Sue McNeil

A Regression Formulation of the Matrix Estimation Problem

Matrices are widely used in transportation planning to represent the distribution of characteristics or as origin-destination matrices. Developing such matrices by means of surveys is expensive and time consuming, and once the survey data are collected and compiled the matrices are rapidly outdated. Other methods which are commonly used are unable to include all available data or to provide a measure of the uncertainty of the estimates. This paper formulates a quadratic programming method to estimate matrix entry estimates as an equivalent constrained generalized least squares estimation problem. As well as being able to include any available information in the form of constraints, the variance-covariance matrix of the entry estimates may be found and confidence intervals calculated for matrix entry estimates with some added distributional assumptions. The problem of updating the proportions of nationwide automobile trips by purpose and trip length from 1970 to 1977 is included as a simple example to illustrate the method.

Neighborhood Environment and Adherence to a Walking Intervention in African American Women

This secondary analysis examined relationships between the environment and adherence to a walking intervention among 252 urban and suburban, midlife African American women. Participants received an enhanced or minimal behavioral intervention. Walking adherence was measured as the percentage of prescribed walks completed. Objective measures of the womens neighborhoods included walkability (land use mix, street intersection density, housing unit density, public transit stop density), aesthetics (physical deterioration, industrial land use), availability of outdoor (recreational open space) and indoor (recreation centers, shopping malls) walking facilities/spaces, and safety (violent crime incidents). Ordinary least squares regression estimated relationships. The presence of one and especially both types of indoor walking facilities were associated with greater adherence. No associations were found between adherence and other environmental variables. The effect of the enhanced intervention on adherence did not differ by environmental characteristics. Aspects of the environment may influence African American women who want to be more active.

Comparing the Efficiency of Public Transportation Subunits Using Data Envelopment Analysis

This paper discusses the need for a performance measure that compares the efficiencies of subunits within a transportation organization, reflects the diversity of inputs and outputs, and is objective and consistent. The study presents a method for developing such a performance indicator, and illustrates its use with an application to the park-and-ride lots of the Chicago Transit Authority. The proposed method applies Data Envelopment Analysis supplemented by Stochastic Frontier Analysis to estimate efficiency scores for each subunit. The research shows how the scores can provide objective and valid indicators of each subunit’s efficiency, while accounting for key goals and values of internal and external stakeholders. The scores can be practically applied by a transit agency to identify subunit inefficiencies, and, as demonstrated by several brief case studies, this information can be used as the basis for changes that will improve both subunit and system performance.

Use of Automatic Vehicle Location and Passenger Count Data to Evaluate Bus Operations

New technologies such as automatic vehicle location (AVL) and automatic passenger counters (APC) make tremendous amounts of data available to transit planners and operators. Transit agencies would like to use these data to inform service planning and management and ultimately to provide more reliable service. This requires data processing in such a way as to provide pertinent information to transit planners. The research presented considers a sample of data collected from Chicago Transit Authority buses during the initial stage of AVL and APC implementation in Chicago, Illinois. Methods were developed for extracting information from these data that could be used to compute service reliability indicators. This research also discusses some of the challenges encountered in the data collection process. At the time of the data collection, the home garage for the bus route under consideration was not fully stocked with AVL-equipped buses. Other challenges included the misplacement of some time points and underc...

Side collision warning systems for transit buses

Transit buses are involved in many more accidents than other vehicles. Collision warning systems (CWS) are therefore placed most efficiently on these buses. In our project, we investigate their operating environment and available technologies to develop performance specifications for such CWS. The paper discusses our findings of transit buses driving through very cluttered surroundings and being involved in many different types of accidents where currently available CWS no not work effectively. One of the focuses of our work is pedestrians around the bus and their detection.

Neighborhood Characteristics, Adherence to Walking, and Depressive Symptoms in Midlife African American Women

BACKGROUND African American women have more symptoms of depressed mood than white women. Adverse neighborhood conditions may contribute to these symptoms. Although reductions in depressive symptoms with physical activity have been demonstrated in white adults, little research has examined the mental health benefits of physical activity in African American women. Further, it is unknown whether physical activity can offset the effects of living in disadvantaged neighborhoods on depressive symptoms. The purpose of this study was to examine the relationships among neighborhood characteristics, adherence to a physical activity intervention, and change over time in depressive symptoms in midlife African American women. METHODS Two hundred seventy-eight women participated in a home-based, 24-week moderate-intensity walking intervention. Either a minimal treatment (MT) or enhanced treatment (ET) version of the intervention was randomly assigned to one of the two community health centers. Walking adherence was measured as the percentage of prescribed walks completed. Objective and perceived measures of neighborhood deterioration and crime were included. RESULTS Adjusting for demographics, body mass index (BMI), and depressive symptoms at baseline, walking adherence and objective neighborhood deterioration were associated with significantly lower depressive symptoms, whereas perceived neighborhood deterioration was associated with significantly higher depressive symptoms at 24 weeks. CONCLUSIONS Adherence to walking as well as aspects of the environment may influence depressive symptoms in African American women. In addition to supporting active lifestyles, improving neighborhood conditions may also promote mental health among African American women.

