Gate-violation behavior at highway-rail grade crossings and the consequences: Using geo-Spatial modeling integrated with path analysis

Accident Analysis and Prevention

Volumn 109, Issue , 2017, Pages 99-112

  Liu, Jun ^a   Khattak, Asad J ^a  

^a UNIVERSITY OF TENNESSEE   (United States)

Author keywords

Gate Violation; Geographically weighted regression; Highway Rail grade crossing; Injury severity; Path analysis

Indexed keywords

DRIVER TRAINING; RAILROAD CROSSINGS; REGRESSION ANALYSIS; TRANSPORTATION;

GATE-VIOLATION; GEOGRAPHICALLY WEIGHTED REGRESSION; INJURY SEVERITY; PATH ANALYSIS; RAIL GRADES;

BEHAVIORAL RESEARCH;

ADULT; CAR DRIVING; ENVIRONMENTAL PLANNING; GEOGRAPHIC MAPPING; HIGH RISK BEHAVIOR; HUMAN; ILLINOIS; IOWA; MALE; MINNESOTA; PREVENTION AND CONTROL; PSYCHOLOGY; RAILWAY; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT; UNITED STATES; WISCONSIN;

ACCIDENTS, TRAFFIC; ADULT; AUTOMOBILE DRIVING; ENVIRONMENT DESIGN; GEOGRAPHIC MAPPING; HUMANS; ILLINOIS; IOWA; MALE; MINNESOTA; RAILROADS; RISK-TAKING; UNITED STATES; WISCONSIN;

EID: 85031724111     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2017.10.010     Document Type: Article

References (56)

