Macro and micro models for zonal crash prediction with application in hot zones identification

Journal of Transport Geography

Volumn 54, Issue , 2016, Pages 248-256

  Huang, Helai ^a   Song, Bo ^a   Xu, Pengpeng ^b   Zeng, Qiang ^c   Lee, Jaeyoung ^d   Abdel Aty, Mohamed ^d  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

^c SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^d UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Bayesian inference; Conditional autoregressive model; Crash prediction model; Integrated screening; Spatial correlation; Zonal safety analysis

Indexed keywords

ACCIDENT; BAYESIAN ANALYSIS; COMPARATIVE STUDY; PREDICTION; SPATIAL ANALYSIS; TRANSPORTATION PLANNING; TRANSPORTATION SAFETY;

FLORIDA [UNITED STATES]; HILLSBOROUGH COUNTY [FLORIDA]; UNITED STATES;

EID: 84975470957     PISSN: 09666923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jtrangeo.2016.06.012     Document Type: Article

References (53)

1. AASHTO Highway Safety Manual 2010, first ed.
2. Abdel-Aty M., Siddiqui C., Huang H. Integrating trip and roadway characteristics in managing safety at traffic analysis zones. Transp. Res. Rec. 2011, 2213:20-28.
3. Abdel-Aty M., Lee J., Siddiqui C., Choi K. Geographical unit based analysis in the context of transportation safety planning. Transp. Res. A 2013, 49:62-75.
4. Aguero-Valverde J. Multivariate spatial models of excess crash frequency at area level: case of Costa Rica. Accid. Anal. Prev. 2013, 59:365-373.
5. Aguero-Valverde J., Jovanis P.P. Spatial analysis of fatal and injury crashes in Pennsylvania. Accid. Anal. Prev. 2006, 38:618-625.
6. Aguero-Valverde J., Jovanis P.P. Spatial correlation in multilevel crash frequency models: effects of different neighboring structures. Transp. Res. Rec. 2010, 2165:21-33.
7. Besag J., York J., Molli E.A. Bayesian image restoration with two applications in spatial statistics. Ann. Inst. Stat. Math. 1991, 43:1-59.
8. Cheng W., Washington S. New criterion for evaluating methods of identifying hot spots. Transp. Res. Rec. 2008, 2083:76-85.
9. Cui G., Wang X., Kwon D. A framework of boundary collision data aggregation into neighbourhoods. Accid. Anal. Prev. 2015, 83:1-17.
10. Dong N., Huang H., Xu P., Ding Z., Wang D. Evaluating spatial-proximity structures in crash prediction models at the level of traffic analysis zones. Transp. Res. Rec. 2014, 2432:46-52.
11. Dong N., Huang H., Zheng L. Support vector machine in crash prediction at the level of traffic analysis zones: assessing the spatial proximity effects. Accid. Anal. Prev. 2015, 82:192-198.
12. Dong N., Huang H., Lee J., Gao M., Abdel-Aty M. Macroscopic hotspots identification: a Bayesian spatio-temporal interaction approach. Accid. Anal. Prev. 2016, 92:256-264.
13. Gelman A., Carlin J.B., Stern H.S., Rubin D.B. Bayesian Data Analysis 2003, Chapman & Hall, New York. second ed.
14. Girasek D.C., Taylor B. An exploratory study of the relationship between socioeconomic status and motor vehicle safety features. Traffic Inj. Prev. 2010, 11(2):151-155.
15. Hadayeghi A., Shalaby A.S., Persaud B.N. Development of planning level transportation safety tools using geographically weighted Poisson regression. Accid. Anal. Prev. 2010, 42(2):676-688.
16. Haynes R., Jones A., Kennedy V., Harvey I., Jewell T. District variations in road curvature in England and Wales and their association with road-traffic crashes. Environ. Plan. A 2007, 39(5):1222-1237.
17. Huang H., Abdel-Aty M. Multilevel data and Bayesian analysis in traffic safety. Accid. Anal. Prev. 2010, 42(6):1556-1565.
18. Huang H., Chin H.C., Haque M.M. Empirical evaluation of alternative approaches in identifying crash hot spots: naïve ranking, empirical Bayes, and full Bayes methods. Transp. Res. Rec. 2009, 2103:32-41.
19. Huang H., Abdel-Aty M., Darwiche A.L. County-level crash risk analysis in Florida: Bayesian spatial modeling. Transp. Res. Rec. 2010, 2148:27-37.
20. Huang H., Zeng Q., Pei X., Wong S.C., Xu P. Predicting crash frequency using an optimized radial basis function neural network model. Transportmetrica A 2016, 12(4):330-345.
21. Lee J. Development of Traffic Safety Zones and Integrating Macroscopic and Microscopic Safety Data Analytics for Novel Hot Zone Identification 2014, University of Central Florida, Orlando, Florida, (Doctoral dissertation).
22. Lee J., Abdel-Aty M., Choi K. Analysis of residence characteristics of at-fault drivers in traffic crashes. Saf. Sci. 2014, 68:6-13.
23. Lee J., Abdel-Aty M., Jiang X. Development of zone system for macro-level traffic safety analysis. J. Transp. Geogr. 2014, 38:13-21.
24. Lee J., Abdel-Aty M., Choi K., Huang H. Multi-level hot zone identification for pedestrian safety. Accid. Anal. Prev. 2015, 76:64-73.
