Accident; analysis and prevention
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Governments aim to promote a shift from car to bicycle, but concerns about road safety seem to represent an important argument against this encouragement. This study examines the road safety impact of a modal shift from short car trips to cycling in Dutch municipalities. The road safety effect is estimated using Accident Prediction Models (APMs) that account for the non-linearity of risk. ⋯ The neutral effect on fatalities, despite the high fatality risk for cyclists, can be explained by there being fewer cars on the road to pose a risk to others, the shorter length of bicycle trips compared to the car trips they replace, and the "safety in numbers" phenomenon. The rise in the number of serious road injuries is due wholly to the high number of cycling crashes with no other vehicle involved. The effect of a modal shift is dependent on the age of the population in which the shift is concentrated, and can be influenced by measures affecting cyclists' injury risk.
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The objective of this paper is to develop crash estimation models at traffic analysis zone (TAZ) level as a function of land use characteristics. Crash data and land use data for the City of Charlotte, Mecklenburg County, North Carolina were used to illustrate the development of TAZ level crash estimation models. Negative binomial count models (with log-link) were developed as data was observed to be over-dispersed. ⋯ The coefficient for single-family residential area was observed to be negative, indicating a decrease in the number of crashes with an increase in single-family residential area. Models were also developed to estimate these crashes by severity (injury and property damage only crashes). The outcomes can be used in safety conscious planning, land use decisions, long range transportation plans, and, to proactively apply safety treatments in high risk TAZs.