Project Title:
Crash Risk Reduction at Signalized Intersections Using Longitudinal Data

Project Objective:
In an on-going study, Burkey and Obeng attempt to resolve problems with the earlier studies by using a large data set for Greensboro, North Carolina. Working with the traffic-engineering department of the City of Greensboro, North Carolina Department of Transportation and the Highway Safety Research Institute, these researchers have collected and are analyzing a large data set on intersection accidents that include red light cameras as a variable.

Project Abstract:
Small urban areas currently rely on automobile traffic as the primary means of transportation.  As such, these areas are faced with the struggle of keeping traffic flowing as quickly and smoothly as possible, while also attempting to keep costs low and safety high.  Because nearly half of all accidents occur at or near intersections, more detailed research is needed to investigate the characteristics of drivers, intersections, and enforcement that can ameliorate the accident problem.  This proposal will build on previous research by this team on accidents at intersections (which focused primarily on the efficacy of Automate Red Light Cameras).  Taking advantage of data previously collected on the properties of intersections, this project will add additional data on the characteristics of the drivers  (e.g. age, alcohol, and seatbelt use), land use surrounding the intersection (e.g. residential, light industrial), and vehicle characteristics (e.g. type of vehicle, speed, and damage estimates).  Additionally, we will include more recent data to extend the existing time series from 45 months to 57 months.  The goals of this project are to identify which of these characteristics may indicate an increased likelihood of being involved in an accident, or sustaining an injury given that an accident has occurred.  Lastly, we will extend our previous research involving Red Light Cameras, assessing the impact of the additional data on previous results.  The results of this study will be shared with both the academic community and practicing engineers in publications and at conferences. 

Technology Transfer Activities:
Technology transfer activities will be performed while awaiting the comments of reviewers. These activities will primarily focus on using the results in preparing press releases, journal articles for submission and possible acceptance for publication. This will also offer the opportunity to review the models and make changes if necessary. In addition, results of this research will be presented at conferences.  In the past, research by this team has been presented at the Southeastern Local Roads Conference sponsored by the LTAP, and we will present our results at similar conferences in the future.

Potential Benefits of the Project:
We expect our results will accomplish two main goals that can be used widely. By completing the study, many urban areas will have some guidance for improving signalized intersections to reduce accidents. Furthermore, it will provide additional information about the efficacy of red light cameras in terms of intersection choice. This is because most companies contracted to provide RLC systems derive revenue on a citation basis, and choose which intersections will be monitored. This makes their goals incongruent with those of transportation planners. As a part of our statistical analysis, we will evaluate the current set of locations of cameras as compared with other sites, which we were unable to do in our current study because of its limited scope.

The results of this research will benefit all communities by allowing them to better understand the factors that contribute to the types and severity of accidents that occur at intersections. This will allow public education programs to be developed with the goal of reducing accidents. Additionally, this project will add much-needed empirical evidence on the effectiveness of some characteristics of intersections and red lights that reduce accidents.