Chapter
Aug 31, 2020
International Conference on Transportation and Development 2020

Severity of Worker-Involved Work Zone Crashes: A Study of Contributing Factors

Publication: International Conference on Transportation and Development 2020

ABSTRACT

Despite the recent efforts to investigate crash severity, worker presence and its impact on injury severity in work zone crashes is still unexplored. A better understanding of work zone crash characteristics can help to enhance roadway safety for not only road users, but construction crew. Employing a mixed logit (MXL) modeling framework, the present study aims to identify and investigate contributing factors associated with work zone crashes involved workers. Random forest (RF), a data mining approach, is also applied to evaluate variables’ importance for comparison between worker-involved and non-worker involved crashes. The estimation results demonstrated that work on the shoulder or median, advance warning area, daytime non-peak, and multi-occupant variables have heterogeneous effects on injury severity. The analysis of marginal effects indicated variables with substantial influences on injury severity outcomes. The results of this study provide valuable insights for work zone crashes analysis.

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REFERENCES

Abdelmohsen, A. Z., El-Rayes, K., 2018. Optimizing the planning of highway work zones to maximize safety and mobility. Journal of Management in Engineering 34 (1), 04017048.
Anastasopoulos, P. C., Mannering, F. L., 2009. A note on modeling vehicle accident frequencies with random-parameters count models. Accident Analysis & Prevention 41 (1), 153-159.
Anderson, J., Hernandez, S., 2017. Roadway classifications and the accident injury severities of heavy-vehicle drivers. Analytic Methods in Accident Research 15, 17-28.
Arditi, D., Lee, D.-E., Polat, G., 2007. Fatal accidents in nighttime vs. Daytime highway construction work zones. Journal of Safety Research 38 (4), 399-405.
Artba, 2018. American road & transportation builders association. National Work Zone Safety Information Clearinghouse.
Behnood, A., Mannering, F., 2017. Determinants of bicyclist injury severities in bicycle-vehicle crashes: A random parameters approach with heterogeneity in means and variances. Analytic methods in accident research 16, 35-47.
Cerwick, D. M., Gkritza, K., Shaheed, M. S., Hans, Z., 2014. A comparison of the mixed logit and latent class methods for crash severity analysis. Analytic Methods in Accident Research 3, 11-27.
Christoforou, Z., Cohen, S., Karlaftis, M. G., 2010. Vehicle occupant injury severity on highways: An empirical investigation. Accident Analysis & Prevention 42 (6), 1606-1620.
Garber, N. J., Zhao, M., 2002. Distribution and characteristics of crashes at different work zone locations in virginia. Transportation Research Record 1794 (1), 19-25.
Ghasemzadeh, A., Ahmed, M. M., 2019. Exploring factors contributing to injury severity at work zones considering adverse weather conditions. IATSS research 43 (3), 131-138.
Haghighi, N., Liu, X. C., Zhang, G., Porter, R. J., 2018. Impact of roadway geometric features on crash severity on rural two-lane highways. Accident Analysis & Prevention 111, 34-42.
Haleem, K., Abdel-Aty, M., 2012. Application of glasso in variable selection and crash prediction at unsignalized intersections. Journal of transportation engineering 138 (7), 949-960.
Haleem, K., Alluri, P., Gan, A., 2015. Analyzing pedestrian crash injury severity at signalized and non-signalized locations. Accident Analysis & Prevention 81, 14-23.
Harb, R., Radwan, E., Yan, X., Pande, A., Abdel-Aty, M., 2008. Freeway work-zone crash analysis and risk identification using multiple and conditional logistic regression. Journal of Transportation Engineering 134 (5), 203-214.
Kamyab, A., Mcdonald, T., Storm, B., Anderson-Wilk, M., 2003. Effectiveness of extra enforcement in construction and maintenance work zones.
Khattak, A. J., Khattak, A. J., Council, F. M., 2002. Effects of work zone presence on injury and non-injury crashes. Accident Analysis & Prevention 34 (1), 19-29.
Khattak, A. J., Targa, F., 2004. Injury severity and total harm in truck-involved work zone crashes. Transportation research record 1877 (1), 106-116.
Kitali, A. E., Alluri, P., Sando, T., Haule, H., Kidando, E., Lentz, R., 2018. Likelihood estimation of secondary crashes using bayesian complementary log-log model. Accident Analysis & Prevention 119, 58-67.
Li, Y., Bai, Y., 2009. Highway work zone risk factors and their impact on crash severity. Journal of Transportation engineering 135 (10), 694-701.
Li, Z., Liu, P., Wang, W., Xu, C., 2012. Using support vector machine models for crash injury severity analysis. Accident Analysis & Prevention 45, 478-486.
Liaw, A., Wiener, M., 2002. Classification and regression by randomforest. R news 2 (3), 18-22.
