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Widely used data-collection methods fail to fully capture the lived experiences and un-met travel demands of marginalized populations and those at disproportionate risk of experiencing transportation disadvantage (TD). This study describes an interdisciplinary collaboration between social work, civil -engineering, and computer science on the development of a transportation data collection tool, MyAmble. The theoretical framework of social exclusion was used as part of the study design in order to better understand the process of marginalization as a result of inability to participate in wider society, in part through lack of transportation. Thus, MyAmble augments the best practices in transportation daily diary research using features designed to characterize and quantify latent travel demand among individuals experiencing TD, as well as the subjective impact of lack of transportation on quality of life and well-being. MyAmble includes several innovations – a daily digital trip planning that captures latent demand, a text-messaging based qualitative interview tool, a self-guided travel history survey, and a challenge logger. We describe the design process and implementation that occurred during a five-day pilot test and present a case study. Finally, findings from the case study suggest that MyAmble was able to successfully capture planned, unplanned, and unserved trips as well as the lived experiences of TD. [ABSTRACT FROM AUTHOR]

No previous research provided a comprehensive review of the bicycle volume estimation techniques assessing the current research gaps in data and modeling makes it challenging to understand the most effective and accurate strategies to estimate bicycle volumes. This article provides a detailed review of 58 studies published from 1996 to 2021. The review results indicate that conventional modeling approaches such as Linear regression, Negative Binomial, Poisson regressions, and a factor-up method represent the most popular econometric statistical models for bicycle volume estimation, while a decision tree is popular among machine-learning-based techniques due to its simplicity and ease of application, interpretation, and estimation with small data sets. In addition, Strava data, Socio-demographic variables, and bicycle facilities significantly contribute to the predictions. The study documents the current research gaps and recommends future research directions to improve data source evaluations, variable creations, modeling, and scalability/transferability advancements. [ABSTRACT FROM AUTHOR]

As agencies consider strategies for meeting the livability goals (e.g., public health, mobility, and access) of communities, they often repurpose the existing right-of-way of arterials to meet traffic operation or safety goals. Agencies need more definitive guidance on when this repurposing of existing right-of-way can be done without negatively affecting safety. Researchers around the world have considered the safety efficacy of lane width, but none defines lane width design recommendations of urban arterials. This study uses treed regression analysis on crash data collected from four cities of Nebraska to develop predictive models for identifying the crash modification factors of different lane widths. The analysis from five treed regression models indicates that narrower lanes increase the likelihood and the frequency of injury and noninjury crashes on high-volume segments; however more specifically, the results also show that narrower lane widths can be adopted for segments with lower volumes, a sufficient number of through lanes, and lower speed limits without degrading safety. Based on these crash modification factors, the research team creates design recommendations for arterial lane widths using combinations of speed limit, average annual daily traffic per lane, and number of through lanes. [ABSTRACT FROM AUTHOR]

Nearly 1 in 5 Americans will struggle with major depression in their lives; some will have recurring bouts. Recent psychiatric research has given new attention to the prevalence of cognitive deficits in major depression and the impact such deficits have on remission and overall life functioning. When depression is partially treated i.e., leaving residual symptoms, patients have higher rates of relapse and lower functional outcomes. Impaired cognitive functioning is a frequent residual symptom, persisting in about 45% of patients even when emotional symptoms have improved, and results in a disproportionate share of the functional impairment, particularly in the workplace. Patients with depression have disrupted circuitry in brain regions responsible for cognition and it is therefore important to screen depressed patients for cognitive as well as emotional symptoms. Cognitive dysfunction should be evaluated in every mood disordered patient with validated self-report scales such as the Patient Health Questionnaire-9 or the Beck Depression Inventory and objective measures of cognitive function are also very very useful. Two easily administered tests are the Trails B Test and the Digit Symbol Substitution Test. Each take less than two minutes and measure working memory, executive function, and processing speed and can track cognitive improvement in depressed patients. Treatment of cognitive dysfunction in major depression is complicated by the ‘serotonin conundrum’: SSRI’s frequently do not treat to full remission, and can cause cognitive blunting—actually adding to cognitive problems. Based on recent data including results from a recently completed meta-analysis by McIntyre and colleagues, an evidence-based algorithm for treating cognitive symptoms in depression is presented. A hierarchy of antidepressants and augmentation strategies based on the best available evidence is discussed. In conclusion, cognitive symptoms in major depressive disorder have been recognized as a target of therapeutic improvement by the FDA and have become a focus of clinical importance. [ABSTRACT FROM PUBLISHER]

This article provides a technical evaluation of the traffic control element of the Anaheim Advanced Traffic Control System Field Operations Test (FOT), sponsored by the US Department of Transportation. The primary objective for this test was the evaluation of adaptive traffic signal control technologies, including the Split Cycle and Offset Optimization Technique (SCOOT) for intersection signal control. The SCOOT evaluation was defined relative to existing, first generation Urban Traffic Control System (UTCS)-based control using standard US field detectorization. This US geometry is not the detector configuration normally used with SCOOT. SCOOT was implemented with some degree of success, though technical problems limited its performance. Anaheim's existing communication and controller systems contributed major deployment limitations since they were less adequate than anticipated. SCOOT remains in use in selected areas, with plans for system expansion. [ABSTRACT FROM AUTHOR]

Cell phone usage may impair a driver's decision-making at a dilemma zone. This research seeks to identify the impact of cell phone usage on different dilemma zone driver behaviors. Participants were exposed to different driving situations in a simulator where they had a phone call while driving through signalized intersections. A combination of variables was collected; therefore, this research estimates Classification and Regression Tree (CART) and stepwise logistic regression models to describe the factors influencing dilemma zone driver behavior. While the logistic regression models focus on the overall impact of the variables, the CART model develops subpopulations based on the variables' impact. Cell phone usage, especially incoming calls on a handheld device, and the overall experiment appear to encourage conservative behavior where the drivers opt to stop even when they are "expected" to go. Unfortunately, when the drivers decide to go, they tend to make the wrong choice and run the red light. Using hands-free devices on outgoing calls appears to reduce the likelihood of performing an illegal maneuver. This represents a potential opportunity for future policy and technological advancements to improve intersection safety by only permitting outgoing hands-free calls on arterials. [ABSTRACT FROM AUTHOR]