Estimating countermeasure effects for reducing collisions at highway-railway grade crossings

Accident Analysis and Prevention

Volumn 39, Issue 2, 2007, Pages 406-416

  Saccomanno, Frank F ^a   Park, Peter Young Jin ^a   Fu, Liping ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Bayesian data fusion; Countermeasure; Highway railway grade crossing; Safety

Indexed keywords

COST EFFECTIVENESS; HIGHWAY ACCIDENTS; INVESTMENTS; MATHEMATICAL MODELS; SENSOR DATA FUSION;

BAYESIAN DATA FUSION; CALIBRATED MODELS; COUNTERMEASURE EFFECTS; HIGHWAY RAILWAY GRADE CROSSING;

ACCIDENT PREVENTION;

ACCIDENT PREVENTION; ARTICLE; BAYES THEOREM; CANADA; HUMAN; RAILWAY; STATISTICS; TRAFFIC ACCIDENT;

ACCIDENT PREVENTION; ACCIDENTS, TRAFFIC; BAYES THEOREM; CANADA; HUMANS; RAILROADS;

EID: 33845218898     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2006.08.016     Document Type: Article

References (34)

1. Abbess C.R., Jarrett D.F., and Wright C.C. Accidents at blackspots: estimating the effectiveness of remedial treatment, with special reference to the 'Regression-To-Mean' effect. Traffic Eng. Control 22 10 (1981) 535-542
2. Agent, K.R., Stamatiadis, N., Jones, S., 1996. Development of Accident Reduction Factors, Research Report, KTC-96-13. Kentucky Transportation Center, College of Engineering, University of Kentucky.
3. Clarke, D.B., Sarasua, W.A., 2003. Fatal Crashes on Rural Secondary Highways. Columbia, South Carolina Department of Transportation, Final Report for Research Project SPR-608, FHWA-SC-03-04.
4. Eck R.W., and Halkias J.A. Further investigation of the effectiveness of warning devices at rail-highway grade crossings. Transportation Research Record 1010, TRB (1985), National Research Council, Washington, DC pp. 94-101
5. El Faouzi N.-E. Bayesian and evidential approaches for traffic data fusion: methodological issues and case study. Presented at the 85th Transportation Research Board Meeting. Washington, DC (2006)
6. Farr E.H. Summary of the DOT Rail-highway Crossing Resource Allocation Procedure. revised ed. (1987), Federal Railroad Administration, U.S. Department of Transportation, Transportation System Center, Cambridge MA
7. Farr, E.H., Hitz, J.S., 1985. Effectiveness of Motorist Warning Devices at Rail-highway Crossings. Final Report, FHWA/RD-85/015. U.S. Department of Transportation, Federal Highway Administration, Transportation Systems Center, Cambridge, MA.
8. Federal Railroad Administration, 2002. GradeDec 2000 Version 2.0 Reference Manual, Office of Policy and Program Development. U.S. Department of Transportation, Transportation System Center, Cambridge MA.
9. Gan, A., Shen, J., Rodriguez, A., 2005. Update of Florida Crash Reduction Factors and Countermeasures to Improve the Development of District Safety Improvement Projects. Final Report, FDOT 99700-3596-119. Lehman Center for Transportation Research, Florida International University, Miami.
10. Harkey, D., 2005. Crash Reduction Factors for Traffic Engineering and Intelligent Transportation System Improvements: State-of-Knowledge Report, NCHRP Research Result Digest 299, Interim Report, NCHRP Project 17-25. National Cooperative Highway Research Program Project, Washington, DC.
11. Harlow L.L., Mulaik S.A., and James H.S. What if There were No Significant Tests? (1997), Lawrence Erlbaum Associates Inc.
12. Harwood, D.W., Council, F.M., Hauer, E., Hughes, W.E., Vogt, A., 2000. Prediction of the Expected Safety Performance of Rural Two-Lane Highways, Final Report, FHWA-RD-99-207. Federal Highway Administration, U.S. Department of Transportation, Washington, DC.
13. Hauer E., and Persaud B.N. How to estimate the safety of rail-highway grade crossings and the safety effects of warning devices. J. Transport. Res. Record 1114 (1987) 131-140 TRB, National Research Council, Washington, DC