Lo, A., Chernoff, H., Zheng, T., Lo, S.-H., 2015. Why significant variables aren’t automatically good predictors. Proceedings of the National Academy of Sciences 112 (45), 13892-13897.
Mamdoohi, S., Song, Z., Sharifi, M. S., Nasr-Isfahani, H., 2018, Estimation of standard pedestrian equivalent factors for heterogeneous pedestrian stream containing individuals with disabilities. Transportation Research Board 97th Annual MeetingTransportation Research Board.
Mannering, F. L., Shankar, V., Bhat, C. R., 2016. Unobserved heterogeneity and the statistical analysis of highway accident data. Analytic methods in accident research 11, 1-16.
Mansourkhaki, A., Karimpour, A., Yazdi, H. S., 2017. Introducing prior knowledge for a hybrid accident prediction model. KSCE Journal of Civil Engineering 21 (5), 1912-1918.
Mokhtarimousavi, S., 2019. A time of day analysis of pedestrian-involved crashes in california: Investigation of injury severity, a logistic regression and machine learning approach using hsis data. Institute of Transportation Engineers. ITE Journal 89 (10), 25-33.
Mokhtarimousavi, S., Anderson, J. C., Azizinamini, A., Hadi, M., 2019. Improved support vector machine models for work zone crash injury severity prediction and analysis. Transportation Research Record, 0361198119845899.
Mokhtarimousavi, S., Anderson, J. C., Azizinamini, A., Hadi, M., 2020. Factors affecting injury severity in vehicle-pedestrian crashes: A day-of-week analysis using random parameter ordered response models and artificial neural networks. International Journal of Transportation Science and Technology, https://doi.org/10.1016/j.ijtst.2020.01.001.
Osman, M., Mishra, S., Paleti, R., Golias, M., 2019. Impacts of work zone component areas on driver injury severity. Journal of Transportation Engineering, Part A: Systems 145 (8), 04019032.
Osman, M., Paleti, R., Mishra, S., 2018. Analysis of passenger-car crash injury severity in different work zone configurations. Accident Analysis & Prevention 111, 161-172.
Ozturk, O., 2014. Investigating impact of work zones on crash frequency, severity and traffic Rutgers The State University of New Jersey-New Brunswick.
Qi, Y., Srinivasan, R., Teng, H., Baker, R., 2013. Analysis of the frequency and severity of rear-end crashes in work zones. Traffic injury prevention 14 (1), 61-72.
S4a, 2018. Signal four analytics. The GeoPlan Center, Department of Urban & Regional Planning, University of Florida.
Savolainen, P. T., Mannering, F. L., Lord, D., Quddus, M. A., 2011. The statistical analysis of highway crash-injury severities: A review and assessment of methodological alternatives. Accident Analysis & Prevention 43 (5), 1666-1676.
Seraneeprakarn, P., Huang, S., Shankar, V., Mannering, F., Venkataraman, N., Milton, J., 2017. Occupant injury severities in hybrid-vehicle involved crashes: A random parameters approach with heterogeneity in means and variances. Analytic Methods in Accident Research 15, 41-55.
Taylor, D. R., Muthiah, S., Kulakowski, B. T., Mahoney, K. M., Porter, R. J., 2007. Artificial neural network speed profile model for construction work zones on high-speed highways. Journal of Transportation Engineering 133 (3), 198-204.
Washington, S. P., Karlaftis, M. G., Mannering, F., 2010. Statistical and econometric methods for transportation data analysis Chapman and Hall/CRC.
Yang, H., Ozbay, K., Ozturk, O., Xie, K., 2015. Work zone safety analysis and modeling: A state-of-the-art review. Traffic injury prevention 16 (4), 387-396.
Ye, F., Lord, D., 2014. Comparing three commonly used crash severity models on sample size requirements: Multinomial logit, ordered probit and mixed logit models. Analytic methods in accident research 1, 72-85.
Yu, R., Abdel-Aty, M., 2014. Analyzing crash injury severity for a mountainous freeway incorporating real-time traffic and weather data. Safety science 63, 50-56.

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Go to International Conference on Transportation and Development 2020
International Conference on Transportation and Development 2020
Pages: 47 - 59
Editor: Guohui Zhang, Ph.D., University of Hawaii
ISBN (Online): 978-0-7844-8314-5

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Published online: Aug 31, 2020
Published in print: Aug 31, 2020

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Authors

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Seyedmirsajad Mokhtarimousavi [email protected]
1Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Florida International Univ., ARC, Miami, FL. Email: [email protected]
Atorod Azizinamini, Ph.D. [email protected]
P.E.
2Professor and Chair, Accelerate Bridge Construction University Transportation Center, Dept. of Civil and Environmental Engineering, Florida International Univ., Miami, FL. Email: [email protected]
Mohammed Hadi, Ph.D. [email protected]
P.E.
3Professor, Dept. of Civil and Environmental Engineering, Florida International Univ., Miami, FL. Email: [email protected]

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