279
Views
6
CrossRef citations to date
0
Altmetric
Original Articles

Applying Bayesian data mining to measure the effect of vehicular defects on crash severity

ORCID Icon, &

References

  • American Association of State Highway and Transportation Officials (AASHTO). (2010). Highway safety manual (1st ed.)., Washington, DC: American Association of State Highway and Transportation Officials.
  • Al-Ghaweel, I., Mursi, S. A., Jack, J. P., & Joel, I. (2009). Factors affecting road traffic accidents in Benghazi. Journal of Family & Community Medicine, 16(1), 7–9.
  • Akloweg, Y., Hayshi, Y., & Kato, H. (2011). The effect of used cars on African road traffic accidents: A case study of Addis Ababa, Ethiopia. International Journal of Urban Sciences, 15(1), 61–69. doi:10.1080/12265934.2011.580153
  • Baireddy, R., Zhou, H., & Jalayer, M. (2018). Multiple correspondence analysis of pedestrian crashes in rural Illinois. Transportation Research Record: Journal of the Transportation Research Board, 2672(38), 116–127. doi:10.1177/0361198118777088
  • Barry, S., Ginpil, S., & O’Neill, T. J. (1999). The effectiveness of air bags. Accident Analysis and Prevention, 31(6), 781–787.
  • Conroy, C., Tominaga, G. T., Erwin, S., Pacyna, S., Velky, T., Kennedy, F., … Coimbra, R. (2008). The influence of vehicle damage on injury severity of drivers in head-on motor vehicle crashes. Accident Analysis & Prevention, 40(4), 1589–1594. doi:10.1016/j.aap.2008.04.006
  • Cuerden, R., Edwards, M., & Pittman, M. (2011). Effect of vehicle defects in road accidents. Report: PPR565, Transport Research Laboratory (TRL), UK.
  • Das, S., & Sun, X. (2015). Factor association with multiple correspondence analysis in vehicle–pedestrian crashes. Transportation Research Record: Journal of the Transportation Research Board, 2519(1), 95–103. doi:10.3141/2519-11
  • Das, S., Sun, X., Wang, F., & Leboeuf, C. (2015). Estimating likelihood of future crashes for crash-prone drivers. Journal of Traffic and Transportation Engineering (English Edition), 2(3), 145–157. doi:10.1016/j.jtte.2015.03.003
  • Das, S., & Sun, X. (2016). Association knowledge for fatal run-off-road crashes by multiple correspondence analysis. IATSS Research, 39(2), 146–155. doi:10.1016/j.iatssr.2015.07.001
  • Das, S., Brimley, B. K., Lindheimer, T., & Pant, A. (2017). Safety impacts of reduced visibility in inclement weather. Final Report ATLAS-2017-19, University of Michigan, MI.
  • Das, S., Minjares-Kyle, L., Avelar, R. E., Dixon, K. K., & Bommanayakanahalli, B. (2017). Improper passing related crashes on rural roadways: Using association rules negative binomial miner. Presented at the Transportation Research Board 96th Annual Meeting: Transportation Research Board.
  • Das, S., Dutta, A., Jalayer, M., Bibeka, A., & Wu, L. (2018). Factors influencing the patterns of wrong way driving crashes on freeway exit ramps and median crossovers: Exploration using ‘Eclat’ association rules to promote safety. International Journal of Transportation Science and Technology, 7(2), 114–123. doi:10.1016/j.ijtst.2018.02.001
  • Das, S., Dutta, A., Avelar, R., Dixon, K., Sun, X., & Jalayer, M. (2018). Supervised association rules mining on pedestrian crashes in urban areas: Identifying patterns for appropriate countermeasures. International Journal of Urban Sciences, 23(1), 1–19. doi:10.1080/12265934.2018.1431146
  • Das, S., Mudgal, A., Dutta, A., & Geedipally, S. (2018). Vehicle consumer complaint reports involving severe incidents: Mining large contingency tables. Transportation Research Record: Journal of the Transportation Research Board, 2672(32), 72. doi:10.1177/0361198118788464
  • Das, S., Avelar, R., Dixon, K., & Sun, X. (2018). Investigation on the wrong way driving crash patterns using multiple correspondence analysis. Accident Analysis & Prevention, 111, 43–55. doi:10.1016/j.aap.2017.11.016
  • Das, S., Kong, X., & Tsapakis, I. (2019). Hit and run crash analysis using association rules mining. Journal of Transportation Safety & Security. doi:10.1080/19439962.2019.1611682
  • Das, S., Dutta, A., & Sun, X. (2019). Patterns of rainy weather crashes: Applying rules mining. Journal of Transportation Safety & Security. doi:10.1080/19439962.2019.1572681
  • DEKRA Automobil GmbH. Road Safety Report (2015). A future based on experience. DEKRA, Stuttgart, Germany. http://www.dekra-vision-zero.com/downloads/road_safety_report_2015.pdf.
