Predicting Future Driving Risk of Crash-Involved Drivers Based on a Systematic Machine Learning Framework
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Lin Liu | Chengcheng Xu | Chen Wang | Weitao Lv | Cheng-yuan Xu | Chen Wang | Lin Liu | W. Lv
[1] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[2] Xun Zhang,et al. Analyzing fault and severity in pedestrian-motor vehicle accidents in China. , 2014, Accident; analysis and prevention.
[3] Feng Chen,et al. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data. , 2018, Journal of safety research.
[4] Guangnan Zhang,et al. Risk factors associated with traffic violations and accident severity in China. , 2013, Accident; analysis and prevention.
[5] Randall Guensler,et al. Relationships between Crash Involvement and Temporal-Spatial Driving Behavior Activity Patterns , 2007 .
[6] Mehdi Jabbari Nooghabi,et al. Validation of the influencing factors associated with traffic violations and crashes on freeways of developing countries: A case study of Iran. , 2018, Accident; analysis and prevention.
[7] Yasushi Nishida. Analyzing accidents and developing elderly driver-targeted measures based on accident and violation records , 2015 .
[8] Xiaoduan Sun,et al. Estimating likelihood of future crashes for crash-prone drivers , 2015 .
[9] Suren Chen,et al. Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models , 2016, International journal of environmental research and public health.
[10] Chengcheng Xu,et al. Modeling faults among e-bike-related fatal crashes in China , 2017, Traffic injury prevention.
[11] Abolfazl Mohammadzadeh Moghaddam,et al. Introducing a risk estimation index for drivers: A case of Iran , 2014 .
[12] Srinivas S Pulugurtha,et al. Methods to rank traffic rule violations resulting in crashes for allocation of funds. , 2017, Accident; analysis and prevention.
[13] Muhammad Zahid,et al. Predicting Risky and Aggressive Driving Behavior among Taxi Drivers: Do Spatio-Temporal Attributes Matter? , 2020, International journal of environmental research and public health.
[14] Yao Danya,et al. Driving behavior differences between crash-involved and crash-not-involved drivers using urban traffic surveillance data , 2016, 2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI).
[15] Xingda Qu,et al. The role of personality traits and driving experience in self-reported risky driving behaviors and accident risk among Chinese drivers. , 2017, Accident; analysis and prevention.
[16] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[17] Michael A Gebers. STRATEGIES FOR ESTIMATING DRIVER ACCIDENT RISK IN RELATION TO CALIFORNIA'S NEGLIGENT-OPERATOR POINT SYSTEM , 1999 .
[18] M. Greenwood,et al. An Inquiry into the Nature of Frequency Distributions Representative of Multiple Happenings with Particular Reference to the Occurrence of Multiple Attacks of Disease or of Repeated Accidents , 1920 .
[19] Ronald S Coppin,et al. THE DISTRIBUTION AND PREDICTION OF DRIVER ACCIDENT FREQUENCIES , 1971 .
[20] Pierre Joly,et al. Previous convictions or accidents and the risk of subsequent accidents of older drivers. , 2002, Accident; analysis and prevention.
[21] Gregory W. Corder,et al. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach , 2009 .
[22] Nikiforos Stamatiadis,et al. Evaluation Of Retesting in Kentucky's Driver License Process , 1999 .
[23] Klaus Nordhausen,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman , 2009 .
[24] Ricardo D. Blasco,et al. Accident probability after accident occurrence , 2003 .
[25] Changxi Ma,et al. The Impact of Aggressive Driving Behavior on Driver-Injury Severity at Highway-Rail Grade Crossings Accidents , 2018, Journal of Advanced Transportation.
[26] Chengcheng Xu,et al. Association rule analysis of factors contributing to extraordinarily severe traffic crashes in China. , 2018, Journal of safety research.
[27] Gustavo E. A. P. A. Batista,et al. A study of the behavior of several methods for balancing machine learning training data , 2004, SKDD.
[28] Nikiforos Stamatiadis,et al. Crash involvement of drivers with multiple crashes. , 2006, Accident; analysis and prevention.
[29] Sergio A. Useche,et al. Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers. , 2017, Accident; analysis and prevention.
[30] Keli A Braitman,et al. Effects of Age and Experience on Young Driver Crashes: Review of Recent Literature , 2009, Traffic injury prevention.
[31] Mark Goadrich,et al. The relationship between Precision-Recall and ROC curves , 2006, ICML.
[32] Randall Guensler,et al. Differences in observed speed patterns between crash-involved and crash-not-involved drivers: Application of in-vehicle monitoring technology , 2011 .
[33] Qiang Meng,et al. Remote park-and-ride network equilibrium model and its applications , 2018 .
[34] Sukhvir S Brar. Estimating the over-involvement of suspended, revoked, and unlicensed drivers as at-fault drivers in California fatal crashes. , 2014, Journal of safety research.
[35] Dae-Hwan Kim,et al. Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model , 2016, Traffic injury prevention.
[36] Changxi Ma,et al. Developing a Coordinated Signal Control System for Urban Ring Road Under the Vehicle-Infrastructure Connected Environment , 2018, IEEE Access.
[37] Patricia Delhomme,et al. Evaluating individual risk proneness with vehicle dynamics and self-report data - toward the efficient detection of At-risk drivers. , 2019, Accident; analysis and prevention.
[38] Raymond C Peck,et al. Using traffic conviction correlates to identify high accident-risk drivers. , 2003, Accident; analysis and prevention.
[39] Lisa Buckley,et al. Adolescent involvement in anti-social and delinquent behaviours: predicting future injury risk. , 2012, Accident; analysis and prevention.
[40] Zhiyuan Liu,et al. Willingness to board: A novel concept for modeling queuing up passengers , 2016 .