Impact of Optimally Minimizing Delay Times on Safety at Signalized Intersections in Urban Areas, Case Study: The City of Virginia Beach

Optimally minimizing delay times at signalized intersections can significantly improve both traffic flow and safety.However, most traffic flow optimizing tools do not measure the effect on safety. This study uses nonlinear programming(NLP) algorithms to optimally minimize delay times and employs both Safety performance functions (SPFs)and empirical Bayes (EB) before-after methodology to measure the impact on safety presented as a Crash ModificationFactor (CMF). A crash modification factor (CMF) is a multiplicative factor used by transportation practitionersto compute the expected number of crashes at specific study site(s) after a countermeasure has been proposed or isimplemented. Using 2013 traffic data from seventeen signalized intersections located in Virginia Beach, the resultsshow that optimally minimizing intersection delay times can result in a safety improvement of approximately 26.46%that is a CMF of 0.735. This result is not conclusive, but the significance of the findings shows the need for furtherinvestigations and potential inclusion in the future editions of the Highway Safety Manual (HSM).

Impact of Optimally Minimizing Delay Times on Safety at Signalized Intersections in Urban Areas, Case Study: The City of Virginia Beach Keywords:

Safety , crash modification factors , delay , safety performance functions , empirical bayes