Better Rested than Sorry: Data-Driven Approach to Reducing Drowsy Driving Crashes on Interstates
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 10
Abstract
Driver perception-reaction time and ability to sustain attention decrease as drivers become drowsy. The consequences of drowsy driving crashes are often worse on interstate highways due to the relatively high travel speeds typical on such facilities. To address the problem of driver fatigue, rest areas are often located along interstates and other long-distance highways to serve as public facilities at which motorists can take a break from driving. This paper explores the relationship between a range of crash factors and the injury severity outcomes of drowsy driving crashes on interstates in Alabama. The crash outcomes were examined in relation to interstate rest area locations. Findings from the study establish that severe injury crashes were more likely to be recorded on interstates that did not have any public rest areas. In addition, drowsy driving crashes that occurred more than 16.1 km (10 mi) away from a public rest area and those that occurred after a driver passed a rest area were more likely to record severe injuries. Other factors that were found to be associated with drowsy driving crash outcomes include unlit roadway conditions, driver gender and age, seatbelt use, location attributes of the crash site, and some temporal factors. Drowsy driving crashes involving out-of-state drivers were also found to have higher chances of recording severe injuries. Increased driver education and public campaigns are recommended as strategies to reduce drowsy driving–related crashes. While drivers should be encouraged to utilize rest areas, state officials should ensure adequate security and sanitation as well as provide amenities to make rest areas more attractive to motorists.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to thank the Alabama Transportation Institute (ATI) for the financial support of this work and the Center for Advanced Public Safety at the University of Alabama for access to the crash data.
References
Adanu, E., A. Hainen, and S. Jones. 2018. “Latent class analysis of factors that influence weekday and weekend single-vehicle crash severities.” Accid. Anal. Prev. 113: 187–192. https://doi.org/10.1016/j.aap.2018.01.035.
Anastasopoulos, P., and F. Mannering. 2011. “An empirical assessment of fixed and random parameter logit models using crash- and non-crash-specific injury data.” Accid. Anal. Prev. 43 (3): 1140–1147. https://doi.org/10.1016/j.aap.2010.12.024.
Arvin, R., M. Kamrani, and A. J. Khattak. 2019. “The role of pre-crash driving instability in contributing to crash intensity using naturalistic driving data.” Accid. Anal. Prev. 132: 105226. https://doi.org/10.1016/j.aap.2019.07.002.
Balan, L., and R. Paleti. 2018. “Modified mixed generalized ordered response model to handle misclassification in injury severity data.” Transp. Res. Rec. 2672 (30): 53–63. https://doi.org/10.1177/0361198118796352.
Behnood, A., and F. Mannering. 2017. “Determinants of bicyclist injury severities in bicycle-vehicle crashes: A random parameters approach with heterogeneity in means and variances.” Anal. Methods Accid. Res. 16: 35–47. https://doi.org/10.1016/j.amar.2017.08.001.
Bhat, C. 2003. “Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences.” Trans. Res. Part B 37 (9): 837–855. https://doi.org/10.1016/S0191-2615(02)00090-5.
Bhat, C. R., and V. Pulugurta. 1998. “A comparison of two alternative behavioral choice mechanisms for household auto ownership decisions.” Transp. Res. Part B: Methodol. 32 (1): 61–75. https://doi.org/10.1016/S0191-2615(97)00014-3.
Bujosa, A., A. Riera, and R. L. Hicks. 2010. “Combining discrete and continuous representations of preference heterogeneity: A latent class approach.” Environ. Resour. Econ. 47 (4): 477–493. https://doi.org/10.1007/s10640-010-9389-y.
de Pinho, R. S., F. P. da Silva-Júnior, J. P. C. Bastos, W. S. Maia, M. T. de Mello, V. M. de Bruin, and P. F. C. de Bruin. 2006. “Hypersomnolence and accidents in truck drivers: A cross-sectional study.” Chronobiol. Int. 23 (5): 963–971. https://doi.org/10.1080/07420520600920759.
Elliott, M. R., M. J. Kallan, D. R. Durbin, and F. K. Winston. 2006. “Effectiveness of child safety seats vs seat belts in reducing risk for death in children in passenger vehicle crashes.” Arch. Pediatr. Adolesc. Med. 160 (6): 617–621. https://doi.org/10.1001/archpedi.160.6.617.
