References
- Atwood, J., Guo, F., Fitch, G., & Dingus, T. A. (2018). The driver-level crash risk associated with daily cellphone use and cellphone use while driving. Accident Analysis & Prevention, 119, 149–154. doi:https://doi.org/10.1016/j.aap.2018.07.007
- Beanland, V., Fitzharris, M., Young, K. L., & Lenné, M. G. (2013). Driver inattention and driver distraction in serious casualty crashes: Data from the Australian National Crash In-depth Study. Accident Analysis & Prevention, 54, 99–107. doi:https://doi.org/10.1016/j.aap.2012.12.043
- Blows, S., Ameratunga, S., Ivers, R. Q., Lo, S. K., & Norton, R. (2005). Risky driving habits and motor vehicle driver injury. Accident Analysis & Prevention, 37(4), 619–624. doi:https://doi.org/10.1016/j.aap.2005.03.003
- Bunn, T. L., Slavova, S., Struttmann, T. W., & Browning, S. R. (2005). Sleepiness/fatigue and distraction/inattention as factors for fatal versus nonfatal commercial motor vehicle driver injuries. Accident Analysis & Prevention, 37(5), 862–869. doi:https://doi.org/10.1016/j.aap.2005.04.004
- Carney, C., Harland, K. K., & McGehee, D. V. (2016). Using event-triggered naturalistic data to examine the prevalence of teen driver distractions in rear-end crashes. Journal of Safety Research, 57, 47–52. doi:https://doi.org/10.1016/j.jsr.2016.03.010
- Carney, C., Harland, K. K., & McGehee, D. V. (2018). Examining teen driver crashes and the prevalence of distraction: Recent trends, 2007–2015. Journal of Safety Research, 64, 21–27. doi:https://doi.org/10.1016/j.jsr.2017.12.014
- Charlton, S. G. (2009). Driving while conversing: Cell phones that distract and passengers who react. Accident; Analysis and Prevention, 41(1), 160–173. doi:https://doi.org/10.1016/j.aap.2008.10.006
- Choudhary, P., & Velaga, N. R. (2017). Modelling driver distraction effects due to mobile phone use on reaction time. Transportation Research Part C: Emerging Technologies, 77, 351–365. doi:https://doi.org/10.1016/j.trc.2017.02.007
- Chu, H. C. (2014). Assessing factors causing severe injuries in crashes of high-deck buses in long-distance driving on freeways. Accident; Analysis and Prevention, 62, 130–136. doi:https://doi.org/10.1016/j.aap.2013.09.016
- Cooper, J. M., Vladisavljevic, I., Medeiros-Ward, N., Martin, P. T., & Strayer, D. L. (2009). An investigation of driver distraction near the tipping point of traffic flow stability. Human Factors, 51(2), 261–268. doi:https://doi.org/10.1177/0018720809337503
- D’Addario, P., & Donmez, B. (2019). The effect of cognitive distraction on perception-response time to unexpected abrupt and gradually onset roadway hazards. Accident Analysis & Prevention, 127, 177–185. doi:https://doi.org/10.1016/j.aap.2019.03.003
- De Pauw, E., Daniels, S., Thierie, M., & Brijs, T. (2014). Safety effects of reducing the speed limit from 90 km/h to 70 km/h. Accident Analysis & Prevention, 62, 426–431. doi:https://doi.org/10.1016/j.aap.2013.05.003
- Donmez, B., & Liu, Z. (2015). Associations of distraction involvement and age with driver injury severities. Journal of Safety Research, 52, 23–28. doi:https://doi.org/10.1016/j.jsr.2014.12.001
- Fitch, G. M., Soccolich, S. A., Guo, F., McClafferty, J., Fang, Y., Olson, R. L., Perez, M. A., Hanowski, R. J., Hankey, J. M., & Dingus, T. A. (2013). The impact of hand-held and hands-free cell phone use on driving performance and safety-critical event risk (No. DOT HS 811 757). National Highway Traffic SafetyAdministration, Washington, DC, United States.
- Gao, J., & Davis, G. A. (2017). Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation. Journal of Safety Research, 63, 195–204. doi:https://doi.org/10.1016/j.jsr.2017.10.012
- Greenberg, J., Tijerina, L., Curry, R., Artz, B., Cathey, L., Kochhar, D., Kozak, K., Blommer, M., & Grant, P. (2003). Driver distraction: Evaluation with event detection paradigm. Transportation Research Record: Journal of the Transportation Research Board, 1843(1), 1–9. doi:https://doi.org/10.3141/1843-01
- Guo, F., Klauer, S. G., Fang, Y., Hankey, J. M., Antin, J. F., Perez, M. A., Lee, S. E., & Dingus, T. A. (2017). The effects of age on crash risk associated with driver distraction. International Journal of Epidemiology, 46(1), 258–265. doi: https://doi.org/10.1093/ije/dyw234c
- Hanley, P. F., & Sikka, N. (2012). Bias caused by self-reporting distraction and its impact on crash estimates. Accident; Analysis and Prevention, 49, 360–365. doi:https://doi.org/10.1016/j.aap.2012.02.008
- Hasan, A. S., Orvin, M. M., & Jalayer, M. (2021). Analysis of distracted driving crashes in New Jersey using mixed logit model (No. TRBAM-21-02932). Transportation Research Board 100th Annual Meeting, Washington DC, United States.
