01657516

Component

The authors propose in this paper a spatial random coefficients flexible multivariate count model to examine, at the spatial level of a census tract, the number of pedestrian injuries by injury severity level. The authors' model, unlike many other macro-level pedestrian injury studies in the literature, explicitly acknowledges that risk factors for different types of pedestrian injuries can be very different, as well as accounts for unobserved heterogeneity in the risk factor effects. The authors also recognize the multivariate nature of the injury counts by injury severity level within each census tract (as opposed to independently modeling the count of pedestrian injuries by severity level). The data for the authors' analysis is drawn from a 2009 pedestrian crash database from the Manhattan region of New York City. Several groups of census tract-based risk factors are considered in the empirical analysis based on earlier research. The empirical analysis sheds light on both engineering as well as behavioral countermeasures to reduce the number of pedestrian vehicle crashes by severity of these crashes.

This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.

18-04741

English

0000-0002-0715-8121

14p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Maps; References

Crash data; Databases; Injury severity; Mathematical models; Multivariate analysis; Pedestrian vehicle crashes; Pedestrians

Manhattan (New York, New York)

Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors

Transportation Research Board Annual Meeting 2018 Paper #18-04741

TRIS, TRB, ATRI

Jan 8 2018 11:10AM