1. AASHTO, Highway Safety Manual. 2010, American Association of State Highway and Transportation Officials, Washington, DC.
2. Aguero-Valverde, J., Jovanis, P.P., Spatial analysis of fatal and injury crashes in Pennsylvania. Accid. Anal. Prev. 38 (2006), 618–625.
3. Austin, R.D., Carson, J.L., An alternative accident prediction model for highway-rail interfaces. Accid. Anal. Prev. 34 (2002), 31–42.
4. Bartier, P.M., Keller, C.P., Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Comput. Geosci. 22 (1996), 795–799.
5. Bozdogan, H., Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions. Psychometrika 52 (1987), 345–370.
6. Brunsdon, C., Fotheringham, S., Charlton, M., Geographically weighted regression. J. R. Stat. Soc. Series D (Stat.) 47 (1998), 431–443.
7. Cooper, D.L., Ragland, D.R., Applying Safety Treatments To Rail-Highway At-Grade Crossings. 2012.
8. Dobson, A.J., Barnett, A., An Introduction to Generalized Linear Models. 2008, CRC press.
9. Eluru, N., Bagheri, M., Miranda-Moreno, L.F., Fu, L., A latent class modeling approach for identifying vehicle driver injury severity factors at highway-railway crossings. Accid. Anal. Prev. 47 (2012), 119–127.
10. Elvik, R., Vaa, T., The Handbook of Road Safety Measures. 2004, Elsevier, Amsterdam ISBN 0–08-044091–6.
11. Elvik, R., Vaa, T., Erke, A., Sorensen, M., The Handbook of Road Safety Measures. 2009, Emerald Group Publishing.
12. FRA, Federal Railroad Administration Guide For Preparing U.S. DOT Crossing Inventory Forms Federal Railroad Administration. 2015, U.S. Department of Transportation, Washington, D.C.
13. FRA, Highway-Rail Accidents (6180.57). Federal Railroad Administration. 2015, U.S. Department of Transportation, Washington, D.C.
14. Fan, W., Kane, M.R., Haile, E., Analyzing severity of vehicle crashes at highway-Rail grade crossings: multinomial logit modeling. J. Trans. Res. Forum 54:2 (2015), 39–56.
15. Fotheringham, A.S., Charlton, M.E., Brunsdon, C., Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environ. Plann. A 30 (1998), 1905–1927.
16. Fotheringham, A.S., Brunsdon, C., Charlton, M., Geographically Weighted Regression: the Analysis of Spatially Varying Relationships. 2003, John Wiley & Sons.
17. Ghomi, H., Bagheri, M., Fu, L., Miranda-Moreno, L.F., Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: a comparative study. Traffic Inj. Prev. 17:8 (2016), 833–841.
18. Graham, D.J., Glaister, S., Spatial variation in road pedestrian casualties: the role of urban scale density and land-use mix. Urban Stud. 40 (2003), 1591–1607.
19. Gross, F., Persaud Lyon, B.C., A Guide to Developing Quality Crash Modification Factors. 2010.
20. Hadayeghi, A., Shalaby, A.S., Persaud, B.N., Development of planning level transportation safety tools using geographically weighted Poisson regression. Accid. Anal. Prev. 42 (2010), 676–688.
21. Haleem, K., Gan, A., Contributing factors of crash injury severity at public highway-railroad grade crossings in the US. J. Saf. Res. 53 (2015), 23–29.
22. Hao, W., Daniel, J., Motor vehicle driver injury severity study under various traffic control at highway-rail grade crossings in the United States. J. Saf. Res. 51 (2014), 41–48.
23. Horton, S., Carroll, M., Chaudhary, T., Mozenter, J., Skinner, D., Success Factors in the Reduction of Highway-Rail Grade Crossing Incidents from 1994 to. DOT-VNTSC-FRA-09-01. 2003, FRA, Department of Transportation, U.S, 2009.
24. Hu, S.-R., Li, C.-S., Lee, C.-K., Investigation of key factors for accident severity at railroad grade crossings by using a logit model. Saf. Sci. 48 (2010), 186–194.
25. Khattak, A., Rocha, M., Are SUVs supremely unsafe vehicles?: analysis of rollovers and injuries with sport utility vehicles. Trans. Res. Rec. J. Trans. Res. Board 1840 (2003), 167–177.
26. Khattak, A.J., Clarke, D., Liu, J., Wang, X., Zhang, M., What Is the Extent of Harm in Rail-pedestrian Crashes? No. NURailTK-R06. Natioal Univesity Rail (NURail) Center. 2013, University of Illionis at Urbana-Chapaign, 2014.
27. Khattak, A., Gate violations by truck drivers at highway-rail grade crossings in two cities. J. Trans. Res. Forum, 2013, 117–217.
28. Khattak, A., Severity of pedestrian crashes at highway-Rail grade crossings. Transportation Research Board 92nd Annual Meeting, 2013.
29. LaScala, E.A., Gerber, D., Gruenewald, P.J., Demographic and environmental correlates of pedestrian injury collisions: a spatial analysis. Accid. Anal. Prev. 32 (2000), 651–658.
30. Lenné M.G., Rudin-Brown, C.M., Navarro, J., Edquist, J., Trotter, M., Tomasevic, N., Driver behaviour at rail level crossings: responses to flashing lights: traffic signals and stop signs in simulated rural driving. Appl. Ergon. 42 (2011), 548–554.
