Traffic analysis zone level crash estimation models based on land use characteristics

• Published in: Accident analysis and prevention 2013-01, Vol.50, p.678-687
• Main Authors: Pulugurtha, Srinivas S., Duddu, Venkata Ramana, Kotagiri, Yashaswi
• Format: Article
• Language: English
• Subjects: Accidents, Traffic - statistics & numerical data; Automobile Driving; Biological and medical sciences; Correlation; Crash; Crashes; Environment Design; Estimation; GLM; Humans; Injury Severity Score; Land use; Land use characteristics; Mathematical models; Medical sciences; Miscellaneous; Models, Statistical; Negative binomial; North Carolina - epidemiology; Prevention and actions; Public health. Hygiene; Public health. Hygiene-occupational medicine; Residential; Residential areas; Risk Assessment; Safety; Traffic analysis zone (TAZ); Traffic engineering; Traffic flow; Urban Population; Wounds and Injuries - epidemiology
• ISSN: 0001-4575; 1879-2057
• DOI: 10.1016/j.aap.2012.06.016

► Maintaining a delicate balance between different land uses in a traffic analysis zone (TAZ) or area helps improve safety and maximize derived benefits. ► Mixed use development, urban residential, multi-family residential, business and office district areas are strongly associated with an increase in crashes in a TAZ. ► TAZs with single-family residential area tend to have a neutralizing effect on crashes. ► Institutional, industrial and research district areas are strongly associated with injury crashes. 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. Demographic/socio-economic characteristics such as population, the number of household units and employment, traffic indicators such as trip productions and attractions, and, on-network characteristics such as center-lane miles by speed limit were observed to be correlated to land use characteristics, and, hence were not considered in the development of TAZ level crash estimation models. Urban residential commercial, rural district and mixed use district land use variables were observed to be correlated to other land use variables and were also not considered in the development of the models. Results obtained indicate that land use characteristics such as mixed use development, urban residential, single-family residential, multi-family residential, business and, office district are strongly associated and play a statistically significant role in estimating TAZ level crashes. 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.