  • DuMouchel, W. (1999). Bayesian data mining in large frequency tables, with an application to the FDA spontaneous reporting system. The American Statistician, 53(3), 177–190. doi:10.2307/2686093
  • Factor, R., Yair, G., & Mahalel, D. (2010). Who by accident? The social morphology of car accidents. Risk Analysis, 30(9), 1411. doi:10.1111/j.1539-6924.2010.01423.x
  • Fatality Analysis and Reporting System (FARS). (2018). National Highway Traffic Safety Administration. ftp://ftp.nhtsa.dot.gov/fars/.
  • Green, E. R., Agent, K. R., Pigman, J. G., & Ross, P. A. (2018). Analysis of traffic crash data in Kentucky (2012–2016). Lexington, KY: Kentucky Transportation Center, University of Kentucky. uknowledge.uky.edu/ktc_researchreports/1585.
  • Hoque, M. S., & Hasan, M. R. (2006). Vehicle factors in road accidents: The context of developing countries. Paper presented at International Conference on Road Safety in Developing Countries, Dhaka, Bangladesh.
  • Ihrie, J., Ahmed, I., & Poncet, A. (2017). EBGM scores for mining large contingency tables. Version 0.1.0
  • Islam, M. B., & Kanitpong, K. (2008). Identification of factors in road accidents through in-depth accident analysis. IATSS Research, 32(2), 58–67. doi:10.1016/S0386-1112(14)60209-0
  • Jalayer, M., Zhou, H., & Das, S. (2018). Exploratory analysis of run-off-road crash patterns. Data analytics for smart cities. Washington, DC: CRC Press.
  • Jalayer, M., Pour-Rouholamin, M., & Zhou, H. (2018). Wrong-way driving crashes: A multiple correspondence approach to identify contributing factors. Traffic Injury Prevention, 19(1), 35–41. doi:10.1080/15389588.2017.1347260
  • Kane, S., Liberman, E., DiViesti, T., & Click, F. (2018) Toyota sudden unintended acceleration. www.rightinginjustice.com/media/2010/02/SRS-Report-on-Toyota-Sudden-Unintended-Acceleration.pdf.
  • Kinsey, G. (1976). Contribution of unroadworthy vehicles to accidents. 2nd Conference, National Institute of Transport and Road Research, Pietersburg, South Africa.
  • Lloyd, L., Wallbank, C., Broughton, J., & Cuerden, R. (2017). Estimating the potential impact of vehicle secondary safety regulations and consumer testing programs on road casualties in emerging markets. Journal of Transportation Safety & Security, 9, 147–149. doi:10.1080/19439962.2016.1228091
  • Malaysian Institute of Road Safety Research. (2018). Automotive consumerism: A study of car user’s practices & behaviour in Klang Valley, Malaysia. Selangor Darul Ehsan, Malaysia.
  • Moodley, S., & Allopi, D. (2008). An analytical study of vehicle defects and their contribution to road accidents. In Proceedings of the 27th Southern Africa Transport Conference, Pretoria, South Africa.
  • National Highway Traffic Safety Administration. (2018). Office of defects investigation. www-odi.nhtsa.dot.gov/downloads/.
  • National Motor Vehicle Crash Causation Survey. (2018). DOT HS 811 059. crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811059.
  • R Core Team (2013). R: A language and environment for statistical computing, version 3.4.1. (2017). Vienna, Austria: The R Foundation for Statistical Computing. http://www.R-project.org/
  • Schoor, O. V., & Niekerk, J. L. (2001). Mechanical failures as a contributing cause to motor vehicle accidents-South Africa. Accident Analysis & Prevention, 33(6), 713–721.
  • Solah, M. S., Hamzah, A., Ariffin, A. H., Paiman, N. F., Hamid, I. A., … Osman, M. R. (2017). Private vehicle roadworthiness in Malaysia from the vehicle inspection perspective. Journal of the Society of Automotive Engineers Malaysia, 1(3), 262–271.
  • Treat, J., Tumbas, N., McDonald, S., Shinar, D., Hume, R., … Castellan, N. (1979). Tri-level study of the causes of traffic accidents. DOT Hs-034-3-535.
  • U.S. Department of Transportation (USDOT). (2015). Critical reasons for crashes investigated in the national motor vehicle crash causation survey: A brief statistical summary. Report No. DOT HS 812 115.
  • U.S. Department of Transportation (USDOT). (1975). National traffic safety newsletter, NHTSA Washington D.C.
  • Vaughan, R. (1992). Vehicle ageing and safety. Paper presented at Wheels ’92 Conference and Workshop, Sydney, Australia.
  • Weng, J., & Li, G. (2019). Exploring shipping accident contributory factors using association rules. Journal of Transportation Safety & Security, 11(1), 36–57. doi:10.1080/19439962.2017.1341440
  • Wolf, R. (1968). Truck accidents and traffic safety – An overview. SAE meeting, Detroit.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.