Competition," Journal of Retailing, Elsevier, vol. 94(3), pages 328-342.
    18. Muhammad Ijaz & Lan Liu & Yahya Almarhabi & Arshad Jamal & Sheikh Muhammad Usman & Muhammad Zahid, 2022. "Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances," IJERPH, MDPI, vol. 19(17), pages 1-24, August.
    19. Timothy J. Richards & Gordon J. Klein & Celine Bonnet & Zohra Bouamra-Mechemache, 2020. "Strategic Obfuscation and Retail Pricing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 57(4), pages 859-889, December.
    20. Muhammad Wisal Khattak & Hans De Backer & Pieter De Winne & Tom Brijs & Ali Pirdavani, 2024. "Comparative Evaluation of Crash Hotspot Identification Methods: Empirical Bayes vs. Potential for Safety Improvement Using Variants of Negative Binomial Models," Sustainability, MDPI, vol. 16(4), pages 1-22, February.

    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:14055-:d:956466. 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.