Near-crash identification in a connected vehicle environment

Transportation Research Record

Volumn 2424, Issue 1, 2014, Pages 20-28

  Talebpour, Alireza ^a   Mahmassani, Hani ^a   Mete, Fiorella ^b   Hamdar, Samer ^c  

^a Northwestern University   (United States)

^b POLITECNICO DI TORINO   (Italy)

^c The George Washington University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCIDENTS; INTELLIGENT SYSTEMS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; TRAFFIC CONTROL;

DATA SET; DETECTION ALGORITHM; DRIVING SIMULATOR; DRIVING TEST; FIXED THRESHOLD; TEST TRACK; TRAFFIC STREAMS; TRAJECTORIES DATUM; VEHICLE TECHNOLOGY; VEHICLE TRAJECTORIES;

VEHICLES;

EID: 84910081011     PISSN: 03611981     EISSN: 21694052     Source Type: Journal    
DOI: 10.3141/2424-03     Document Type: Article

References (22)

1. Fatality Analysis Reporting System. NHTSA. < http://www.nhtsa.gov/FARS'>http://www.nhtsa.gov/FARS>
2. NASS General Estimates System. NHTSA. < http://www.nhtsa.gov/Data/National+Automotive+Sampling+System+(NASS)/NASS+General+Estimates+System>
3. Smith, D. L., W. G. Najm, and R. A. Glassco. Feasibility of Driver Judgment as Basis for a Crash Avoidance Database. In "Transportation Research Record: Journal of the Transportation Research Board, No. 1784", Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 9-16.
4. The 100-Car Naturalistic Driving Study: A Descriptive Analysis of Light Vehicle-Heavy Vehicle Interactions from the Light Vehicle Driver's Perspective. FMCSA, U.S. Department of Transportation, 2006.
5. Thomas, F. D., R. D. Blomberg, R. C. Peck, L. A. Cosgrove, and P. M. Salzberg. Evaluation of a High Visibility Enforcement Project Focused on Passenger Vehicles Interacting with Commercial Vehicles. "Journal of Safety Research", Vol. 39, No. 5, 2008, pp. 459-468.
6. Van der Horst, A. R. A. "A Time-Based Analysis of Road User Behaviour in Normal and Critical Encounters." TNO Institute for Perception, Soesterberg, Netherlands, 1990.
7. Evaluating the Relationship Between Near-Crashes and Crashes: Can Near-Crashes Serve as a Surrogate Safety Metric for Crashes? NHTSA, U.S. Department of Transportation. 2010.
8. Guo, F., S. G. Klauer, J. M. Hankey, and T. A. Dingus. Near Crashes as Crash Surrogate for Naturalistic Driving Studies. In "Transportation Research Record: Journal of the Transportation Research Board, No. 2147", Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 66-74.
9. Jovanis, P. P., J. Aguero-Valverde, K.-F. Wu, and V. Shankar. Analysis of Naturalistic Driving Event Data: Omitted-Variable Bias and Multilevel Modeling Approaches. In "Transportation Research Record: Journal of the Transportation Research Board, No. 2236", Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 49-57.
10. Najm, W. G., M. D. Stearns, H. Howarth, J. Koopmann, and J. Hitz. "Evaluation of an Automotive Rear-End Collision Avoidance System." Final report. DOT-VNTSC-NHTSA-06-01. NHTSA, U.S. Department of Transportation, 2006.
11. Kiefer, R., D. LeBlanc, M. Palmer, J. Salinger, R. Deering, and M. Shulman. "Development and Validation of Functional Definitions and Evaluation Procedures for Collision Warning/Avoidance Systems." Final report. DOT HS 808 964. NHTSA, U.S. Department of Transportation, 1999.
12. "Safety Compass: Highway Safety Solutions for Saving Lives." A Publication of the FHWA Safety Program. Winter 2012-2013 Issue. Vol. 6, No. 3, 2012.
13. Eccles, K., F. Gross, M. Liu, and F. Council. "Crash Data Analysis for Vehicle-to-Infrastructure Communications for Safety Applications." FHWA-HRT-11-040. U.S. Department of Transportation, 2012.
14. Hamdar, S. H., H. S. Mahmassani, and M. Treiber. Individual Variations Versus Collective Traffic Patterns: Heterogeneity Effect in a Risk-Taking Environment. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
15. Kim, J., and H. S. Mahmassani. Correlated Parameters in Driving Behavior Models: Car-Following Example and Implications for Traffic Microsimulation. In "Transportation Research Record: Journal of the Transportation Research Board, No. 2249", Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 62-77.
16. Talebpour, A., H. S. Mahmassani, and S. H. Hamdar. Multiregime Sequential Risk-Taking Model of Car-Following Behavior: Specification, Calibration, and Sensitivity Analysis. In "Transportation Research Record: Journal of the Transportation Research Board, No. 2260", Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 60-66.
17. Smith, D., W. Najm, and A. Lam. "Analysis of Braking and Steering Performance in Car-Following Scenarios." SAE Technical Paper. 2003-01-0283.
18. SWOV Institute for Road Safety Research. "SWOV Fact Sheet: Headway Times and Road Safety." Leidschendam, Netherlands, 2007.
19. "NGSIM I-80 Data Analysis." Summary report. Cambridge Systematics Inc., Cambridge, Mass., 2006.
20. "NGSIM US101 Data Analysis." Summary report. Cambridge Systematics Inc., Cambridge, Mass., 2007.
21. Hourdos, J. N., V. Garg, P. G. Michalopoulos, and G. A. Davis. Real-Time Detection of Crash-Prone Conditions at Freeway High-Crash Locations. In "Transportation Research Record: Journal of the Transportation Research Board, No. 1968", Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 83-91.
22. Talebpour, A., H. S. Mahmassani, and S. H. Hamdar. Safety First: Microsimulation Approach to Assessing Congestion Effects on Risk Experienced by Drivers. In "Transportation Research Record: Journal of the Transportation Research Board, No. 2316", Transportation Research Board of the National Academies, Washington, D.C., 2012, pp. 106-113.