The development and the calibration of a microscopic traffic simulation model, using MITSIMLab, for the entire metropolitan area of Des Moines, Iowa, are presented. The primary contributions include the application of a microscopic model on such a large-scale network and an effort for joint calibration of the model parameters and estimation of origin-destination flows. The application of microscopic traffic simulation models to very large networks such as this poses a number of methodological and practical challenges that are not faced with smaller applications. Solutions to these problems are both heuristic and analytical. The solutions presented are generic and hence applicable to any large-scale microscopic traffic modeling.
According to the Iowa Department of Transportation's crash database (GIS-ALAS), between 5% and 10% of all crashes in Iowa occur at commercial driveways. Most of these occur at arterials within municipalities. In recent years, nearly one-quarter of these crashes occurred in the Des Moines metropolitan area, making the area a prime candidate for improved access management. Case study research in Iowa has shown that access management is an effective highway safety tool: well-managed routes can be 40% to 50% safer than poorly managed routes. The Des Moines metropolitan area has many miles of older arterials that were constructed before access management was considered. This paper describes a cooperative effort of the Des Moines Area Metropolitan Planning Organization and the Center for Transportation Research and Education at Iowa State University to develop an access management study and program for the Des Moines metro area. The overall goal of the study is to use the knowledge developed to make improvements that will reduce access-related crashes. This project will also help local officials better consider access to avoid future safety and operational problems. The major task described in this paper was to identify and rank the Des Moines metro area's access management problems by using Iowa's GIS-ALAS database and other geospatial data. This process was developed to identify arterial segments in the metro area most promising for further investigation with regard to access management.
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