Calibration of Microsimulation Models for Multimodal Freight Networks.

摘要

This research presents a framework for incorporating the unique operating characteristics of multi-modal freight networks into the calibration process for microscopic traffic simulation models. Because of the nature of heavy freight movements in US DOT Region VII (Nebraska, Iowa, Missouri, Kansas), the focus of the project is on heavy gross vehicles (HGV), or, trucks. In particular, a genetic algorithm (GA) based optimization technique was developed and used to find optimum parameter values for the vehicle performance model used by Verkehr In Staedten-SIMulationmodell (VISSIM), a widely used microscopic traffic simulation software. At present, the Highway Capacity Manual (HCM), which is the most common reference for analyzing the operational characteristics of highways, only provides guidelines for highway segments where the heavy vehicle percentages are 25 or less. However, significant portions of many highways, such as Interstate 80 (I-80) in Nebraska, have heavy vehicle percentages greater than 25 percent. Therefore, with the anticipated increase in freight-moving truck traffic, there is a real need to be able to use traffic micro-simulation models to effectively recreate and replicate situations where there is significant heavy vehicle traffic. The procedure developed in this research was successfully applied to the calibration of traffic operations on a section of I-80 in California. For this case study, the calibrated model provided more realistic results than the uncalibrated model (default values) and reaffirmed the importance of calibrating microscopic traffic simulation models to local conditions.