Eluru, N. 2013. “Evaluating alternate discrete choice frameworks for modeling ordinal discrete variables.” Accid. Anal. Prev. 55: 1–11. https://doi.org/10.1016/j.aap.2013.02.012.
Eluru, N., C. Bhat, and D. Hensher. 2008. “A mixed generalized ordered response model for examining pedestrian and bicyclist injury severity level in traffic crashes.” Accid. Anal. Prev. 40 (3): 1033–1054. https://doi.org/10.1016/j.aap.2007.11.010.
Eluru, N., and C. R. Bhat. 2007. “A joint econometric analysis of seat belt use and crash-related injury severity.” Accid. Anal. Prev. 39 (5): 1037–1049. https://doi.org/10.1016/j.aap.2007.02.001.
Eluru, N., R. Paleti, R. M. Pendyala, and C. R. Bhat. 2010. “Modeling injury severity of multiple occupants of vehicles.” Transp. Res. Rec. 2165 (1): 1–11. https://doi.org/10.3141/2165-01.
Eskandarian, A., P. Delaigue, R. Sayed, and A. Mortazavi. 2008. “Development and verification of a truck driving simulator for driver drowsiness studies.” Accessed June 4, 2020. http://www.cisr.gwu.edu/truck_sim.pdf.
Fountas, G., and P. C. Anastasopoulos. 2017. “A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities.” Anal. Methods Accid. Res. 15: 1–16. https://doi.org/10.1016/j.amar.2017.03.002.
Fountas, G., A. Fonzone, N. Gharavi, and T. Rye. 2020. “The joint effect of weather and lighting conditions on injury severities of single-vehicle accidents.” Anal. Methods Accid. Res. 27: 100124. https://doi.org/10.1016/j.amar.2020.100124.
Greene, W. H., and D. A. Hensher. 2003. “A latent class model for discrete choice analysis: Contrasts with mixed logit.” Trans. Res. Part B 37: 681–698. https://doi.org/10.1016/S0191-2615(02)00046-2.
Greene, W. H., and D. A. Hensher. 2013. “Revealing additional dimensions of preference heterogeneity in a latent class mixed multinomial logit model.” Appl. Econ. 45 (14): 1897–1902. https://doi.org/10.1080/00036846.2011.650325.
Howard, M. E., A. V. Desai, R. R. Grunstein, C. Hukins, J. G. Armstrong, D. Joffe, P. Swann, D. A. Campbell, and R. J. Pierce. 2004. “Sleepiness, sleep-disordered breathing, and accident risk factors in commercial vehicle drivers.” Am. J. Respir. Crit. Care Med. 170 (9): 1014–1021. https://doi.org/10.1164/rccm.200312-1782OC.
Islam, S., and F. Mannering. 2006. “Driver aging and its effect on male and female single-vehicle accident injuries: Some additional evidence.” J. Saf. Res. 37 (3): 267–276. https://doi.org/10.1016/j.jsr.2006.04.003.
Jung, S., S. Joo, and C. Oh. 2017. “Evaluating the effects of supplemental rest areas on freeway crashes caused by drowsy driving.” Accid. Anal. Prev. 99 (Feb): 356–363. https://doi.org/10.1016/j.aap.2016.12.021.
Kang, M. W., S. U. Momtaz, and T. E. Barnett. 2015. “Crash analysis and public survey for drowsy-driving advisory systems.” J. Transp. Eng. 141 (9): 04015016. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000777.
Kim, J., G. F. Ulfarsson, S. Kim, and V. N. Shankar. 2013. “Driver-injury severity in single-vehicle crashes in California: A mixed-logit analysis of heterogeneity due to age and gender.” Accid. Anal. Prev. 50 (Jan): 1073–1081. https://doi.org/10.1016/j.aap.2012.08.011.
Kozak, K., J. Pohl, W. Birk, J. Greenberg, B. Artz, M. Blommer, L. Cathey and R. Curry. 2006. “Evaluation of lane departure warnings for drowsy drivers.” In Vol. 50 of Proc. Human Factors and Ergonomics Society Annual Meeting, 2400–2404. Los Angeles: SAGE.
