AbstractVariable speed limit (VSL) and variable advisory speed (VAS) signs are efficient, cost-effective and among the state-of-the-art active traffic management (ATM) strategies. They adopt the idea of dynamically changing posted speed limits to improve highway safety performance and operation by harmonizing traffic speed. VSL/VAS system involves changing speed limits according to real-time traffic events and weather conditions. Hence, traditional average annual daily traffic (AADT) based crash prediction models may not capture the temporal effect of traffic characteristics due to the high level of aggregation. To address this issue, short-term safety performance functions (SPFs) with aggregation levels of average annual weekday hourly traffic (AAWDHT) and average annual weekday peak traffic (AAWDPT) along with AADT-based SPFs were developed using high-resolution traffic detector and VSL/VAS operational data. In this study, the Poisson log-normal model performed well at each level of aggregation and thus is recommended for developing short-term SPFs. In line with previous studies, traffic volume and standard deviation of speed were found to be positively associated with crash frequency in all the estimated models. In addition, it was found that implementation of VSL/VAS significantly reduced crash frequency by 15.97% and 26.14% for the AAWDHT and AAWDPT models, respectively. The safety improvement was captured in the short-term models in a more distinguished way than in the highly aggregated AADT-based model. The findings of this study pave the way for practitioners and policymakers to evaluate and select important parameters for VSL/VAS strategy implementation on freeways.