17 resultados para data transportation

em Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States


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The objective of this research was to develop a methodology for transforming and dynamically segmenting data. Dynamic segmentation enables transportation system attributes and associated data to be stored in separate tables and merged when a specific query requires a particular set of data to be considered. A major benefit of dynamic segmentation is that individual tables can be more easily updated when attributes, performance characteristics, or usage patterns change over time. Applications of a progressive geographic database referencing system in transportation planning are vast. Summaries of system condition and performance can be made, and analyses of specific portions of a road system are facilitated.

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The object of this report is to present the data and conclusions drawn from the analysis of the origin and destination information. Comments on the advisability and correctness of the approach used by Iowa are encouraged.

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The purposes of this report (Phase II of the project) are to specify in mathematical form the individual modules of the conceptual model developed in Phase I, to identify and evaluate sources of data for the model set, and to develop the transport networks necessary to support the models.

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Laser scanning is a terrestrial laser-imaging system that creates highly accurate three-dimensional images of objects for use in standard computer-aided design software packages. This report describes results of a pilot study to investigate the use of laser scanning for transportation applications in Iowa. After an initial training period on the use of the scanner and Cyclone software, pilot tests were performed on the following projects: intersection and railroad bridge for training purposes; section of highway to determine elevation accuracy and pair of bridges to determine level of detail that can be captured; new concrete pavement to determine smoothness; bridge beams to determine camber for deck-loading calculations; stockpile to determine volume; and borrow pit to determine volume. Results show that it is possible to obtain 2-6 mm precision with the laser scanner as claimed by the manufacturer compared to approximately one-inch precision with aerial photogrammetry using a helicopter. A cost comparison between helicopter photogrammetry and laser scanning showed that laser scanning was approximately 30 percent higher in cost depending on assumptions. Laser scanning can become more competitive to helicopter photogrammetry by elevating the scanner on a boom truck and capturing both sides of a divided roadway at the same time. Two- and three-dimensional drawings were created in MicroStation for one of the scanned highway bridges. It was demonstrated that it is possible to create such drawings within the accuracy of this technology. It was discovered that a significant amount of time is necessary to convert point cloud images into drawings. As this technology matures, this task should become less time consuming. It appears that laser scanning technology does indeed have a place in the Iowa Department of Transportation design and construction toolbox. Based on results from this study, laser scanning can be used cost effectively for preliminary surveys to develop TIN meshes of roadway surfaces. It also appears that this technique can be used quite effectively to measure bridge beam camber in a safer and quicker fashion compared to conventional approaches. Volume calculations are also possible using laser scanning. It seems that measuring quantities of rock could be an area where this technology would be quite beneficial since accuracy is more important with this material compared to soil. Other applications for laser scanning could include developing as-built drawings of historical structures such as the bridges of Madison County. This technology could also be useful where safety is a concern such as accurately measuring the surface of a highway active with traffic or scanning the underside of a bridge damaged by a truck. It is recommended that the Iowa Department of Transportation initially rent the scanner when it is needed and purchase the software. With time, it may be cost justifiable to purchase the scanner as well. Laser scanning consultants can be hired as well but at a higher cost.

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Building on the policy directions advanced in the publication "Policy Strategies for Iowa in Making Major Road Investments", this report defines each policy issue and discusses how transportation can play a role in addressing it. Perspectives from several focus group meetings conducted in nine communities in Iowa are discussed. The report also examines available data pertaining to the issues. Finally, the report presents several specific recommendations dealing with issues on economic development, safety, choice of transportation modes, and financing transportation in the future. The recommendations are directed at proving the Iowa Transportation Commission with the best possible insights to be used in making investment decisions that will impact the quality of life in Iowa in future years.

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The objective of the evaluation of the weather forecasting services used by the Iowa Department of Transportation is to ascertain the accuracy of the forecasts given to maintenance personnel and to determine whether the forecasts are useful in the decision-making process and whether the forecasts have potential for improving the level of service. The Iowa Department of Transportation has estimated the average cost of fighting a winter storm to be about $60,000 to $70,000 per hour. This final report is to provide an evaluation report describing the collection of weather data and information associated with the weather forecasting services provided to the Iowa Department of Transportation and its maintenance activities and to determine their impact in winter maintenance decision-making.

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This report evaluates the use of remotely sensed images in implementing the Iowa DOT LRS that is currently in the stages of system architecture. The Iowa Department of Transportation is investing a significant amount of time and resources into creation of a linear referencing system (LRS). A significant portion of the effort in implementing the system will be creation of a datum, which includes geographically locating anchor points and then measuring anchor section distances between those anchor points. Currently, system architecture and evaluation of different data collection methods to establish the LRS datum is being performed for the DOT by an outside consulting team.

