Tytuł artykułu
Treść / Zawartość
Pełne teksty:
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Snow removal and deicing using snowplow trucks assist transportation agencies to enhance roadway safety and mobility. However, due to slower travel speeds during these operations, motorists often end up in crashes for poor visibility and disturbance of the snow. Despite the risk associated with snowplows, no previous study was found that exclusively investigate the factors associated with injury severity in snowplow-involved crashes. Therefore, this paper presents an extensive exploratory analysis and fills this knowledge gap by identifying the significant contributing factors affecting the occupant injury severity from the aspects of crashes with snowplow involvement. The study utilized eleven years (2010-2020) of historical snowplow-related crash data from Wyoming. Both the binary logit model and mixed binary logit model were developed to investigate the impacts of the various occupant, vehicle, crash, roadway, and environmental characteristics on the corresponding occupant injury severity. As one of the important findings from this research concludes that other vehicle drivers are more responsible than snowplow drivers contributing to more severe injuries in crashes involving snowplows. Recommendations suggested based on the modeling results are expected to help transportation agencies and policymakers take necessary actions in reducing snowplow-involved crashes by targeting appropriate strategies and proper resource allocation.
Rocznik
Tom
Strony
73--88
Opis fizyczny
Bibliogr. 45 poz., tab.
Twórcy
autor
- Wyoming Technology Transfer Center, University of Wyoming, 1000 E. University Ave., EN 3029, Laramie, WY 82071, USA
autor
- Department of Civil and Architectural and Construction Engineering, University of Wyoming, 1000 E. University Ave., Rm 3071, Laramie, WY 82071, USA
autor
- Wyoming Technology Transfer Center, 1000 E. University Ave., Dept. 3295, Laramie, WY 82071, USA
Bibliografia
- Bhat, C.R. (2003). Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences. Transportation Research Part B: Methodological, 37 (9), 837-855. https://doi.org/10.1016/S0191-2615(02)00090-5
- Camden, M.C., Hickman, J.S., Tidwell, S., Soccolich, S.A., Hammond, R., & Hanowski, R.J. (2020). Defensive Driving for Snowplow Operators (No. CR 18-01). Minnesota. Department of Transportation. Clear Roads Pooled Fund.
- Chen, C., Zhang, G., Huang, H., Wang, J., & Tarefder, R.A. (2016). Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model. Accident Analysis & Prevention, 96, 79-87. https://doi.org/10.1016/j.aap.2016.06.015
- Chen, F., & Chen, S. (2011). Injury severities of truck drivers in single- and multi-vehicle accidents on rural highways. Accid. Anal. Prev., 43(5), 1677-1688. https://doi.org/10.1016/j.aap.2011.03.026
- Clear Roads. (2022). Research for Winter Highway Maintenance. Retrieved from https://clearroads.org/
- Dao, B., Hasanzadeh, S., Walker, C.L., Steinkruger, D., Esmaeili, B., & Anderson, M.R. (2019). Current practices of winter maintenance operations and perceptions of winter weather conditions. Journal of Cold Regions Engineering, (3), 04019008. https://doi.org/10.1061/(ASCE)CR.1943-5495.0000191
- Eisenberg, D., & Warner, K.E. (2005). Effects of snowfalls on motor vehicle collisions, injuries, and fatalities. American Journal of Public Health, 95(1), 120-124. https://doi.org/10.2105/AJPH.2004.048926
- Eluru, N., Paleti, R., Pendyala, R. M., & Bhat, C. R. (2010). Modeling multiple vehicle occupant injury severity: A copula-based multivariate approach. Transportation Research Record, 2165, 1-11. https://doi.org/10.3141/2165-01
- Evrensel, C.A., Jiang, Y., Kim, K., Dur, O., Hu A., and Ma, K. (2008). Winter Maintenance Improvements: Phase I. Report No: RDT08-001. Nevada Department of Transportation (NDOT).
- Farid, A., & Ksaibati, K. (2021). Modeling severities of motorcycle crashes using random parameters. Journal of Traffic and Transportation Engineering (English Edition), 8(2), 225-236. https://doi.org/10.1016/j.jtte.2020.01.001.