- Ho, D., Imai, K., King, G., & Stuart, E. A. (2011). Matchit: Nonparametric preprocessing for parametric causal inference. Journal of Statal Software, 42(8), 1–28
- Hu, D., Feng, X., Zhao, X., Li, H., Ma, J., & Fu, Q. (2020). Impact of HMI on driver’s distraction on a freeway under heavy foggy condition based on visual characteristics. Journal of Transportation Safety & Security, (published online).doi:https://doi.org/10.1080/19439962.2020.1853641
- Intini, P., Berloco, N., Colonna, P., Ranieri, V., & Ryeng, E. (2018). Exploring the relationships between drivers’ familiarity and two-lane rural road accidents. A multi-level study. Accident Analysis & Prevention, 111, 280–296. doi:https://doi.org/10.1016/j.aap.2017.11.013
- Jiang, X., Lyles, R. W., & Guo, R. (2014). A comprehensive review on the quasi-induced exposure technique. Accident; Analysis and Prevention, 65, 36–46. doi:https://doi.org/10.1016/j.aap.2013.12.008
- Klauer, S. G., Guo, F., Simons-Morton, B. G., Ouimet, M. C., Lee, S. E., & Dingus, T. A. (2014). The prevalence and risk of secondary task engagement with novice drivers: Distracted driving and risk of road crashes among novice and experienced drivers. New England Journal of Medicine, 370(1), 54–59. doi:https://doi.org/10.1056/NEJMsa1204142
- Klauer, S. G., Dingus, T. A., Neale, V. L., Sudweeks, J. D., & Ramsey, D. J. (2006). The impact of driver inattention on near-crash/crash risk: An analysis using the 100-car naturalistic driving study data. Report No. DOT HS 810 594, National Highway Traffic Safety Administration.
- Laberge, J., Scialfa, C., White, C., & Caird, J. (2004). Effects of passenger and cellular phone conversations on driver distraction. Transportation Research Record: Journal of the Transportation Research Board, 1899(1), 109–116. doi:https://doi.org/10.3141/1899-15
- Le, A. S., Suzuki, T., & Aoki, H. (2020). Evaluating driver cognitive distraction by eye tracking: From simulator to driving. Transportation Research Interdisciplinary Perspectives, 4, 100087. doi:https://doi.org/10.1016/j.trip.2019.100087
- Lee, J. D., Young, K. L., & Regan, M. A. (2008). Defining driver distraction. Driver Distraction: Theory, Effects, and Mitigation, 13(4), 31–40.
- Li, W., Gkritza, K., & Albrecht, C. (2014). The culture of distracted driving: Evidence from a public opinion survey in Iowa. Transportation Research Part F: Traffic Psychology and Behaviour, 26, 337–347. doi:https://doi.org/10.1016/j.trf.2014.01.002
- Li, H., Graham, D. J., & Majumdar, A. (2013). The impacts of speed cameras on road accidents: An application of propensity score matching methods. Accident; Analysis and Prevention, 60, 148–157. doi:https://doi.org/10.1016/j.aap.2013.08.003
- Lu, D., Guo, F., & Li, F. (2020). Evaluating the causal effects of cellphone distraction on crash risk using propensity score methods. Accident; Analysis and Prevention, 143, 105579. doi:https://doi.org/10.1016/j.aap.2020.105579
- Lym, Y., & Chen, Z. (2020). Does space influence on the frequency and severity of the distraction-affected vehicle crashes? An empirical evidence from the Central Ohio. Accident Analysis & Prevention, 144, 105606. doi:https://doi.org/10.1016/j.aap.2020.105606
- Ma, Y., Gu, G., Yin, B., Qi, S., Chen, K., & Chan, C. (2020). Support vector machines for the identification of real-time driving distraction using in-vehicle information systems. Journal of Transportation Safety & Security, (published online).doi:https://doi.org/10.1080/19439962.2020.1774019
- Mahmoudzadeh, A., Razi-Ardakani, H., & Kermanshah, M. (2019). Studying crash avoidance maneuvers prior to an impact considering different types of driver’s distractions. Transportation Research Procedia, 37, 203–210. doi:https://doi.org/10.1016/j.trpro.2018.12.184
- National Highway Traffic Safety Administration. (2015). Traffic safety facts: Distracted driving 2013. Washington, DC, United States: National Center for Statistics and Analysis, US Department of Transportation.
