Investigating the relation between instantaneous driving decisions and safety critical events in naturalistic driving environment
Tài liệu tham khảo
Ahmed, 2018, Effects of truck traffic on crash injury severity on rural highways in Wyoming using Bayesian binary logit models, Accid. Anal. Prev., 117, 106, 10.1016/j.aap.2018.04.011
Ali, 2019, Detection of critical safety events on freeways in clear and rainy weather using SHRP2 naturalistic driving data: parametric and non-parametric techniques, Saf. Sci., 119, 141, 10.1016/j.ssci.2019.01.007
Arvin, 2019, The role of pre-crash driving instability in contributing to crash intensity using naturalistic driving data, Accid. Anal. Prev., 132
Asirt, 2016
Behnood, 2017, The eff ;ects of drug and alcohol consumption on driver injury severities in single-vehicle crashes, Traffic Inj. Prev., 18, 10.1080/15389588.2016.1262540
Ben-Akiva, 1985
Boyle, 2008, Driver performance in the moments surrounding a microsleep, Transp. Res. Part F, 11
Campbell, 2012, The SHRP 2 naturalistic driving study: addressing driver performance and behavior in trafc safety, TR News, 282
Chatterjee, 2015
Fitch, 2015, Drivers’ visual behavior when using handheld and hands-free cell phones, J. Safety Res., 105
Gaweesh, 2019, Evaluating the safety effectiveness of a weather- based variable speed limit for a rural mountainous freeway in Wyoming variable speed limit for a rural mountainous freeway, J. Transp. Saf. Secur., 0, 1
Ghasemzadeh, 2017, Drivers’ lane-keeping ability in heavy rain: preliminary investigation using SHRP 2 naturalistic driving study data, Transp. Res. Rec., 2663, 10.3141/2663-13
Ghasemzadeh, 2018, Utilizing naturalistic driving data for in-depth analysis of driver lane-keeping behavior in rain: non-parametric MARS and parametric logistic regression modeling approaches, Transp. Res. Part C Emerg. Technol., 90, 10.1016/j.trc.2018.03.018
Ghasemzadeh, 2018, Parametric ordinal logistic regression and non-parametric decision tree approaches for assessing the impact of weather conditions on driver speed selection using naturalistic driving data, Transp. Res. Rec., 2672, 2, 10.1177/0361198118758035
Greene, 2008
Haghighi, 2018, Impact of roadway geometric features on crash severity on rural two-lane highways, Accid. Anal. Prev., 111
Halton, 1960, On the efficiency of evaluating certain quasi-random sequences of points in evaluating multi-dimensional integrals, Numer. Math., 2, 84, 10.1007/BF01386213
Hankey, 2016
Hassan, 2017, Investigation of drivers’ behavior towards speeds using crash data and self-reported questionnaire, Accid. Anal. Prev., 98
Henclewood, 2014
Hu, 2010, Median barrier crash severity: some new insights, Accid. Anal. Prev., 42, 1697, 10.1016/j.aap.2010.04.009
Jovanis, 2011, Analysis of naturalistic driving event data: omitted-variable bias and multilevel modeling approaches, Transp. Res. Rec., 2236
Khattak, 2020, A Bayesian modeling framework for crash severity effects of active traffic management systems, Accid. Anal. Prev., 145, 10.1016/j.aap.2020.105544
Khattak, 2017, Estimating safety effects of adaptive signal control technology using the empirical bayes method, J. Safety Res.
Khattak, 2017, Using new mode choice model nesting structures to address emerging policy questions: a case study of the Pittsburgh Central Business District, Sustainability, 10.3390/su9112120
Khattak, 2018, Evaluating the impact of adaptive signal control technology on driver stress and behavior using real-world experimental data, Transp. Res. Part F, 58, 133, 10.1016/j.trf.2018.06.006
Khattak, 2019, Operational performance evaluation of adaptive traffic control systems: a Bayesian modeling approach using real-world GPS and private sector PROBE data, J. Intell. Transp. Syst.
