Modeling and evaluating safety impacts of access management features in the Las Vegas, Nevada, Valley

Timur Mauga, Mohamed Kaseko

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


This paper presents results of a study that developed statistical models that relate access management (AM) features to traffic safety in midblock sections of street segments. The objective of the study was to evaluate and quantify the impact of the AM features on traffic crashes in the midblock sections. Models were calibrated for two main types of median treatments for street segments: raised medians (RM) and two-way left-turn lanes (TWLTL). Other AM features considered were signal spacing and the densities of driveways, median openings, and unsignalized crossroads. Separate models were developed to determine the impact on total crash rates and types and severity of crashes. The study results confirmed the intuitive expectation that these AM features do have a significant impact on safety. They show that the crash rate of segments with RM was lower by 23% as compared with segments with TWLTL. The results also showed that higher densities of driveways, unsignalized crossroads, and median openings resulted in higher crash rates and severity. For example, for segments with RM, each additional median opening per mile resulted in a 4.7% increase in the total crash rate. These results are compared with the results of previous similar studies. It is anticipated that the results of this study will assist local jurisdictions in the Las Vegas, Nevada, Valley in developing new AM policies and programs.

Original languageEnglish
Pages (from-to)57-65
Number of pages9
JournalTransportation Research Record
Issue number2171
Publication statusPublished - Jan 12 2010
Externally publishedYes

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering


Dive into the research topics of 'Modeling and evaluating safety impacts of access management features in the Las Vegas, Nevada, Valley'. Together they form a unique fingerprint.

Cite this