Application of Nondestructive Evaluation to Subway Tunnel Systems

Subway tunnel condition assessment presents significant challenges for engineers and managers and is becoming increasingly important as the systems continue to age. Tunnels are in constant heavy use in an aggressive environment. Tunnel systems are vast, dark, and noisy. The national investment in subway tunnels is enormous, and careful maintenance and management are necessary to protect this investment. Technologies that can rapidly and accurately access the condition of subway tunnels without interfering with the normal operation of the system were studied. First, issues and problems in subway tunnel maintenance were reviewed through the literature and by interviewing transit agency managers and engineers. Next, different nondestructive evaluation (NDE) methods including spectral analysis of surface waves, impact echo, ground-penetrating radar, and impulse response were evaluated to determine the advantages and limitations of these methods on different problems like water leakage, corrosion, and cracks in subway tunnel systems. Issues of data and infrastructure management were also considered. NDE technologies have considerable potential for improving the maintenance and management of transit infrastructure. However, to fully realize that potential, further development is needed. It is necessary to distinguish between methods that require interruption of subway traffic from those that do not. Rapid screening NDE methods must be researched to develop clear signals of delamination, moisture-related damage, and other issues of concern. It is also necessary to develop automated procedures to process the vast amounts of data generated during extensive NDE testing. Case studies and demonstration projects must be developed and documented to convince managers of the utility of this approach.

Applications of expert systems in railroad maintenance: Scheduling rail relays

Abstract Railroads replace rail when it exhibits too many defects, wears beyond safe limits, or develops extensive plastic deformation. The complex process of developing a plan for rail relay or replacement is known as rail scheduling. A knowledge based expert system has been developed to guide the rail scheduling process. A prototype was developed in conjunction with Burlington Northern Railroad (BN) in order to provide more formal, more consistent, and more rational criteria for rail replacement. A productive system was then developed for use in preparing BNs 1990 rail relay program. The system demonstrates the role of expert systems in supporting decision making in railroad maintenance and identified several areas for other applications of expert systems.

Improving Resilience of Critical Infrastructure Systems Postdisaster

The nations capacity for maintenance and improvement of infrastructure systems and its ability to maintain and improve infrastructure systems and ensure the continued service of critical infrastructure systems are receiving special attention because recent disasters have had a significant impact on critical infrastructure. These critical infrastructure systems are the foundation of the nations economic and social systems. Much research and many policy studies have been conducted to develop methods to improve protection of critical infrastructure with a focus on decreased vulnerability. This paper describes the development of a framework for a decision support system. The objective of the decision support system is to reduce the vulnerability of places and infrastructure systems through the use of mitigation strategies that increase system resilience and resistance to the stresses imposed by disasters. The decision support system will also provide an understanding of the many variables involved in developing strategies to improve the resilience of critical infrastructure systems. This decision support system, referred to as the Critical Infrastructure Resilience Decision Support System (CIR-DSS), uses systems dynamics and recognizes the impacts of disasters, including damage and disruption to critical infrastructure. Results include those of risk and cost–benefit analyses of alternative strategies that also recognize U.S. government policies for recovery and mitigation. A case study focused on transportation infrastructure was used to test and validate the CIR-DSS framework.

Impact of Road Conditions and Disruption Uncertainties on Network Vulnerability

Researchers have studied the vulnerability of roadway systems to disasters, such as terrorist attacks or natural disasters. However, the literature has not explicitly addressed other factors, such as infrastructure condition, that can significantly affect the vulnerability of roadway systems. In this study, the authors developed an algorithmic framework to address how the condition of a roadway network affects its vulnerability to disruptions. The vulnerability of the network was computed with respect to two measures: network efficiency and vehicle miles of travel. The results show that the average condition of the roadways in the network, the difference between the conditions of the roads, the uncertainties associated with road disruption probabilities, and link topological positions affect the roadway vulnerability.