Simplified, data-driven, errorable car-following model to predict the safety effects of distracted driving

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Volumn , Issue , 2012, Pages 1149-1154

  Przybyla, J ^a   Taylor, J ^a   Jupe, J ^b   Zhou, X ^a  

^a University of Utah   (United States)

^b Armstrong Forensic Engineers   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAR-FOLLOWING MODELS; COGNITIVE PSYCHOLOGY; CRASH RATE; DRIVER BEHAVIOR; DRIVER DISTRACTIONS; FULLY INTEGRATED; LONGITUDINAL DRIVING; NORMAL DRIVING;

BEHAVIORAL RESEARCH; INTELLIGENT SYSTEMS; TRAFFIC SURVEYS;

DIGITAL STORAGE;

EID: 84871231480     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITSC.2012.6338913     Document Type: Conference Paper

References (26)

1. G. Newell, "A simplified car-followign theory: a lower order model," Transportation Research Part B, vol. 36, pp. 195-205, 2002.
2. National Safety Council, "Injury Facts," 2010.
3. National Center for Health Statistics Mortality Data, "National Safety Council Analysis of," 2010.
4. CDC, "Nonfatal, Motor Vehicle Occupant Injuries," MMWR, 2011.
5. S. McEvoy and M. Stevenson, "An exploration of the role of driver distraction in serious road crashes," IJ Faulks et al, eds. Distracted Driving, pp. 189-211, 2007.
6. J. Stutts, R. Knipling, R. Pfefer, T. Neuman, K. Slack and K. Hardy, "Guidance for implementing of the AASHTO strategic highway safety plan: A guide for reducing crashes involving drowsy and distracted drivers.," NCHRP Rep. No. 500-14, Transportation Research Board, Washington, D.C., 2005.
7. V. Neale, T. Dingus, S. Klauer, J. Sudweeks and M. Goodman, "An overview of the 100-car naturalistic study and findings," National Highway Traffic Safety Administration Paper NO. 05-0400, Washington D.C., 2009.
8. McCartt, Hellinga and Braitman, "Cell phones and driving: review of research," Traffic Injury Prevention, vol. 7, pp. 89-106, 2006.
9. Wickens and Horrey, "The Impact of Cell Phone Conversations on Driving, A Meta-Analytic Approach," Technical Report. University of Illinois at Urbana-Champign, 2004.
10. J. Caird, C. Willness, P. Steel and C. Scialfa, "A meta-analysis of the effects of cell phones on driver performance," Accident Analysis and Prevention, vol. 40, pp. 1282-1293, 2008.
11. C. Brace, K. Young and M. Regan, "Analysis of the literature: The use of mobile phones while driving," Monash University Accident Research Centre, Austrailia, 2007.
12. R. Chandler, R. Herman and E. Montroll, "Traffic Dynamics: Studies in Car-Following," Operations Research, vol. 6, no. 2, pp. 165-184, 1958.
13. J. J. Tyler, "The Characterisitic of Model-Following Systems as Synthesized by Optimal Control," Automatic Control, IEEE Transaction, vol. 9, no. 4, pp. 485-498, 1964.
14. P. Gipps, "Behavioral Car-Following Modle for Computer Simulation," Transportation Research, vol. 15B, no. 2, pp. 105-111, 1981.
15. K. Nagel and M. Schreckenberg, "A Cellular Automation Model for Freeway Traffic," J. PHysic I France, vol. 2, pp. 2221-2229, 1992.
16. S. Krauss, P. Wagner and C. Grawron, "Continuous limit of the Nagel-Schreckenberg model," Physical Review I, vol. 54, no. 4, pp. 3707-3712, 1996.
17. D. Jost and K. Nagel, "Probabilistic Traffic Flow Breakdown In Stochastic Car-following Models," Transportation Research Record, vol. 1852, pp. 152-158, 2003.
18. P. Wagner and I. Lubashevsky, "Empirical Basis for Car-Following Theory Development," Statistical Mechanics, 2006.
19. H. H. Yang and H. Peng, "Development of an Errorable Car-Following Driver Model," Vehicle System Dynamics, vol. 48, no. 6, pp. 751-773, 2009.
20. J. Kim, Y. Wang and G. Ulfarsson, "Modeling the Probability of Freeway Rear-End Crash Occurance," Journal of Transportation Engineering, 2006.
21. F. Wu, J. Lu and J. Jiang, "Estimation of Car-following Model Parameters Distribution Using Bootstrap Method," in 3rd International Conference on Road Safety and Simulation, Indianapolis, 2011.
22. C. Oh and T. Kim, "Estimation of rear-end crash potential using vehicle trajectory data," Accident Analysis and Prevention, vol. 42, pp. 1888-1893, 2010.
23. J. Taylor, X. Zhou and N. Rouphail, Calibrating Time-Dependent Car-Following Models Based on Vehicle Trajectory Data: A Dynamic Time Warping Approach, 91st Annual Meeting of TRB, Washington, D.C., Paper 12-4575, 2012.
24. S. Pavel, "Dynamic Time Warping Algorithm Review," December 2008. [Online]. Available: http://cadl.ics.hawaii.edu/techreports/08-04/08-04. pdf. [Accessed May 2012].
25. E. Keogh and M. Pazzani, "Derivative Dynamic Time Warping," in International Proceeding of the First International SIA Conference on Data Mining, Chicago, IL, 2001.
26. FHWA, "Traffic Analysis Tools Program," 22 September 2011. [Online]. Available: http://ops.fhwa.dotlgov/trafficanalysistools/index.htm. [Accessed 5 October 2011].