01698132

Component

Road traffic fatality rate has long served as a regular indicator to evaluate and compare road safety performances for different administrative divisions. This article introduced a novel method known as spatial Markov chains model to incorporate the spatial effects into the temporal dynamic of the fatality rates. Comparing with the traditional Markov chains model, the proposed spatial Markov chains model can quantify the influence of neighboring sites explicitly in the transition process. A case study using a long time span dataset from 1975 to 2015 in the 48 lower states of the United States was conducted to illustrate the proposed model. The fatality rates were measured as the number of traffic fatalities per 100 million vehicle miles or per 10,000 residents. Our results show that the probability of transition for one state between different levels of traffic fatality risks depends largely on the context of its surrounding neighbors. Another important finding is that relative to the estimates of traditional Markov chains model, states surrounded by neighborhoods with relatively low fatality rates takes a longer time to transform to a higher level of fatality risk in the spatial Markov chains model, whereas those with high risk neighborhoods takes less time to deteriorate. These findings confirm that it is imperative to incorporate spatial effects when modeling the temporal dynamic of safety indicators to assess and monitor the safety trends of the areas of interests.

This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation. Alternate title: Incorporating Spatial Effects into Temporal Dynamic of Traffic Fatality Risks: A Case Study on Lower States of the USA, 1975-2015.

19-03389

English

21p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Case studies; Fatalities; Highway traffic; Risk; Risk assessment; Spatial analysis; Trend (Statistics)

United States

Data and Information Technology; Highways; Safety and Human Factors

Transportation Research Board Annual Meeting 2019 Paper #19-03389

TRIS, TRB, ATRI

Dec 7 2018 9:47AM