Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto

Accident Analysis and Prevention

Volumn 95, Issue , 2016, Pages 157-171

  Yasmin, Shamsunnahar ^a   Eluru, Naveen ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Bicycle crashes; Latent segmentation negative binomial model; Latent segmentation poisson model; Population heterogeneity

Indexed keywords

ACCIDENTS; BICYCLES; BINS; CRASHWORTHINESS; DECISION MAKING; REGRESSION ANALYSIS; RISK ANALYSIS; RISK ASSESSMENT; SAFETY ENGINEERING; TRAFFIC CONTROL;

ACCESSIBILITY MEASURES; BICYCLE CRASHES; NEGATIVE BINOMIAL MODELS; POISSON MODEL; POPULATION HETEROGENEITY; SOCIO-DEMOGRAPHIC CHARACTERISTICS; SOCIOECONOMIC CHARACTERISTICS; TRAFFIC ANALYSIS ZONES;

SPORTING GOODS;

ADOLESCENT; ADULT; AGED; CANADA; CHILD; CYCLING; ENVIRONMENTAL PLANNING; FEMALE; HUMAN; MALE; MIDDLE AGED; PREVENTION AND CONTROL; RISK ASSESSMENT; SAFETY; SOCIOECONOMICS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT; YOUNG ADULT;

ACCIDENTS, TRAFFIC; ADOLESCENT; ADULT; AGED; BICYCLING; CANADA; CHILD; ENVIRONMENT DESIGN; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, ECONOMETRIC; RISK ASSESSMENT; SAFETY; SOCIOECONOMIC FACTORS; YOUNG ADULT;

EID: 84978538367     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2016.07.015     Document Type: Article

References (58)

