Institute for Transportation

About the research

CTRE is a subcontractor to the University of Missouri – Columbia on the project: Research Utilizing the SHRP2 Safety Data to Support Highway Safety.

About the research

Helikite-based platform is a prototype Unmanned Aerial Vehicle (UAV) for remote sensing applications, deployed via a helium-filled balloon. Control software and hardware were developed enabling real-time video surveillance and operation of an integrated high-resolution digital camera. System development includes printed circuit-board production, programming of single-board computer, and integration of radio telemetry modules, wireless video transmitter, and power sub-systems. The system can be used to monitor traffic and safety projects from as high as 500 feet.

About the research

Winter maintenance, particularly snow removal and the stress of snow removal materials on public structures, is an enormous budgetary burden on municipalities and nongovernmental maintenance organizations in cold climates. Lately, geo-spatial technologies such as remote sensing, geographical information systems (GIS), and decision support tools are providing valuable assistance in planning snow removal operations. A few researchers recently used geo-spatial technologies for the development of winter maintenance tools. However, most of these winter maintenance tools, while having the potential to address some of the informational needs of snow removal agencies, are not typically placed in the hands of planners and other interested stakeholders. Most tools are not constructed with a nontechnical user in mind and lack an easy-to-use, easily understood interface.

A major goal of the project was to implement a web-based Winter Maintenance Decision Support System (WMDSS) for planning snow removal operations that enhances the capacity of stakeholders (city/county planners, resource managers, transportation personnel, citizens, and policy makers) to evaluate different procedures to manage snow removal assets optimally. This goal was accomplished by integrating geo-spatial analytical techniques (GIS and remote sensing), existing snow removal asset management systems (SRAMS), and web-based spatial decision support systems. In order to extract up-to-date transportation infrastructure features, this study used hyperspectral imagery from the high-resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Classifiers such as the Spectral Angle Mapper (SAM), Mixture-tuned Matched Filtering (MTMF) and Mixture-Tuned Matched Filtering combined with Classification and Regression Tree (MTMF-CART) were used to extract the transportation infrastructures. The study found that the MTMF classification method produced the best overall results compared to both the SAM classifier and MTMF-CART methods, and the overall accuracies for the three classifications were 81.89%, 88.92%, and 84.32%, respectively. The web-based decision support system was implemented using the ESRI ArcIMS ActiveX Connector and related web technologies like ASP, JavaScript, HTML, and XML. The expert knowledge is represented as business rules using Visual Rule Studio, and is integrated with the system. The developed system not only manages and allocates resources, but also provides expert advice to assist complex decision making such as routing, optimal resource allocation, and live weather information monitoring. This system was developed in collaboration with Black Hawk County; the City of Columbia, MO; the Iowa DOT; and the cities of Cedar Falls, IA and Waterloo, IA. Demonstration versions of this product were also given to these agencies in order to improve the usability and applicability of the system.

Funding Sources:
Iowa Department of Transportation
U.S. Department of Transportation
University of Northern Iowa

About the research

Through a cooperative agreement with the Taxi, Limousine, and Paratransit Association and support through the MTC Research & Training Grant DTRS99-6-0007, the Center for Transportation Studies was able to devote considerable time and effort to the research and training of private transportation providers for the efficient and effective provision of public transportation services. This work consisted of the research and development of a series of industry seminars with the purpose of sharing findings and offering recommendations to the large number of private transportation officials engaged in providing public transportation.

The topics for the seminars were selected on the basis of surveys and an understanding of the most important issues and concerns in the industry. Over the course of two years, these seminars were given on the topics of marketing, maintenance, dealing with the media, human resource development, and technology innovations. Seminar attendees were able to learn best practices and share experience on issues involving the human resources management, dispatching technologies, relation with media, sales and marketing, or fleet maintenance.

Funding Sources:
U.S. Department of Transportation

About the research

The purpose of the project was to develop useable techniques to integrate a broader range of potential impacts of transportation investments into transportation planning and decision-making. The research project described in this report developed a multi-attribute framework that can be used to assist in organizing and synthesizing information to measure costs and benefits, both monetary and non-monetary, of highway corridor investments.

A modular approach was taken to developing individual techniques to quantify the potential impacts that could be utilized within the framework. The framework is flexible enough to accommodate the incorporation of additional techniques over time. To determine the range of potential impacts to consider, the values and needs of various stakeholders in highway corridors were taken into account and incorporated into variables, or indicators, to be used in a comprehensive system for evaluating impacts, costs, and benefits.

Example techniques include a consideration and demonstration of the utility of geographic information systems (GIS) to organize data for use with the hedonic land valuation method. A prediction map was generated from this process, indicating the price consumers are willing to pay for a house in relation to its location with respect to highway corridors. This information is useful in analyzing the impact of competing corridor alternatives.

In order to measure other indicators, the project also assessed the utility of highresolution satellite remote sensing (RS) image data to provide highly accurate inputs necessary for economic models and as a means of measuring success after investments have been made. A methodology was developed to identify commercial and industrial origins and destinations from impervious surfaces. This, in turn, was translated into a calculation of average travel distances that could be used to quantify accessibility impacts associated with corridor alternatives.

