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This chapter traces the history of the derived-demand concept, its application to the transportation context, and an important challenge to the derived view of transportation demand. The derived-demand concept, which underpins the logic of accessibility in transportation and land-use planning, originated in realms entirely removed from transportation. The derived-demand term was coined in 1895 by the economist Alfred Marshall, who used it to describe the demand curves for goods that were intermediate to the consumption or production of other goods. However, the first application of Marshall's derived-demand concept to transportation may have come four decades later in Michael Bonavia's 1936 book The Economics of Transport. The derived-demand concept in transportation was developed further by Robert Mitchell and Chester Rapkin, who were interested in forecasting demand for transportation on the basis of land-use patterns across a metropolitan area. Ultimately, the consensus view that transportation demand is mostly derived is not an absolute truth but, rather, is based on the view that transportation is most usefully viewed—in most circumstances and for most trips—as one means to an end, rather than an end in itself.

This chapter addresses how public transport plays a special role in accessibility. Like driving, biking, or walking, its first job is to provide the mobility that allows travelers to reach their destinations. However, public transport differs from other modes in its capacity to boost proximity indirectly; it can bring origins and destinations closer together to shape land-use development toward higher proximity. These proximity impacts operate at both local and regional scales. When public transport enables large and concentrated downtowns to thrive, or when it facilitates metropolitan compactness overall, it is supporting a regional accessibility benefit that accrues to transit users and nonusers alike. Public transport also differs from other modes in that measuring its accessibility involves a series of technical challenges that planners and public officials must confront when they seek to extend the accessibility shift to the transit context. The chapter then considers the special challenges of public-transport accessibility measurement and then demonstrates one application of such measurement: the assessment of bus versus rail transportation deployments for their respective contributions to metropolitan accessibility.

Introduction Many U.S. cities have adopted the Vision Zero strategy with the specific goal of eliminating traffic-related deaths and injuries. To achieve this ambitious goal, safety professionals have increasingly called for the development of a safe systems approach to traffic safety. This approach calls for examining the macrolevel risk factors that may lead road users to engage in errors that result in crashes. This study explores the relationship between built environment variables and crash frequency, paying specific attention to the environmental mediating factors, such as traffic exposure, traffic conflicts, and network-level speed characteristics. Methods: Three years (2011–2013) of crash data from Mecklenburg County, North Carolina, were used to model crash frequency on surface streets as a function of built environment variables at the census block group level. Separate models were developed for total and KAB crashes (i.e., crashes resulting in fatalities (K), incapacitating injuries (A), or non-incapacitating injuries (B)) using the conditional autoregressive modeling approach to account for unobserved heterogeneity and spatial autocorrelation present in data. Results: Built environment variables that are found to have positive associations with both total and KAB crash frequencies include population, vehicle miles traveled, big box stores, intersections, and bus stops. On the other hand, the number of total and KAB crashes tend to be lower in census block groups with a higher proportion of two-lane roads and a higher proportion of roads with posted speed limits of 35 mph or less. Conclusions: This study demonstrates the plausible mechanism of how the built environment influences traffic safety. The variables found to be significant are all policy-relevant variables that can be manipulated to improve traffic safety. Practical Applications: The study findings will shape transportation planning and policy level decisions in designing the built environment for safer travels.

This paper reviews the literature on the relationship between the built environment and roadway safety, with a focus on studies that analyse small geographical units, such as census tracts or travel analysis zones. We review different types of built environment measures to analyse if there are consistent relationships between such measures and crash frequency, finding that for many built environment variables there are mixed or contradictory correlations. We turn to the treatment of exposure, because built environment measures are often used, either explicitly or implicitly, as measures of exposure. We find that because exposure is often not adequately controlled for, correlations between built environment features and crash rates could be due to either higher levels of exposure or higher rates of crash risk per unit of exposure. Then, we identify various built environment variables as either more related to exposure, more related to risk, or ambiguous, and recommend further targeted research on those variables whose relationship is currently ambiguous.