31. Li, Z., Lee, S., Lee, Y., Valiou, E., Geographically-weighted regression models for improved predictability of urban intersection vehicle crashes. Transportation and Development Institute Congress, 2011, 1315–1329.
32. Li, Z., Wang, W., Liu, P., Bigham, J.M., Ragland, D.R., Using geographically weighted Poisson regression for county-level crash modeling in California. Saf. Sci. 58 (2013), 89–97.
33. Liu, J., Bartnik, B., Richards, S.H., Khattak, A.J., How are driver characteristics related to safety at railroad-crossings? The case of passive railroad grade crossings. 93rd Annual Meeting of the Transportation Research Board, Washington D.C, 2014.
34. Liu, J., Khattak, A.J., Richards, S.H., Nambisan, S., What are the differences in driver injury outcomes at highway-rail grade crossings?: Untangling the role of pre-crash behaviors. Accid. Anal. Prev. 85 (2015), 157–169.
35. Liu, J., Bartnik, B., Richards, S.H., Khattak, A.J., Driver behavior at highway rail grade crossings with passive traffic controls: a driving simulator study. J. Transp. Saf. Secur. 8:Suppl. 1 (2016), 37–55.
36. Liu, J., Wang, X., Khattak, A.J., Hu, J., Cui, J., Ma, J., How big data serves for freight safety management at highway-rail grade crossings? A spatial approach fused with path analysis. Neurocomputing 181 (2016), 38–52.
37. Liu, J., Khattak, A., Wali, B., Do safety performance functions vary across space? application of geographically weighted regressions. 96th Annual Meeting of the Transportation Research Board, Washington D.C, 2017.
38. Liu, J., Khattak, A., Wang, X., A comparative study of driving performance in metropolitan regions using large-scale vehicle trajectory data: implications for sustainable cities. Int. J. Sustain. Trans. 11:3 (2017), 170–185.
39. Meliker, J.R., Maio, R.F., Zimmerman, M.A., Kim, H.M., Smith, S.C., Wilson, M.L., Spatial analysis of alcohol-related motor vehicle crash injuries in southeastern Michigan. Accid. Anal. Prev. 36 (2004), 1129–1135.
40. Noland, R.B., Quddus, M.A., Congestion and safety: a spatial analysis of London. Trans. Res. Part A: Policy Pract. 39 (2005), 737–754.
41. Ogden, B.D., Railroad-Highway Grade Crossing Handbook FHWA-SA-07-010. 2007, Institute of Transportation Engineers.
42. Park, Y.-J., Saccomanno, F.F., Collision frequency analysis using tree-based stratification. Trans. Res. Rec. J. Trans. Res. Board 1908 (2005), 121–129.
43. Pirdavani, A., Bellemans, T., Brijs, T., Wets, G., Application of geographically weighted regression technique in spatial analysis of fatal and injury crashes. J. Transp. Eng., 2014.
44. Quddus, M.A., Modelling area-wide count outcomes with spatial correlation and heterogeneity: an analysis of London crash data. Acci. Anal. Prev. 40 (2008), 1486–1497.
45. Raub, R.A., Examination of highway-Rail grade crossing collisions over 10 years in seven midwestern states. ITE J. 76 (2006), 16–26.
46. Raub, R.A., Examination of highway-rail grade crossing collisions nationally from 1998 to 2007. Trans. Res. Rec. J. Trans. Res. Board 2122 (2009), 63–71.
47. Rudin-Brown, C.M., Lenné M.G., Edquist, J., Navarro, J., Effectiveness of traffic light vs. boom barrier controls at Road?Rail level crossings: a simulator study. Accid. Anal. Prev. 45 (2012), 187–194.
48. Russo, B., Savolainen, P., An examination of factors affecting the frequency and severity of crashes at rail-Grade crossings. Transportation Research Board 92nd Annual Meeting, 2013.
49. Saefuddin, A., Setiabudi, N.A., Fitrianto, A., On comparison between logistic regression and geographically weighted logistic regression: with application to Indonesian poverty data. World Appl. Sci. J. 19 (2012), 205–210.
50. Silverman, B.W., Density Estimation for Statistics and Data Analysis. 1986, Chapman and Hall New York.
51. StataCorp, Stata Multiple-Imputation Reference Manual. 2013.
52. Wang, C., Quddus, M.A., Ison, S.G., Impact of traffic congestion on road accidents: a spatial analysis of the M25 motorway in England. Accid. Anal. Prev. 41 (2009), 798–808.
53. Wang, Y., Kockelman, K., Wang, X., Anticipation of land use change through use of geographically weighted regression models for discrete response. Trans. Res. Reco. J. Trans. Res. Board, 2011, 111–123.
54. Wang, X., Liu, J., Khattak, A.J., Clarke, D., Non-crossing rail-trespassing crashes in the past decade: a spatial approach to analyzing injury severity. Saf. Sci. 82 (2016), 44–55.
55. Witte, K., Donohue, W.A., Preventing vehicle crashes with trains at grade crossings: the risk seeker challenge. Accid. Anal. Prev. 32 (2000), 127–139.
56. Zhao, S., Khattak, A., Motor vehicle drivers’ injuries in train–motor vehicle crashes. Accid. Anal. Prev. 74 (2015), 162–168.