Modeling Inclement Weather Impacts on Traffic Stream Behavior

Abstract

The research identifies the steady-state car-following model parameters within state-of-the-practice traffic simulation software that require calibration to reflect inclement weather and roadway conditions. The research then develops procedures for calibrating non-steady state car-following models to capture inclement weather impacts and applies the procedures to the INTEGRATION software on a sample network. The results demonstrate that the introduction of rain precipitation results in a 5% reduction in light-duty vehicle speeds and a 3% reduction in heavy-duty vehicle speeds. An increase in the rain intensity further reduces light-duty vehicle and heavy-duty truck speeds resulting in a maximum reduction of 9.5% and 5.5% at the maximum rain intensity of 1.5 cm/h, respectively. The results also demonstrate that the impact of rain on traffic stream speed increases with the level of congestion and is more significant than speed differences attributed to various traffic operational improvements and thus should be accounted for in the analysis of alternatives. In the case of snow precipitation, the speed reductions are much more significant (in the range of 55%). Furthermore, the speed reductions are minimally impacted by the snow precipitation intensity. The study further demonstrates that precipitation intensity has no impact on the relative merit of various scenarios (i.e. the ranking of the scenario results are consistent across the various rain intensity levels). This finding is important given that it demonstrates that a recommendation on the optimal scenario is not impacted by the weather conditions that are considered in the analysis.