1. Abdel-Aty, M., Siddiqui, C., Huang, H., Wang, X., Integrating trip and roadway characteristics to manage safety in traffic analysis zones. Transp. Res. Rec. 2213 (2011), 20–28.
2. Abdel-Aty, M., Lee, J., Siddiqui, C., Choi, K., Geographical unit based analysis in the context of transportation safety planning. Transp. Res. Part A 49:0 (2013), 62–75.
3. Aguero-Valverde, J., Jovanis, P.P., Spatial analysis of fatal and injury crashes in Pennsylvania. Accid. Anal. Prev. 38:3 (2006), 618–625.
4. Amoros, E., Martin, J.L., Laumon, B., Comparison of road crashes incidence and severity between some French counties. Accid. Anal. Prev. 35:4 (2003), 537–547.
5. Bago d'Uva, T., Latent class models for utilisation of health care. Health Econ. 15:4 (2006), 329–343.
6. Bhat, C.R., Endogenous segmentation mode choice model with an application to intercity travel. Transp. Sci. 31:1 (1997), 34–48.
7. Brüde, U., Larsson, J., Models for predicting accidents at junctions where pedestrians and cyclists are involved. How well do they fit?. Accid. Anal. Prev. 25:5 (1993), 499–509.
8. Carter, D., Council, F., Factors contributing to pedestrian and bicycle crashes on rural highways. Paper Presented at the Transportation Research Board 86th Annual Meeting Paper, 2007.
9. Cho, G., Rodríguez, D.A., Khattak, A.J., The role of the built environment in explaining relationships between perceived and actual pedestrian and bicyclist safety. Accid. Anal. Prev. 41:4 (2009), 692–702.
10. Cottrill, C.D., Thakuriah, P.V., Evaluating pedestrian crashes in areas with high low-income or minority populations. Accid. Anal. Prev. 42:6 (2010), 1718–1728.
11. De Guevara, F.L., Washington, S.P., Oh, J., Forecasting crashes at the planning level: simultaneous negative binomial crash model applied in Tucson, Arizona. Transp. Res. Rec. 1987 (2004), 191–199.
12. Dong, C., Clarke, D.B., Richards, S.H., Huang, B., Differences in passenger car and large truck involved crash frequencies at urban signalized intersections: an exploratory analysis. Accid. Anal. Prev. 62:0 (2014), 87–94.
13. Eluru, N., Bhat, C.R., A joint econometric analysis of seat belt use and crash-related injury severity. Accid. Anal. Prev. 39:5 (2007), 1037–1049.
14. 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. 47:0 (2012), 119–127.
15. Greene, W.H., Hensher, D.A., A latent class model for discrete choice analysis: contrasts with mixed logit. Transp. Res. Part B 37:8 (2003), 681–698.
16. Hadayeghi, A., Shalaby, A., Persaud, B., Macrolevel accident prediction models for evaluating safety of urban transportation systems. Transp. Res. Rec. 1840 (2003), 87–95.
17. Hadayeghi, A., Shalaby, A., Persaud, B., Safety prediction models: proactive tool for safety evaluation in urban transportation planning applications. Transp. Res. Rec. 2019 (2007), 225–236.
18. Hadayeghi, A., Shalaby, A., Persaud, B., Development of planning-level transportation safety models using full Bayesian semiparametric additive techniques. J. Transp. Saf. Secur. 2:1 (2010), 45–68.
19. Hadayeghi, A., Shalaby, A.S., Persaud, B.N., Development of planning level transportation safety tools using Geographically Weighted Poisson Regression. Accid. Anal. Prev. 42:2 (2010), 676–688.
20. Huang, H., Abdel-Aty, M., Darwiche, A., County-level crash risk analysis in Florida. Transp. Res. Rec. 2148 (2010), 27–37.
21. Jang, T.Y., Count data models for trip generation. J. Transp. Eng. 131:6 (2005), 444–450.
22. Jung, S., Jang, K., Yoon, Y., Kang, S., Contributing factors to vehicle to vehicle crash frequency and severity under rainfall. J. Safety Res. 50:0 (2014), 1–10.
23. Karlaftis, M.G., Tarko, A.P., Heterogeneity considerations in accident modeling. Accid. Anal. Prev. 30:4 (1998), 425–433.
24. Kim, K., Pant, P., Yamashita, E., Accidents and accessibility. Transp. Res. Rec. 2147 (2010), 9–17.
25. LaScala, E.A., Gerber, D., Gruenewald, P.J., Demographic and environmental correlates of pedestrian injury collisions: a spatial analysis. Accid. Anal. Prev. 32:5 (2000), 651–658.
26. Lee, J., Abdel-Aty, M., Jiang, X., Development of zone system for macro-level traffic safety analysis. J. Transport Geogr. 38:0 (2014), 13–21.
27. Lee, J., Abdel-Aty, M., Jiang, X., Multivariate crash modeling for motor vehicle and non-motorized modes at the macroscopic level. Accid. Anal. Prev. 78:0 (2015), 146–154.
28. Levine, N., Kim, K.E., Nitz, L.H., Spatial analysis of Honolulu motor vehicle crashes: II. Zonal generators. Accid. Anal. Prev. 27:5 (1995), 675–685.
29. 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.