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Summaries of the data gathered for this project.

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In an effort to achieve greater consistency and comparability in state‐wide seat belt use reporting, the National Highway Traffic Safety Administration (NHTSA) issued new requirements in 2011 for observing and reporting future seat belt use. The requirements included the involvement of a qualified statistician in the sampling and weighting portions of the process as well as a variety of operational details. The Iowa Governor’s Traffic Safety Bureau contracted with Iowa State University’s Survey & Behavioral Research Services (SBRS) in 2011 to develop the study design and data collection plan for the State of Iowa annual survey that would meet the new requirements of the NHTSA. A seat belt survey plan for Iowa was developed by SBRS with statistical expertise provided by Zhengyuan Zhu, Ph.D., Associate Professor of Statistics at Iowa State University. The Iowa plan was submitted to NHTSA in December of 2011 and official approval was received on March 19, 2012.

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The Data Processing Department of ISHC has developed coding forms to be used for the data to be entered into the program. The Highway Planning and Programming and the Design Departments are responsible for coding and submitting the necessary data forms to Data Processing for the noise prediction on the highway sections.

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In February 2001, all 3,595 employees of the Iowa Department of Transportation (IDOT) were invited to participate in a survey related to job satisfaction and work practices. This survey partially replicated assessments made by random, stratified samples of IDOT employees in 1984, 1988, and 1993. The present survey was designed to allow for generalizations about all IDOT employees and various subgroups of employees (i.e., majority and minority employees, males and females, and employees less than 40 years of age and those 40 years of age or older).

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In June 1988, 1341 employees of the Iowa State Department of Transportation (DOT) were surveyed via a mailed questionnaire. The sample was selected such that conclusions about all DOT employees, male employees, female employees, majority employees; minority employees, employees under age 40, and employees 40 years of age or older could be made. These sampling characteristics were chosen in order to facilitate comparisons between current DOT employee attitudes and employee attitudes evaluated in 1984. In addition, the sample size and response rates were sufficiently high that conclusions could be made about each of the six districts, the Ames Highway Division, and the Ames complex, excluding the Highway Division. Altogether fifty-five percent (or 739) questionnaires were· returned. Thirty additional employees voluntarily completed the survey, resulting in a final sample size of 769. The survey covered topics related to job satisfaction, work environment or climate, skill utilization, sexual harassment, communication and information adequacy, and morale. The first four topics were evaluated in 198- while the last two were unique to this survey.

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In March 1993, all 3, 666 employees of the Iowa Department of Transportation (DOT) were invited to participate in a survey related to morale and work practices. Survey questionnaires were sent to employees / homes and participation in the study was voluntary. This survey, in part, replicates assessments made by random, stratified samples of DOT employees in 1984 and 1988. Thus it is possible to evaluate some changes in morale and work practices at three points in time. The present survey was designed to allow for generalizations about all DOT employees and various subgroups of employees (i.e., majority and minority employees, males and females, employees less than 40 years of age and those 40 years of age or older, and work area location). Altogether, 2249 usable questionnaires were returned, yielding a much higher-than-average response rate 61.3%.

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Advances in communication, navigation and imaging technologies are expected to fundamentally change methods currently used to collect data. Electronic data interchange strategies will also minimize data handling and automatically update files at the point of capture. This report summarizes the outcome of using a multi-camera platform as a method to collect roadway inventory data. It defines basic system requirements as expressed by users, who applied these techniques and examines how the application of the technology met those needs. A sign inventory case study was used to determine the advantages of creating and maintaining the database and provides the capability to monitor performance criteria for a Safety Management System. The project identified at least 75 percent of the data elements needed for a sign inventory can be gathered by viewing a high resolution image.

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In an effort to achieve greater consistency and comparability in state-wide seat belt use reporting, the National Highway Traffic Safety Administration (NHTSA) issued new requirements in 2011 for observing and reporting future seat belt use. The requirements included the involvement of a qualified statistician in the sampling and weighting portions of the process as well as a variety of operational details. The Iowa Governor’s Traffic Safety Bureau contracted with Iowa State University’s Survey & Behavioral Research Services (SBRS) in 2011 to develop the study design and data collection plan for the State of Iowa annual survey that would meet the new requirements of the NHTSA. A seat belt survey plan for Iowa was developed by SBRS with statistical expertise provided by Zhengyuan Zhu, Ph.D., Associate Professor of Statistics at Iowa State University and was approved by NHTSA on March 19, 2012.