Remote sensing and GIS were assessed because of the spatial nature of transportation investments and their potential as a measuring tool for the transportation indicators. This multi-attribute framework is consistent with the Missouri Department of Transportation?s (MoDOT?s) overall planning direction of including the perspectives of more individuals/groups and potential impacts in decision making. This overall planning direction is seen in the Planning Framework and the Long-Range Transportation Plan (LRTP).

Funding Sources:
U.S. Department of Transportation
University of Missouri – Columbia

About the research

The objective of this project has been to develop a decision support framework, based on asset management principles, to facilitate effective decision making for selection of appropriate methods to stabilize failed earth slopes. Project activities included development of a simple asset management framework suitable for managing geotechnical assets, development of several analysis models to evaluate alternative slope maintenance and repair strategies, and evaluation of the potential for use of personal digital assistants (PDAs) for implementing geotechnical asset management systems.

A simple framework for managing geotechnical assets was developed based on ?mapping? of a generic asset management framework proposed by the Federal Highway Administration. A number of issues that must be addressed prior to complete implementation of a geotechnical asset management system was also identified. The most significant of these issues are lack of established procedures and techniques for collecting the required data and lack of suitable analysis tools required to evaluate alternative management scenarios. Because ongoing efforts to address the data collection and maintenance are underway, efforts for this project were focused on development of suitable analysis techniques. Two basic forms of analysis models were developed, both of which use decision trees to predict outcomes of alternative stabilization measures. The first form is referred to as the Instant in Time (IIT) form of model to reflect the fact that the model considers only a single application of a repair. In its current form, the IIT model does not model the potential costs of alternative stabilization measures over a consistent ?life-cycle.? The second form of model is referred to as the Specific Time Horizon (STH) form of model because it provides capabilities to model the potential need for repeated application of alternative repair techniques within a specified time period. In doing so, this form of model overcomes the most severe limitations of the IIT form of model while still retaining the significant advantages of the general decision tree approach. Several preliminary tools, referred to as ?break-even? diagrams, were developed using the models to illustrate one potential application of the techniques by field personnel.

Efforts undertaken to implement the developed models using PDAs were unsuccessful due to current lack of portability of PC-based tools to PDAs. However, the ability to port the PC-based models to PDAs is expected to be possible in the near future.

Funding Sources:
U.S. Department of Transportation

About the research

This report presents the results of research on the development of an intelligent system to integrate a generation of snowplowing routes and the optimization of resource/asset allocation for snow removal. The developed system, known as the snow removal asset management system (SRAMS), is an expert system containing the logical rules and expertise of the Iowa Department of Transportation?s snow removal experts in Black Hawk County, Iowa, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a geographic information systems package), Visual Rule Studio 2.2 (an artificial intelligence shell), and Visual Basic 6.0 (a programming tool).

The main goal of the study was to build a knowledge-base that allows the Iowa Department of Transportation and other agencies to optimally manage snow removal assets and resources. The SRAMS was designed to be fully interactive and include provisions for entering meteorological observations and field data to refine the snow removal plan. The system is able to run various scenarios and generate prioritized snowplowing routes in visual format, and to optimize the allocation of assets and resources for snow removal. A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system. Another major benefit of the system is its ability to track inventory of materials such as salt and sand.

This report also documents knowledge acquisition and system design, the algorithms used for optimization, and system validation and field testing. Several appendices with more detailed information are provided at the end of the report.

Funding Sources:
U.S. Department of Transportation

About the research

The objective of the proposed guidelines for a roadway management system (RMS) is to describe a framework for a modular and user-friendly RMS that will assist local government agencies of all sizes in coordinating and planning routine and preventive maintenance, rehabilitation, and reconstruction. These guidelines include a step-by-step procedure to establish a customized RMS for local government agencies. The resulting RMS, based upon the proposed guidelines, will be a systematic methodology that can assist local government agencies to evaluate current pavement conditions, identify problems on pavements, select the best repair and maintenance strategies with the minimum cost, and generate a schedule and priority program for these actions at both project and network levels at both the present time and the future.

As part of these guidelines, we also report the results of a nationwide survey of local government roadway management practices. A questionnaire was developed as part of this survey and sent out to local government agencies throughout the United States. This information was then used to establish the proposed RMS guidelines that are relevant for local government agencies? needs and expectations. In addition, a literature survey was conducted to review current roadway management systems and research, and to reduce the duplication of research, information, or training materials that have been developed by other government agencies or private consultants. Furthermore, the information from both survey methods was evaluated, refined, and customized to the proposed RMS guidelines.

Detailed background information on various aspects of a roadway pavement and an RMS is also given in these guidelines to ensure consistency of usage and understanding since these terms and definitions may vary from one agency to another. The information includes definitions and terms related to pavements, types of pavement, types of pavement distress, etc.

Then, a section on inventory methodology is included. An inventory methodology is established for use in the data collection process. It is imperative that only necessary information be collected to reduce time and cost in the data collection process. This section also provides terms and definitions used in the inventory program, referencing and defining methods for the roadway network, and the understanding between project and network levels. This information is expected to clarify the scope and level of responsibility for local government agencies.