- Farid, A., & Ksaibati, K. (2020). Modeling two-lane highway passing-related crashes using mixed ordinal probit regression. Journal of Transportation Engineering, Part A: Systems, 146(9), 04020092. https://doi.org/10.1061/jtepbs.0000428.
- Federal Highway Administration (FHWA). Snow and Ice. http://www.ops.fhwa.dot.gov/weather/weather_events/snow_ice.htm
- Fu, L., & Perchanok, M.S. (2006). Effects of winter weather and maintenance treatments on highway safety (No. 06-0728).
- Haleem, K., & Gan, A. (2013). Effect of driver’s age and side of impact on crash severity along urban freeways: A mixed logit approach. Journal of Safety Research, 46, 67-76. https://doi.org/10.1016/j.jsr.2013.04.002
- Halton, J.H., (1960). On the efficiency of evaluating certain quasirandom sequences of points in evaluating multi-dimensional integrals. Numerische Mathematik, 2(1), 84-90. https://doi.org/10.1007/BF01386213
- Hanbali, R.M., & Kuemmel, D.A. (1992). Traffic accident analysis of ice control operation. Transportation Research Board.
- Haq, M. T., Ampadu, V. M. K., & Ksaibati, K. (2023). An investigation of brake failure related crashes and injury severity on mountainous roadways in Wyoming. Journal of Safety Research, 84, 7-17. https://doi.org/10.1016/j.jsr.2022.10.003
- Haq, M. T., Zlatkovic, M., & Ksaibati, K. (2020). Investigating occupant injury severity of truck-involved crashes based on vehicle types on a mountainous freeway: A hierarchical Bayesian random intercept approach. Accident Analysis & Prevention, 144, 105654. https://doi.org/10.1016/j.aap.2020.105654
- Haq, M. T., Zlatkovic, M., & Ksaibati, K. (2021a). Assessment of commercial truck driver injury severity as a result of driving actions. Transportation Research Record, 2675(9), 1707-1719. https://doi.org/10.1177/03611981211009880
- Haq, M. T., Zlatkovic, M., & Ksaibati, K. (2021b). Assessment of commercial truck driver injury severity based on truck configuration along a mountainous roadway using hierarchical Bayesian random intercept approach. Accident Analysis & Prevention, 162, 106392. https://doi.org/10.1016/j.aap.2021.106392
- Heqimi, G. (2016). Using spatial interpolation to determine impacts of snowfall on traffic crashes. Michigan State University.
- Hossain, M. J., Ivan, J. N., Zhao, S., Wang, K., Sharmin, S., Ravishanker, N., & Jackson, E. (2023). Considering demographics of other involved drivers in predicting the highest driver injury severity in multi-vehicle crashes on rural two-lane roads in California. Journal of Transportation Safety & Security, 15(1), 43-58. https://doi.org/10.1080/19439962.2022.2033899
- Iowa Department of Transportation (IOWADOT). (2017). Safe Travel around Snowplows. https://iowadot.gov/maintenance/pdf/SafeTravelAroundSnowplows.pdf.
- Islam, S., Jones, S. L., & Dye, D. (2014). Comprehensive analysis of single-and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama. Accident Analysis & Prevention, 67, 148-158. https://doi.org/10.1016/j.aap.2014.02.014.
- Kutner, M. H., Nachtsheim, C.J., Neter, J., & Li, W. (2005). Applied Linear Statistical Model. 5th ed., New York, NY: McGraw-Hill/Irwin.
- Lemp, J. D., Kockelman, K. M., & Unnikrishnan, A. (2011). Analysis of large truck crash severity using heteroskedastic ordered probit models. Accident Analysis & Prevention, 43(1), 370-380. https://doi.org/10.1016/j.aap.2010.09.006
- Liu, P., & Fan, W. (2020). Exploring injury severity in head-on crashes using latent class clustering analysis and mixed logit model: A case study of North Carolina. Accident Analysis & Prevention, 135, 105388. https://doi.org/10.1016/j.aap.2019.105388
- Michigan Department of Transportation (MDOT). (2017). Michigan NETS Winter Driving Safety Tips. https://www.michigan.gov/documents/Nov05_144130_7.pdf.
- Minnesota Department of Transportation (MnDOT). (1999). Evaluation of the Minnesota Department of Transportation’s Intelligent Vehicle Initiative Snowplow Demonstration Project on Trunk Highway 19 Winter 1998-1999. Booz⋅Allen & Hamilton Inc.
