Modeling the Impact of Inclement Weather on Freeway Traffic Speed at Macroscopic and Microscopic Levels

Abstract

Inclement weather conditions, such as snowy and icy conditions, could have major impacts on driver behavior and on the performance of surface transportation systems. Recently, researchers have had an increased interest in understanding this impact better as well as in modeling it. This study contributes to the emerging literature in the impact of snowy and icy conditions on traffic and driver behavior by modeling the impact of inclement weather on freeway traffic speed, at both the macroscopic and microscopic levels, with data from Buffalo, New York. At the macroscopic level, freeway speed data observed on a Buffalo section of the New York State Thruway were correlated to a set of weather indices introduced by the study; the result was a regression model that could be used to estimate the average freeway speed as a function of weather conditions. At the microscopic level, the study was the first attempt to calibrate a cellular-automata traffic simulation model, specifically, the TRANSIMS model, to inclement weather (i.e., snowy) conditions. For the calibration of TRANSIMS, a vehicle equipped with a Global Positioning System collected second-by-second vehicle dynamics information during both normal and snowy weather conditions. The collected information was the basis for the adjustment of several of the TRANSIMS model parameters. The adjusted parameters enabled the model to closely replicate observed traffic flow parameters at both the macroscopic and microscopic scales.