Comparison of contributing factors in hit-and-run crashes with distracted and non-distracted drivers
作者： Arash M. Roshandeh , Bei Zhou , Ali Behnood
DOI: 10.1016/J.TRF.2015.12.016
关键词: Applied psychology 、 Occupational safety and health 、 Injury prevention 、 Human factors and ergonomics 、 Computer security 、 Population 、 Poison control 、 Distraction 、 Logistic regression 、 Engineering 、 Crash
摘要: Among different types of crashes, hit-and-run is driver’s failure to stop after a vehicle crash. There are many accidents where drivers could actually be at fault or totally innocent, and leaving the scene would turn an innocent driver into criminal. The current paper aims contribute literature by exploring association variables pertaining condition infrastructure, environment, driver, population area, crash severity type with crashes. analysis performed for two data sets: (i) crashes was distracted; (ii) not distracted. Hit-and-run corresponding factors police-reported within Cook County, Illinois, occurring between 2004 2012. A logistic regression model assessed 43 16 categories statistically significant without distraction. For both distraction statuses, 17 were associated increased probability 10 decreased probability. Additionally, it found that on curve level hillcrest road alignment likelihood when distracted Variables related vary depending status. When comparing flee crash, non-distracted 27% less likely do so compared drivers.
sci-hub.se 参考文章(18)
Matthew G. Karlaftis, Fred L. Mannering, Simon P. Washington, Statistical and econometric methods for transportation data analysis ,(2003)
Lina Kattan, Richard Tay, Huafei Sun, Logistic Model of Hit and Run Crashes in Calgary Canadian Journal of Transportation. ,vol. 4, ,(2010)
Carol Holland, Versha Rathod, Influence of personal mobile phone ringing and usual intention to answer on driver error. Accident Analysis & Prevention. ,vol. 50, pp. 793- 800 ,(2013) , 10.1016/J.AAP.2012.07.004
Ali Behnood, Arash M. Roshandeh, Fred L. Mannering, Latent Class Analysis of the Effects of Age, Gender, and Alcohol Consumption on Driver-Injury Severities Analytic Methods in Accident Research. ,vol. 3, pp. 56- 91 ,(2014) , 10.1016/J.AMAR.2014.10.001
Richard Tay, Shakil Mohammad Rifaat, Hoong Chor Chin, A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes. Accident Analysis & Prevention. ,vol. 40, pp. 1330- 1336 ,(2008) , 10.1016/J.AAP.2008.02.003
Louise P. Waddell, Karl K.K. Wiener, What’s driving illegal mobile phone use? Psychosocial influences on drivers’ intentions to use hand-held mobile phones Transportation Research Part F-traffic Psychology and Behaviour. ,vol. 22, pp. 1- 11 ,(2014) , 10.1016/J.TRF.2013.10.008
Guangnan Zhang, Guangzhong Li, Tiancheng Cai, David M Bishai, Changxu Wu, Zeyi Chan, None, Factors contributing to hit-and-run crashes in China Transportation Research Part F-traffic Psychology and Behaviour. ,vol. 23, pp. 113- 124 ,(2014) , 10.1016/J.TRF.2013.12.009
Sonia Amado, Pınar Ulupınar, The effects of conversation on attention and peripheral detection: Is talking with a passenger and talking on the cell phone different? Transportation Research Part F-traffic Psychology and Behaviour. ,vol. 8, pp. 383- 395 ,(2005) , 10.1016/J.TRF.2005.05.001
Richard Tay, Upal Barua, Lina Kattan, Factors contributing to hit-and-run in fatal crashes Accident Analysis & Prevention. ,vol. 41, pp. 227- 233 ,(2009) , 10.1016/J.AAP.2008.11.002
Frederik Platten, Natasa Milicic, Maximilian Schwalm, Josef Krems, Using an infotainment system while driving: a continuous analysis of behavior adaptations Transportation Research Part F-traffic Psychology and Behaviour. ,vol. 21, pp. 103- 112 ,(2013) , 10.1016/J.TRF.2013.09.012