Lam, L. T., R. Norton, M. Woodward, J. Connor, and S. Ameratunga. 2003. “Passenger carriage and car crash injury: A comparison between younger and older drivers.” Accid. Anal. Prev. 35 (6): 861–867. https://doi.org/10.1016/S0001-4575(02)00091-X.
Mannering, F. L., and C. R. Bhat. 2014. “Analytic methods in accident research: Methodological frontier and future directions.” Anal. Methods Accid. Res. 1: 1–22. https://doi.org/10.1016/j.amar.2013.09.001.
Mannering, F. L., V. Shankar, and C. R. Bhat. 2016. “Unobserved heterogeneity and the statistical analysis of highway accident data.” Anal. Methods Accid. Res. 11: 1–16. https://doi.org/10.1016/j.amar.2016.04.001.
McArthur, A., J. Kay, P. T. Savolainen, and T. J. Gates. 2013. “Effects of public rest areas on fatigue-related crashes.” Transp. Res. Rec. 2386 (1): 16–25. https://doi.org/10.3141/2386-03.
McCartt, A. T., J. W. Rohrbaugh, M. C. Hammer, and S. Z. Fuller. 2000. “Factors associated with falling asleep at the wheel among long-distance truck drivers.” Accid. Anal. Prev. 32 (4): 493–504. https://doi.org/10.1016/S0001-4575(99)00067-6.
McFadden, D. 1981. “Econometric models of probabilistic choice.” In A structural analysis of discrete data with econometric applications, edited by C. F. Manski and D. McFadden. Cambridge, MA: MIT Press.
Milton, J., V. Shankar, and F. Mannering. 2008. “Highway accident severities and the mixed logit model: An exploratory empirical analysis.” Accid. Anal. Prev. 40 (1): 260–266. https://doi.org/10.1016/j.aap.2007.06.006.
Morgan, A., and F. Mannering. 2011. “The effects of road-surface conditions, age, and gender on driver-injury severities.” Accid. Anal. Prev. 43 (5): 1852–1863. https://doi.org/10.1016/j.aap.2011.04.024.
NHTSA (National Highway Traffic Safety Administration). 2002. “National survey of distracted and drowsy driving attitudes and behaviors: 2002.” Accessed June 4, 2020. https://one.nhtsa.gov/people/injury/drowsy_driving1/survey-distractive03/drowsy.htm.
NHTSA (National Highway Traffic Safety Administration). 2017. “Drowsy driving 2015.” In Traffic safety facts. Washington, DC: USDOT.
Oviedo-Trespalacios, O., A. P. Afghari, and M. M. Haque. 2020. “A hierarchical Bayesian multivariate ordered model of distracted drivers’ decision to initiate risk-compensating behavior.” Anal. Methods Accid. Res. 26: 100121. https://doi.org/10.1016/j.amar.2020.100121.
Rau, P. 2005. “Drowsy driver detection and warning system for commercial vehicle drivers: Field operational test design, analysis, and progress.” In Proc., 19th Int. Conf. on Enhanced Safety of Vehicles. Washington, DC: National Highway Traffic Safety Administration.
Renski, H., A. J. Khattak, and F. M. Council. 1999. “Effect of speed limit increases on crash injury severity: Analysis of single-vehicle crashes on North Carolina interstate highways.” Trans. Res. Rec. 1665 (1): 100–108. https://doi.org/10.3141/1665-14.
Robertson, L. S. 1976. “Estimates of motor vehicle seat belt effectiveness and use: Implications for occupant crash protection.” Am. J. Public Health 66 (9): 859–864. https://doi.org/10.2105/AJPH.66.9.859.
Salmon, P. M., G. J. Read, and N. J. Stevens. 2016. “Who is in control of road safety? A STAMP control structure analysis of the road transport system in Queensland, Australia.” Accid. Anal. Prev. 96: 140–151. https://doi.org/10.1016/j.aap.2016.05.025.
Savolainen, P. T., F. L. Mannering, D. Lord, and M. A. Quddus. 2011. “The statistical analysis of highway crash-injury severities: A review and assessment of methodological alternatives.” Accid. Anal. Prev. 43 (5): 1666–1676. https://doi.org/10.1016/j.aap.2011.03.025.