Once the data inventory is established, the data collection process can be initiated to gather information from concerned pavements within the roadway network. The data used to evaluate the current pavement condition can be obtained by a variety of methods such as visual inspection rating, nondestructive testing, destructive testing, and others. Moreover, there are several mathematical indices that indicate the current pavement condition and that are widely used by local government agencies, such as the Present Serviceability Index (PSI), International Roughness Index (IRI), and Pavement Condition Index (PCI). These guidelines also provide the step-by-step procedure to obtain the PCI value for different low-volume flexible and built-up pavement types as well as different maintenance strategies. In the proposed guidelines, the PCI value forms the basis for establishing the other components as well as developing the coordination among the components of an RMS.

The integration of an RMS with a geographical information system (GIS) is another approach to achieve the long-term use of an RMS by updating the data on pavements within the roadway network. This report presents the advantages acquired from the integration of an RMS with GIS as a platform, details of systems displaying RMS information on maps, components of GIS, and the approach to establish a central database.

Furthermore, these guidelines present a method to generate the maintenance, rehabilitation, and reconstruction actions in order to maintain and improve the pavement performance based upon the PCI obtained earlier. This will help local government agencies to decide what repair and maintenance actions would be best suitable for concerned pavements.

Without a pavement performance prediction model, the future tasks and schedules cannot be effectively planned. A pavement performance prediction model is developed based upon the collected data on pavements to forecast the PCI value in the future. Therefore, by using this prediction model local government agencies will be able to predict future facility condition, analyze facility life cycle cost, and estimate the type and timing of maintenance and rehabilitation need regarding only the projected PCI.

There are a number of factors used to consider maintenance alternatives needed for pavements such as cost, duration of action, available resource, etc. Generally, the cost of each alternative is the primary factor that most local government agencies are concerned with due to the limited funding each year. In order to compare the cost of each strategy, life cycle cost analysis can be preformed. Consequently, a methodology for life cycle cost analysis is also provided in these guidelines.

Usually, local government agencies do not have enough funds to improve all segments within a roadway network although they have adequate information to identify problems on these segments. The priority program, therefore, is the solution for local government agencies to generate their budget and to numerically plan which concerned segment should be first taken care of. These guidelines identify the numerous factors affecting the priority index such as PCI, average daily traffic, roadway functional classification, roadway location, maintenance history, and pavement riding quality, and provide a methodology for obtaining the priority indices.

The final component of an RMS is to generate a report such that the elected board or council can approve the funds regarding local government agencies? needs. It is imperative that the data and analysis be clear and easy to understand for those who are not technical experts or engineering professionals. These guidelines briefly demonstrate the tasks that should be considered and included in the proposed report. This will guide local government agencies to establish the proposed report for their own customized RMS.

Funding Sources:
U.S. Department of Transportation

About the research

This study developed a methodology for improving the practice of making transit asset investment decisions at state departments of transportation (DOTs) and local transit agencies. The study made four major contributions to the state of transit asset investment decisions.

First, the report provides a review of the literature on the relationship between maintenance (preventive and corrective) costs and transit vehicle conditions, and it discusses its relevance to the vehicle conditions encountered in US transit agencies. The maintenance costs include both vehicle operating costs (i.e., fuel consumption, oil consumption, repair/maintenance, and depreciation) and non-vehicle operating costs (i.e., vehicle downtime due to maintenance work and road calls due to vehicle breakdowns on the road).

The majority of studies in this area find that there are significant differences in vehicle operating costs between road types (i.e., bituminous versus gravel versus earth), age, mileage, and vehicle type. Vehicle repair/maintenance costs are found to be primarily affected by vehicle condition. In terms of non-vehicle operating costs, vehicle downtime due to maintenance work and road calls due to vehicle breakdowns on the road were extensively studied in relation to vehicle condition.

The second contribution of the study is the development of a new vehicle deterioration model based on the ordered probit method. The major capability of the model is to predict the future conditions of the vehicle based on the historical records of the selected dependent factors, such as the vehicle?s age, mileage, current conditions, and so forth. To best predict the vehicle?s future condition, the most valuable dependent variables were identified.

The contribution of possible variables was analyzed and the factors that affect a vehicle?s future condition were specified. The model can identify the relative importance of the independent variables with the given condition ratings. In addition, predictions can be made for individual vehicles or a group of vehicles at different condition ratings, both of which are important for the management system. Knowing the percentages of vehicles at different condition ratings in the future based on the present and historical conditions, a transit fleet manager can allocate the budget more efficiently and accurately.

The third contribution of this study is the development of relationships between vehicle conditions and the cost of preventive and corrective maintenance and a life cycle cost analysis (LCCA) methodology incorporating these cost relationships into network level and project level decisions. One can use these relationships and LCCA to select the best maintenance strategies for short- and long-term operation.

The fourth contribution of this study is to develop an integrated transit asset management system to incorporate the developed models described above and help managers make decisions about which applicable maintenance to use on the basis of minimizing total cost.

Funding Sources:
U.S. Department of Transportation

About the research

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated.

In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team.

Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.