14. Hughes, W., Eccles, K., Harwood, D., Potts, I., Hauer, E., 2004. Development of a Highway Safety Manual, Contractor's Final Report, NCHRP Web Document 62 (NCHRP Project 17-18[4]), National Cooperative Highway Research Program Project, Washington, DC.
15. Hunter J.E., and Schmidt F.L. Methods of Meta-Analysis: Correcting Error and Bias in Research Findings (1990), SAGE Publication, Inc., California
16. Iversen G.R. Bayesian Statistical Inference (1984), Sage Publications, Inc.
17. Laughland, J., Haefner, L., Hall, J., Clough, D., 1975. Methods for Evaluating Highway Safety Improvements. National Cooperative Highway Research Program, NCHRP Report 162. Transportation Research Board, Washington, DC.
18. Law A.M., and Kelton W.D. Simulation Modeling and Analysis. second ed. (1991), McGraw-Hill, Inc.
19. Lee P.M. Bayesian Statistics: An Introduction. third ed. (2004), A Hodder Arnold Publication
20. Lord D. Modeling motor vehicle crashes using Poisson-gamma models: examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter. Accid. Anal. Prevent. 38 4 (2006) 751-766
21. Melcher D.J., Dixon K.K., Washington S., and Wu C.-H. Feasibility of "Subjective" engineering assessments of road safety improvements: Bayesian analysis development. J. Transport. Res. Record 1758 (2001) 36-43 TRB, National Research Council, Washington, DC
22. Migon H.S., and Gamerman D. Statistical Inference: An Integrated Approach (1999), A Hodder Arnold Publication
23. Morrissey, J., 1980. The Effectiveness of Flashing Lights and Flashing Lights with Gates in Reducing Accident Frequency at Public Rail-Highway Crossings 1975-1978, Final Report, FRA-RRS-80-005. U.S. Department of Transportation, Federal Railroad Administration, Washington, DC.
24. Park, Y.-J. P., Saccomanno, F.F. Reducing treatment selection bias for estimating treatment effects using propensity score method, American Society of Civil Engineers, J. Transport. Eng., (Manuscript number: TE/2005/023489), in press.
25. Park Y.-J., and Saccomanno F.F. Collision frequency analysis using tree-based stratification. J. Transport. Res. Record 1908 (2005) 121-129 TRB, National Research Council, Washington, DC
26. Park Y.-J., and Saccomanno F.F. Evaluating factors affecting safety at highway-railway grade crossings. J. Transport. Res. Record 1918 (2005) 1-9 TRB, National Research Council, Washington, DC
27. Saccomanno F.F., and Lai X. A model for evaluating countermeasures at highway-railway grade crossings. J. Transportat. Res. Record 1918 (2005) 18-25
28. Saccomanno, F.F., Fu, L., Park, Y.-J., Shen, H., 2006. A Decision Support Tool for Prioritizing Safety Improvement Programs at High-Risk Grade Crossings, Part II: Estimating Countermeasure Effectiveness. Interim Report, Department of Civil Engineering, University of Waterloo, Waterloo, Ont., Canada.
29. Sampson, D.B., 2006. The Delta Method, Lecture Note, available at http://oregonstate.edu/instruct/fw431/sampson/LectureNotes/DeltaMethod/DeltaMethod.htm, accessed January 2006.
30. Washington S., and Oh J. Bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty: example applied to at grade railroad crossings in Korea. Accid. Anal. Prevent. 38 2 (2006) 234-247
31. White, D.J., 2002. Development of a methodology for identifying effective countermeasures in regional safety management programs using a Bayesian safety assessment framework (B-SAF). Ph.D. Dissertation. Georgia Institute of Technology.
32. Wright C.C., Abbess C., and Jarrett D.F. Estimating, estimating the regression-to-mean effect associated with road accident black spot treatment: towards a more realistic approach. Accid. Anal. Prevent. 20 3 (1988) 199-214
33. Xu J., and LongF J.S. Confidence intervals for predicted outcomes in regression models for categorical outcomes. Stata J. 5 4 (2005) 537-559
34. Zegeer C.V., Stewart J.R., Council F.M., Reinfurt D.W., and Hamilton E. Safety effects of geometric improvements on horizontal curves. J. Transportat. Res. Record 1356 (1992) 11-19 TRB, National Research Council, Washington, DC