30. Loo, B.P., Tsui, K., Bicycle crash casualties in a highly motorized city. Accid. Anal. Prev. 42:6 (2010), 1902–1907.
31. Lord, D., Mannering, F., The statistical analysis of crash-frequency data: a review and assessment of methodological alternatives. Transp. Res. Part A 44:5 (2010), 291–305.
32. MacNab, Y.C., Bayesian spatial and ecological models for small-area accident and injury analysis. Accid. Anal. Prev. 36:6 (2004), 1019–1028.
33. Moeinaddini, M., Asadi-Shekari, Z., Zaly Shah, M., The relationship between urban street networks and the number of transport fatalities at the city level. Saf. Sci. 62 (2014), 114–120.
34. Naderan, A., Shahi, J., Aggregate crash prediction models: introducing crash generation concept. Accid. Anal. Prev. 42:1 (2010), 339–346.
35. Ng, K.-s., Hung, W.-t., Wong, W.-g., An algorithm for assessing the risk of traffic accident. J. Saf. Res. 33:3 (2002), 387–410.
36. Noland, R.B., Quddus, M.A., Analysis of pedestrian and bicycle casualties with regional panel data. Transp. Res. Rec. 1897 (2004), 28–33.
37. Noland, R.B., Quddus, M.A., A spatially disaggregate analysis of road casualties in England. Accid. Anal. Prev. 36:6 (2004), 973–984.
38. Noland, R.B., Quddus, M.A., A spatially disaggregate analysis of road casualties in England. Accid. Anal. Prev. 36:6 (2004), 973–984.
39. Noland, R.B., Traffic fatalities and injuries: the effect of changes in infrastructure and other trends. Accid. Anal. Prev. 35:4 (2003), 599–611.
40. Nylund, K.L., Asparouhov, T., Muthén, B.O., Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct. Equ. Model. 14:4 (2007), 535–569.
41. Park, B.-J., Lord, D., Application of finite mixture models for vehicle crash data analysis. Accid. Anal. Prev. 41:4 (2009), 683–691.
42. Park, B.-J., Lord, D., Hart, J.D., Bias properties of Bayesian statistics in finite mixture of negative binomial regression models in crash data analysis. Accid. Anal. Prev. 42:2 (2010), 741–749.
43. Pucher, J., Buehler, R., Seinen, M., Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies. Transp. Res. Part A 45:6 (2011), 451–475.
44. Pucher, J., Cycling trends & policies in Canadian cities John Pucher & Ralph Buehler. World Transport Policy Pract. 11:1 (2005), 43–61.
45. Quddus, M.A., Modelling area-wide count outcomes with spatial correlation and heterogeneity: an analysis of London crash data. Accid. Anal. Prev. 40:4 (2008), 1486–1497.
46. Reynolds, C., Harris, M.A., Teschke, K., Cripton, P.A., Winters, M., The impact of transportation infrastructure on bicycling injuries and crashes: a review of the literature. Environ. Health, 8(1), 2009, 47.
47. Siddiqui, C., Abdel-Aty, M., Choi, K., Macroscopic spatial analysis of pedestrian and bicycle crashes. Accid. Anal. Prev. 45 (2012), 382–391.
48. Sobhani, A., Eluru, N., Faghih-Imani, A., A latent segmentation based multiple discrete continuous extreme value model. Transp. Res. Part B 58 (2013), 154–169.
49. Stamatiadis, N., Puccini, G., Socioeconomic descriptors of fatal crash rates in the Southeast USA. Inj. Control Saf. Promot. 7:3 (2000), 165–173.
50. Statistics Canada, 2011 Census of Population. 2011, Statistics Canada, Ottawa.
51. Turner, S., Francis, T., Roozenburg, A., Land Transport, N., Predicting Accident Rates for Cyclists and Pedestrians. 2006, Land Transport, New Zealand.
52. Ukkusuri, S., Hasan, S., Aziz, H., Random parameter model used to explain effects of built-environment characteristics on pedestrian crash frequency. Transp. Res. Rec. 2237 (2011), 98–106.
53. Ukkusuri, S., Miranda-Moreno, L.F., Ramadurai, G., Isa-Tavarez, J., The role of built environment on pedestrian crash frequency. Saf. Sci. 50:4 (2012), 1141–1151.
54. Wedel, M., DeSarbo, W.S., Bult, J.R., Ramaswamy, V., A latent class Poisson regression model for heterogeneous count data. J. Appl. Econometr. 8:4 (1993), 397–411.
55. Wei, F., Lovegrove, G., An empirical tool to evaluate the safety of cyclists: community based: macro-level collision prediction models using negative binomial regression. Accid. Anal. Prev. 61 (2013), 129–137.
56. Wier, M., Weintraub, J., Humphreys, E.H., Seto, E., Bhatia, R., An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accid. Anal. Prev. 41:1 (2009), 137–145.
57. Yasmin, S., Eluru, N., Bhat, C.R., Tay, R., A latent segmentation based generalized ordered logit model to examine factors influencing driver injury severity. Anal. Methods Accid. Res. 1 (2014), 23–38.
58. Zou, Y., Zhang, Y., Lord, D., Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models. Anal. Methods Accid. Res. 1 (2014), 39–52.