- Neyens, D. M., & Boyle, L. N. (2007). The effect of distractions on the crash types of teenage drivers. Accident Analysis & Prevention, 39(1), 206–212. doi:https://doi.org/10.1016/j.aap.2006.07.004
- Neyens, D. M., & Boyle, L. N. (2008). The influence of driver distraction on the severity of injuries sustained by teenage drivers and their passengers. Accident Analysis & Prevention, 40(1), 254–259. doi:https://doi.org/10.1016/j.aap.2007.06.005
- Penmetsa, P., Pulugurtha, S. S., & Duddu, V. R. (2017). Examining injury severity of not-at-fault drivers in two-vehicle crashes. Transportation Research Record: Journal of the Transportation Research Board, 2659(1), 164–173. doi:https://doi.org/10.3141/2659-18
- Precht, L., Keinath, A., & Krems, J. F. (2017). Identifying the main factors contributing to driving errors and traffic violations–Results from naturalistic driving data. Transportation Research Part F: Traffic Psychology and Behaviour, 49, 49–92. doi:https://doi.org/10.1016/j.trf.2017.06.002
- Qin, L., Li, Z. R., Chen, Z., Bill, M. A., & Noyce, D. A. (2019). Understanding driver distractions in fatal crashes: An exploratory empirical analysis. Journal of Safety Research, 69, 23–31. doi:https://doi.org/10.1016/j.jsr.2019.01.004
- Sasidharan, L., & Donnell, E. T. (2013). Application of propensity scores and potential outcomes to estimate effectiveness of traffic safety countermeasures: Exploratory analysis using intersection lighting data. Accident Analysis & Prevention, 50, 539–553. doi:https://doi.org/10.1016/j.aap.2012.05.036
- Sheykhfard, A., & Haghighi, F. (2020). Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran. Journal of Safety Research, 72, 1–8. doi:https://doi.org/10.1016/j.jsr.2019.11.002
- Stevens, A., & Minton, R. (2001). In-vehicle distraction and fatal accidents in England and Wales. Accident Analysis & Prevention, 33(4), 539–545. doi:https://doi.org/10.1016/s0001-4575(00)00068-3
- Stimpson, J. P., Wilson, F. A., & Muelleman, R. L. (2013). Fatalities of pedestrians, bicycle riders, and motorists due to distracted driving motor vehicle crashes in the US, 2005–2010. Public Health Reports, 128(6), 436–442. doi:https://doi.org/10.1177/003335491312800603
- Sundfør, H. B., Sagberg, F., & Høye, A. (2019). Inattention and distraction in fatal road crashes–results from in-depth crash investigations in Norway. Accident Analysis & Prevention, 125, 152–157. doi:https://doi.org/10.1016/j.aap.2019.02.004
- Velmurugan, S., Padma, S., Madhu, E., Anuradha, S., & Gangopadhyay, S. (2013). A study of factors influencing the severity of road crashes involving drunk drivers and non drunk drivers. Research in Transportation Economics, 38(1), 78–83. doi:https://doi.org/10.1016/j.retrec.2012.05.015
- Wang, C., Li, Z., Fu, R., Guo, Y., & Yuan, W. (2019). What is the difference in driver’s lateral control ability during naturalistic distracted driving and normal driving? A case study on a real highway. Accident Analysis & Prevention, 125, 98–105. doi:https://doi.org/10.1016/j.aap.2019.01.030
- Wijayaratna, K. P., Cunningham, M. L., Regan, M. A., Jian, S., Chand, S., & Dixit, V. V. (2019). Mobile phone conversation distraction: Understanding differences in impact between simulator and naturalistic driving studies. Accident Analysis & Prevention, 129, 108–118. doi:https://doi.org/10.1016/j.aap.2019.04.017
- Wood, J., & Donnell, E. T. (2016). Safety evaluation of continuous green T intersections: A propensity scores-genetic matching-potential outcomes approach. Accident Analysis & Prevention, 93, 1–13. doi:https://doi.org/10.1016/j.aap.2016.04.015
- Wu, J., & Xu, H. (2018). The influence of road familiarity on distracted driving activities and driving operation using naturalistic driving study data. Transportation Research Part F: Traffic Psychology and Behaviour, 52, 75–85. doi:https://doi.org/10.1016/j.trf.2017.11.018
- Zhang, Y., Fu, C., & Cheng, S. (2015). Exploring driver injury severity at intersection: An ordered probit analysis. Advances in Mechanical Engineering, 7(2), 567124. doi:https://doi.org/10.1155/2014/567124