Calibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation Procedures

1 2 ABSTRACT 3 4 The weather-sensitive Traffic Estimation and Prediction System (TrEPS) aims to accurately 5 estimate and predict traffic state under inclement weather conditions. Successful application 6 of weather-sensitive TrEPS requires detailed calibration of weather effects on traffic flow 7 model. In this paper, systematic procedures of the entire calibration process are developed, 8 from data collection, through model parameter estimation, to model validation. Following the 9 procedures, dual-regime modified Greenshields model and weather adjustment factors are 10 calibrated for four metropolitan areas across the United States (Irvine, Chicago, Salt Lake 11 City, and Baltimore), using freeway loop detector traffic data and weather data obtained from 12 Automated Surface Observing System (ASOS) stations. It is observed that visibility and 13 precipitation (rain/snow) intensity have significant impacts on the value of some traffic flow 14 model parameters, such as free flow speed and maximum flow rate; while these impacts can 15 be included in weather adjustment factors. The calibrated models are fed as input into 16 weather integrated dynamic traffic assignment simulation system. The results show that the 17 calibrated models are capable of capturing the weather effects on traffic flow more 18 realistically than TrEPS without weather integration.