A case for real-time calibration of data-driven microscopic traffic simulation tools

Despite recent technological advancements in alleviating roadway congestion, there is still a considerable amount of time and fuel wasted by travelers. In searching for solutions to mitigate congestion, a number of research efforts have been geared toward developing simulation tools to provide real-time performance measures. One of the challenges of such tools is that the underlying simulation model does not always adequately reflect field conditions outside of the time period for which it was calibrated. In this paper, this is highlighted when calibrating a model for two different periods. During this exercise, 1000 model replicates were generated to explore the sensitivity of potential calibration parameter values. From this analysis only one replicate was found to be adequately calibrated for both periods. This paper suggests that a real-time calibration algorithm should be included in online, data-driven microscopic traffic simulation tools.