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Affiliation
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Gachon University , College of Social Science , Department of Health Care Management , Seong Nam , Republic of Korea. |
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Abstract
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OBJECTIVE: In 2012, 4,743 pedestrians were killed in the U.S., representing 14 percent of total traffic fatalities. The number of pedestrians injured was higher at 76,000. Therefore, 36 out of 52 of the largest cities in the U.S. have adopted a citywide target of reducing pedestrian fatalities. The number of cities adopting the reduction goal during 2011 and 2012 increased rapidly with 8 more cities. We examined the scaling relationship of pedestrian fatality counts as a function of the population size of 115 to 161 large U.S cities during the period of 1994 to 2011. We also examined the scaling relationship of non-pedestrian and total traffic fatality counts as function of the population size as well.
METHODS: For the data source of fatality measures we used Traffic Safety Facts FARS/GES ANNUAL Report published each year from 1994 to 2011 by National Highway Traffic Safety Administration. Using the data source we conducted both annual cross-sectional and panel data bivariate and multivariate regression models. In the construction of the estimated functional relationship between traffic fatality measures and various factors, we used the simple power function for urban scaling used by Bettencourt et al. ( 2007 ; 2010) and the refined STIRPAT(STochastic Impacts by Regression on Population, Affluence, and Technology) model used in Dietz and Rosa ( 1994 ; 1997) and York et al. (2003).
RESULTS: We found the scaling relationship display diseconomies of scale or sublinear for pedestrian fatalities. However, the relationship displays superlinear relationship in case of non-pedestrian fatality. The scaling relationship for total traffic fatality counts display a near linear pattern. When the relationship was examined by the four subgroups of cities with different population sizes, the most pronounced sublinear scaling relationships for all three types of fatality counts was discovered for the subgroup of mega cities with a population of more than 1 million.
CONCLUSIONS: The scaling patterns of traffic fatalities of subgroups of cities depend on population sizes of the cities in subgroups. Especially 9 mega cities with populations of more than 1 million are significantly different from the remaining cities and should be viewed as a totally separate group. Thus, the analysis on the patterns of traffic fatalities needs to be conducted within the group of mega cities separately from the other cities with smaller population sizes for devising prevention policies to reduce traffic fatalities of both group of mega cities and the other group of smaller cities.
Language: en |