Seraneeprakarn, P., S. Huang, V. Shankar, F. Mannering, N. Venkataraman, and J. Milton. 2017. “Occupant injury severities in hybrid-vehicle involved crashes: A random parameters approach with heterogeneity in means and variances.” Anal. Methods Accid. Res. 15: 41–55. https://doi.org/10.1016/j.amar.2017.05.003.
Shaheed, M. S., and K. Gkritza. 2014. “A latent class analysis of single-vehicle motorcycle crash severity outcomes.” Anal. Methods Accid. Res. 2: 30–38. https://doi.org/10.1016/j.amar.2014.03.002.
Shaheed, M. S. B., K. Gkritza, W. Zhang, and Z. Hans. 2013. “A mixed logit analysis of two-vehicle crash severities involving a motorcycle.” Accid. Anal. Prev. 61: 119–128. https://doi.org/10.1016/j.aap.2013.05.028.
Sherman, P. J., M. Elling and M. Brekke. 1996. The potential of steering wheel information to detect driver drowsiness and associated lane departure. Ames, IA: Midwest Transportation Center, Iowa State Univ.
Srinivasan, K. K. 2002. “Injury severity analysis with variable and correlated thresholds: Ordered mixed logit formulation.” Transp. Res. Rec. 1784 (1): 132–141. https://doi.org/10.3141/1784-17.
Stavrinos, D., J. L. Jones, A. A. Garner, R. Griffin, C. A. Franklin, D. Ball, S. C. Welburn, K. K. Ball, V. P. Sisiopiku, and P. R. Fine. 2013. “Impact of distracted driving on safety and traffic flow.” Accid. Anal. Prev. 61: 63–70. https://doi.org/10.1016/j.aap.2013.02.003.
Tavris, D. R., E. M. Kuhn, and P. M. Layde. 2001. “Age and gender patterns in motor vehicle crash injuries: Importance of type of crash and occupant role.” Accid. Anal. Prev. 33 (2): 167–172. https://doi.org/10.1016/S0001-4575(00)00027-0.
Train, K. 1999. Halton sequences for mixed logit. Working Paper. Berkley, CA: Univ. of California, Berkley.
Washington, S. P., M. G. Karlaftis, and F. L. Mannering. 2011. Statistical and econometric methods for transportation data analysis. 2nd ed. New York: Chapman & Hall/CRC.
Xiong, Y., and F. L. Mannering. 2013. “The heterogeneous effects of guardian supervision on adolescent driver- injury severities: A finite-mixture random-parameters approach.” Trans. Res. Part B 49 (1): 39–54. https://doi.org/10.1016/j.trb.2013.01.002.
Yasmin, S., and N. Eluru. 2013. “Evaluating alternate discrete outcome frameworks for modeling crash injury severity.” Accid. Anal. Prev. 59: 506–521. https://doi.org/10.1016/j.aap.2013.06.040.
Yasmin, S., N. Eluru, C. R. Bhat, and R. Tay. 2014. “A latent segmentation based generalized ordered logit model to examine factors influencing driver injury severity.” Anal. Methods Accid. Res. 1: 23–38. https://doi.org/10.1016/j.aap.2013.06.040.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 10 • October 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Jun 13, 2020
Accepted: Apr 20, 2021
Published online: Aug 3, 2021
Published in print: Oct 1, 2021
Discussion open until: Jan 3, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Jian-jun Wang, Wen-ding ZHAO, Sai Wang, Traffic influence analysis of the area adjacent accident point on freeway in connected environment, International Conference on Smart Transportation and City Engineering (STCE 2023), 10.1117/12.3023978, (23), (2024).
- Rani Rahmadiyani, Ari widyanti, Prevalence of drowsy driving and modeling its intention: An Indonesian case study, Transportation Research Interdisciplinary Perspectives, 10.1016/j.trip.2023.100824, 19, (100824), (2023).
- Yun Xiao, Haoyun Liu, Zijun Liang, An Analysis of the Influential Factors of Violations in Urban-Rural Passenger Transport Drivers, Journal of Advanced Transportation, 10.1155/2022/1652923, 2022, (1-10), (2022).
- Jiahua Gan, Meng Zhang, Yun Xiao, Multidimensional Data Analysis Based on LOGIT Model, Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 10.1007/978-981-19-2456-9_32, (303-315), (2022).