- Naik, B., Tung, L. W., Zhao, S., & Khattak, A. J. (2016). Weather impacts on single-vehicle truck crash injury severity. Journal of Safety Research, 58, 57-65. https://doi.org/10.1016/j.jsr.2016.06.005
- Norrman, J., Eriksson, M., & Lindqvist, S. (2000). Relationships between road slipperiness, traffic accident risk and winter road maintenance activity. Climate Research, 15(3), 185-193. https://doi.org/10.3354/cr015185
- O’Donnell, C.J., & Connor, D.H. (1996). Predicting the severity using models of ordered multiple choice. Accident Analysis and Prevention, 28(6), 739-753. https://doi.org/10.1016/S0001-4575(96)00050-4
- Obeng, K. (2008). Injury severity, vehicle safety features, and intersection crashes. Traffic Injury Prevention, 9(3), 268–276. https://doi.org/10.1080/15389580802040311.
- Pahukula, J., Hernandez, S., & Unnikrishnan, A. (2015). A time of day analysis of crashes involving large trucks in urban areas. Accident Analysis & Prevention, 75, 155-163. https://doi.org/10.1016/j.aap.2014.11.021
- Qiu, L., & Nixon, W. A. (2008). Effects of adverse weather on traffic crashes: systematic review and meta-analysis. Transportation Research Record, 2055(1), 139-146. https://doi.org/10.3141/2055-16
- Tang, W.J., Zhang, G.H., & Liao, M.J. (2015). A framework of winter road maintenance optimization. In 2015 11th International Conference on Natural Computation (ICNC) (pp. 1057-1061), IEEE. https://doi.org/10.1109/ICNC.2015.7378138
- The Trucker. (2021). Multiple snowplows hit on Wyoming interstates, highways over five-day period. Retrieved from https://www.thetrucker.com/trucking-news/the-nation/multiplesnowplows-hit-on-wyoming-interstates-highways-over-five-day-period
- Train, K.E. (2003). Discrete Choice Methods with Simulation. First Ed., Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9780511753930
- Uddin, M., & Huynh, N. (2018). Factors influencing injury severity of crashes involving HAZMAT trucks. International Journal of Transportation Science and Technology, 7(1), 1-9. https://doi.org/10.1016/j.ijtst.2017.06.004.
- Washington, S.P., Karlaftis, M.G., & Mannering, F. (2011). Statistical and Econometric Methods for Transportation Data Analysis, second ed. Chapman & Hall/CRC, Boca Raton.41.
- Wyoming Seatbelt Coalition. (2022). Buckle Up for Life, Wyoming. Retrieved from https://buckleup4lifewy.org/
- Yen, K., Tan, H-S., Steinfeld, A., .... & Ravani, B. (2000). Development of an advanced snowplow driver assistance system (ASP-II). Final Report of Contract RTA65A0054. California Department of Transportation.
- Zhu, X., & Srinivasan, S. (2011a). Modeling occupant-level injury severity: An application to large-truck crashes. Accident Analysis and Prevention, 43(4), 1427-1437. https://doi.org/10.1016/j.aap.2011.02.021
- Zhu, X., & Srinivasan, S. (2011). A comprehensive analysis of factors influencing the injury severity of large-truck crashes. Accident Analysis & Prevention, 43(1), 49-57. https://doi.org/10.1016/j.aap.2010.07.007
- Zockaie, A., Saedi, R., Gates, T. J., Savolainen, P. T., Schneider, B., Ghamami, M., ... & Zhou, C. (2018). Evaluation of a Collision Avoidance and Mitigation System (CAMS) on Winter Maintenance Trucks (No. OR 17-103). Michigan. Dept. of Transportation. Research Administration.
Uwagi
1. The work presented in this paper is sponsored by the Wyoming Department of Transportation (contract number RS08221), and supported by the Mountain Plains Consortium (MPC). All figures, tables, and equations listed in this paper will be included in the final report at the conclusion of this study. Copyright © 2022. All rights reserved, the State of Wyoming, Wyoming Department of Transportation, and the University of Wyoming.
2. Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a8ccea84-f2c0-4c12-92a9-a4b9aa75013d