Khattak, 2019, Crash severity effects of adaptive signal control technology: An empirical assessment with insights from Pennsylvania and Virginia, Accid. Anal. Prev., 154, 151, 10.1016/j.aap.2019.01.008
Khattak, 2020, Exploratory investigation of disengagements and crashes in autonomous vehicles under mixed traffic: an endogenous switching regime framework, IEEE Trans. Intell. Transp. Syst., 10.1109/TITS.2020.3003527
Khattak, 2020, Cooperative lane control application for fully connected and automated vehicles at multilane freeways, Transp. Res. Part C, 111, 294, 10.1016/j.trc.2019.11.007
Klauer, 2006
Kluger, 2016, Identification of safety-critical events using kinematic vehicle data and the discrete fourier transform, Accid. Anal. Prev., 96, 162, 10.1016/j.aap.2016.08.006
Lefèvre, 2014, A survey on motion prediction and risk assessment for intelligent vehicles, ROBOMECH J., 10.1186/s40648-014-0001-z
Lento, 2007, Investment information content in Bollinger Bands?, Appl. Financ. Econ. Lett., 3, 4, 10.1080/17446540701206576
Mannering, 2009, An empirical analysis of driver perceptions of the relationship between speed limits and safety, Transp. Res. Part F, 12
McFadden, 1981, Econometric models of probabilistic choice
Milton, 2008, Highway accident severities and the mixed logit model: an exploratory empirical analysis, Accid. Anal. Prev., 40, 260, 10.1016/j.aap.2007.06.006
Mitchell, 2014, Work and non-work-related vehicle crashes: the contribution of risky driving practices, Saf. Sci., 68
Naik, 2016, Weather impacts on single-vehicle truck crash injury severity, J. Safety Res., 58
NHTSA, 2015
Osman, 2019
Perez, 2017, Performance of basic kinematic thresholds in the identification of crash and near-crash events within naturalistic driving data, Accid. Anal. Prev., 103, 10, 10.1016/j.aap.2017.03.005
Rakauskas, 2004, Effects of naturalistic cell phone conversations on driving performance, J. Safety Res., 35, 4, 10.1016/j.jsr.2004.06.003
Richard, 2020, Using SHRP2 naturalistic driving data to examine driver speeding behavior, J. Safety Res., 10.1016/j.jsr.2020.03.008
Scott-Parker, 2017, Young driver risky behaviour and predictors of crash risk in Australia, New Zealand and Colombia: same but diff ;erent?, Accid. Anal. Prev., 99
Smorti, 2014, Sensation seeking, parental bond, and risky driving in adolescence: some relationships, matter more to girls than boys, Saf. Sci., 70
Train, 2003
TRB, 2013
Wali, 2020, Harnessing ambient sensing & naturalistic driving systems to understand links between driving volatility and crash propensity in school zones – a generalized hierarchical mixed logit framework, Transp. Res. Part C, 114, 10.1016/j.trc.2020.01.028
Wali, 2018, How is driving volatility related to intersection safety? A Bayesian heterogeneity-based analysis of instrumented vehicles data, Transp. Res. Part C, 92, 504, 10.1016/j.trc.2018.05.017
Wali, 2019, Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events—Concept of event-based driving volatility, Accid. Anal. Prev., 132
Wang, 2015, What is the level of volatility in instantaneous driving decisions?, Transp. Res. Part C, 58, 413, 10.1016/j.trc.2014.12.014
Washington, 2011
Weng, 2012, Eff ;ects of environment, vehicle and driver characteristics on risky driving behavior at work zones, Saf. Sci., 50
Xie, 2018, Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects, Traffic Inj. Prev., 19, 2, 10.1080/15389588.2017.1371302
Yan, 2008, Validating a driving simulator using surrogate safety measures, Accid. Anal. Prev., 40
Ye, 2017, Detection of driver engagement in secondary tasks from observed naturalistic driving behavior, Accid. Anal. Prev., 106, 385, 10.1016/j.aap.2017.07.010