25. Levine N., Kim K.E., Nitz L.H. Spatial analysis of Honolulu motor vehicle crashes: II. Zonal generators. Accid. Anal. Prev. 1995, 27:675-685.
26. 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. 2013, 58:89-97.
27. Loo B.P.Y. The identification of hazardous road locations: a comparison of the blacksite and hot zone methodologies in Hong Kong. Int. J. Sustain. Transport. 2009, 3:187-202.
28. Loo B.P.Y., Yao S. The identification of traffic crash hot zones under the link-attribute and event-based approaches in a network-constrained environment. Comput. Environ. Urban. Syst. 2013, 41:249-261.
29. Miaou S., Lord D. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus Empirical Bayes. Transp. Res. Rec. 2003, 1840:31-40.
30. Miaou S., Song J.J., Mallick B.K. Roadway traffic crash mapping: a space-time modeling approach. J. Transp. Stat. 2003, 6:33-57.
31. Pirdavani A., Brijis T., Bellemans T., Kochan B., Wets G. Application of different exposure measures in development of planning-level zonal crash predicition models. Transp. Res. Board 2012, 2280:145-153.
32. Pulugurha S.S., Duddu V.R., Kotagirl Y. Traffic analysis zone level crash estimation models based on land use characteristics. Accid. Anal. Prev. 2013, 50:678-687.
33. Qin X., Ivan J.N., Ravishanker N. Selecting exposure measures in crash rate prediction for two-lane highway segments. Accid. Anal. Prev. 2004, 36(2):183-191.
34. Quddus M.A. Modeling area-wide count outcomes with spatial correlation and heterogeneity: an analysis of London crash data. Accid. Anal. Prev. 2008, 40(4):1486-1497.
35. Siddiqui C., Abdel-Aty M. Nature of modeling boundary pedestrian crashes at zones. Transp. Res. Rec. 2012, 2299:31-40.
36. Siddiqui C., Abdel-Aty M., Choi K. Macroscopic spatial analysis of pedestrian and bicycle crashes. Accid. Anal. Prev. 2012, 45:382-391.
37. Spiegelhalter D., Thomas A., Best N., Lunn D. WinBUGS User Manual 2005, MRC Biostatistics Unit, Cambridge, United Kingdom.
38. Ukkusuri S., Hasan S., Aziz H.M.A. Random parameter model used to explain effects of built-environmental characteristics on pedestrian crash frequency. Transp. Res. Rec. 2011, 2237:98-106.
39. Ukkusuri S., Miranda-Moreno L.F., Ramadurai G., Isa-Tavarez J. The role of built environment on pedestrian crash frequency. Saf. Sci. 2012, 50:1141-1151.
40. Wakefield J.C., Best N.G., Waller L. Bayesian Approaches to Disease Mapping, on Spatial Epidemiology: Methods and Applications 2000, Oxford University Press.
41. Wang X., Abdel-Aty M. Temporal and spatial analysis of rear-end crashes at signalized intersections. Accid. Anal. Prev. 2006, 38(6):1137-1150.
42. Wang J., Huang H. Road network safety evaluation using Bayesian hierarchical joint model. Accid. Anal. Prev. 2016, 90:152-158.
43. Wang Y., Kockelman K.M. A Poisson-lognormal conditional-autoregressive model for multivariate spatial analysis of pedestrian crash counts across neighborhoods. Accid. Anal. Prev. 2013, 60:71-84.
44. 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. 2009, 41(4):798-808.
45. Wang X., Wu X., Abdel-Aty M., Tremont P.J. Investigating of road network features and safety performance. Accid. Anal. Prev. 2013, 56:22-31.
46. Washington S., Metarko J., Fomunung I., Ross R., Julian F., Moran E. An inter-regional comparison: fatal crashes in the southeastern and non-southeastern United States: preliminary findings. Accid. Anal. Prev. 1999, 31(1-2):135-146.
47. Washington S.P., Van Schalkwyk I., Mitra S., Meyer M., Dumbaugh E., Zoll M. Incorporating safety into long-range transportation planning. NCHRP Report 546 2006, Transportation Research Board, Washington, D.C.
48. Washington S.P., Van Schalkwyk I., You D., Shin K., Samuelson J.P. Forecasting the safety impacts of socio-demographic changes and safety countermeasures. NCHRP 8-44(2): Plansafe User Manual 2010, Transportation Research Board, Washington, DC.
49. Xie K., Wang X., Huang H., Chen X. Corridor-level signalized intersection safety analysis in Shanghai, China using Bayesian hierarchical models. Accid. Anal. Prev. 2013, 50:25-33.
50. Xu P., Huang H. Modeling crash spatial heterogeneity: random parameter versus geographically weighting. Accid. Anal. Prev. 2015, 75:16-25.
51. Xu P., Huang H., Dong N., Abdel-Aty M. Sensitivity analysis in the context of regional safety modeling: identifying and assessing the modifiable areal unit problem. Accid. Anal. Prev. 2014, 70:110-120.
52. Zeng Q., Huang H. Bayesian spatial joint modeling of traffic crashes on an urban road network. Accid. Anal. Prev. 2014, 67:105-112.
53. Zeng Q., Huang H., Pei X., Wong S.C. Modeling nonlinear relationship between crash frequency by severity and contributing factors by neural networks. Anal. Meth. Accid. Res. 2016, 10:12-25.