Iowa Department of Transportation Performance Results Achieved for Fiscal Year 2009

The DOT monitors performance of five core functions, under which are eight services, products and activities (SPAs). In all, 56 measures are used to monitor the core functions and SPAs in the DOT’s performance plan. (See Iowa DOT Performance Report – FY2009, pages 1A-9A.) Overall, DOT’s performance was good in fiscal year 2009. Of the 56 measures in the DOT’s performance plan, 43 measures (77%) met or exceeded their targets. Of the 13 measures falling short, ten were within four percent of their target. This means 95 percent of DOT measures met or exceeded 96 percent of their preset target. Performance measures monitoring the core functions of Physical Asset Management and Resource Management showed the DOT did a good job managing resources. A total of 11 of the 14 (79%) core function and SPA measures met or exceeded their predetermined targets. Two of the three measures falling short were within four percent of its target. Core function and SPA measures within the Transportation Systems core function indicated good performance. A total of 22 of the 30 (73%) core function and SPA measures met or exceeded their predetermined targets. Overall, six of the eight measures falling short were within four percent of their target. Performance measures monitoring the core functions of Enforcement and Investigation and Regulation and Compliance showed the DOT performed well. A total of 10 of the 12 (83%) core function and SPA measures met or exceeded their predetermined targets. Both of the measures falling short were within four percent of their target.

Visualization Resources for Iowa State University and the Iowa DOT: An Automated Design Model to Simulator Converter, November 2012

This project developed an automatic conversion software tool that takes input a from an Iowa Department of Transportation (DOT) MicroStation three-dimensional (3D) design file and converts it into a form that can be used by the University of Iowa’s National Advanced Driving Simulator (NADS) MiniSim. Once imported into the simulator, the new roadway has the identical geometric design features as in the Iowa DOT design file. The base roadway appears as a wireframe in the simulator software. Through additional software tools, textures and shading can be applied to the roadway surface and surrounding terrain to produce the visual appearance of an actual road. This tool enables Iowa DOT engineers to work with the universities to create drivable versions of prospective roadway designs. By driving the designs in the simulator, problems can be identified early in the design process. The simulated drives can also be used for public outreach and human factors driving research.

Visualization Resources for Iowa State University and the Iowa DOT: An Automated Design Model to Simulator Converter, November 2012

The creation of three-dimensional (3D) drawings for proposed designs for construction, re-construction and rehabilitation activities are becoming increasingly common for highway designers, whether by department of transportation (DOT) employees or consulting engineers. However, technical challenges exist that prevent the use of these 3D drawings/models from being used as the basis of interactive simulation. Use of driving simulation to service the needs of the transportation industry in the US lags behind Europe due to several factors, including lack of technical infrastructure at DOTs, cost of maintaining and supporting simulation infrastructure—traditionally done by simulation domain experts—and cost and effort to translate DOT domain data into the simulation domain.

Visualization Resources for Iowa State University and the Iowa DOT: An Automated Design Model to Simulator Converter, November 2012

The creation of three-dimensional (3D) drawings for proposed designs for construction, re-construction and rehabilitation activities are becoming increasingly common for highway designers, whether by department of transportation (DOT) employees or consulting engineers. However, technical challenges exist that prevent the use of these 3D drawings/models from being used as the basis of interactive simulation. Use of driving simulation to service the needs of the transportation industry in the US lags behind Europe due to several factors, including lack of technical infrastructure at DOTs, cost of maintaining and supporting simulation infrastructure—traditionally done by simulation domain experts—and cost and effort to translate DOT domain data into the simulation domain.

Development of a New Process for Determining Design Year Traffic Demands, TR-528, 2007

Researchers should continuously ask how to improve the models we rely on to make financial decisions in terms of the planning, design, construction, and maintenance of roadways. This project presents an alternative tool that will supplement local decision making but maintain a full appreciation of the complexity and sophistication of today’s regional model and local traffic impact study methodologies. This alternative method is tailored to the desires of local agencies, which requested a better, faster, and easier way to evaluate land uses and their impact on future traffic demands at the sub-area or project corridor levels. A particular emphasis was placed on scenario planning for currently undeveloped areas. The scenario planning tool was developed using actual land use and roadway information for the communities of Johnston and West Des Moines, Iowa. Both communities used the output from this process to make regular decisions regarding infrastructure investment, design, and land use planning. The City of Johnston case study included forecasting future traffic for the western portion of the city within a 2,600-acre area, which included 42 intersections. The City of West Des Moines case study included forecasting future traffic for the city’s western growth area covering over 30,000 acres and 331 intersections. Both studies included forecasting a.m. and p.m. peak-hour traffic volumes based upon a variety of different land use scenarios. The tool developed took goegraphic information system (GIS)-based parcel and roadway information, converted the data into a graphical spreadsheet tool, allowed the user to conduct trip generation, distribution, and assignment, and then to automatically convert the data into a Synchro roadway network which allows for capacity analysis and visualization. The operational delay outputs were converted back into a GIS thematic format for contrast and further scenario planning. This project has laid the groundwork for improving both planning and civil transportation decision making at the sub-regional, super-project level.

Multimodal Investment Analysis Methodology, Phase One: The Conceptual Model, 1998

The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.