Electric scooters (or e-scooters) have quickly proliferated in cities worldwide, presenting a host of regulatory challenges. We analyze trip origins and destinations for shared e-scooter use at the street-segment level. Street segments are a relevant unit for policy analysis because users park scooters along the streets' curbside, and parking policies target specific street segments. We build Hurdle models for trip origins and destinations using data from Washington DC in 2019. Results show that street segments near tourist sites, hotels, and transit stops attract the most scooter-trip destinations. In contrast, the supply of available e-scooters is the dominant force shaping scooter-trip origins. We find preliminary evidence to suggest that scooters are complementing public transit. Like other studies, we find that areas with younger and more educated demographics correlate with higher e-scooter use. Finally, we demonstrate that the model can identify segments with a high demand for scooter parking.

Conventional transportation practice attributes traffic crashes to human error, leading to the prevailing assumption that crash prevention is principally an outcome of driver education and law enforcement programs. But what if planning and urban design decisions induce human errors? In this study, we examine the literature in organizational systems safety, cognitive psychology, and behavioral economics to detail how cognitive interpretations of the built environment may produce the errors that result in traffic crashes. We proceed to examine crash incidence in Charlotte-Mecklenberg County in light of this cognitive framework and discuss its implications for research and practice.

Most of the research on the influence of the built environment on travel has focused on reducing the impacts of travel, but one of the primary benefits of travel is the opportunity to engage in activities. This study examines a national travel data set to see if variation in the built environment can facilitate participation in out-of-the-home, nonwork activities for households. Although several studies have examined the relationship between the built environment and nonwork trip generation in the past, none have looked at such a wide range of built environments as a national data set can provide. Built environment variables are associated with higher than expected impacts on household participation in nonwork activities, increasing or decreasing activity levels in the range of 8–47 %, depending largely upon the level of household vehicle ownership. For households without vehicles, high residential and employment densities appear to support greater nonwork activity. Households with full access to vehicles appear to be supported by higher than average residential and employment densities and mid-range urban and metropolitan area sizes. Interestingly, activity participation in households with limited vehicle access is for the most part not affected by the built environment in a statistically significant way. In sum, these results suggest that the built environment may play a larger role in facilitating activity participation than previously presumed.

Using 2007 travel-diary data from metropolitan Chicago, I investigate what aspects of urban form contribute most to community completeness, as defined by internal tour capture for nonwork tours. I examine two distinct geographic scales: census-defined ‘places’, and synthetically constructed ‘centered communities’. Centered communities are defined as nonwork travel sheds centered upon well-defined concentrations of activity. Higher accessibility share (a new urban form measure defined in the paper) and higher mixed use both significantly predict greater community completeness, as do higher levels of residential or employment density. Furthermore, I find that mixed-use measures describe something other than simple proximity to job-based attractions; these measures also address the appropriate balance of activities necessary for a complete community. To build more-complete communities, planners need to ensure that local accessibility to a variety of destinations of interest is high relative to the regional accessibility to these same types of destinations outside the community. Keywords: complete communities, jobs–housing balance, internal trip capture, mixed use, accessibility, nonwork travel

We review a variety of common measures of urban land use mix in order to understand their differences and to identify their strengths and limitations. We then apply these measures to data from a Monte Carlo simulation to ascertain statistical relationships among them, finding that they can be placed into four groups where measures within each group produce highly consistent results: Percentage and Exposure Index; all varieties of the Atkinson Index; Balance, Entropy, and Herfindahl–Hirschman indices; and the Dissimilarity and Gini indices. We find that when analyzing two dimensions of land use, generally both the Balance Index and the Dissimilarity Index should be used, and that the Dissimilarity Index should be tested at multiple scales. We provide a number of other practical recommendations about which mixed use measure to apply given the contextual information available to a researcher or analyst.

© 2014 SAGE Publications We examined the influence of the built environment on pedestrian route selection among adolescent girls. Portable global positioning system units, accelerometers, and travel diaries were used to identify the origin, destination, and walking routes of girls in San Diego, California, and Minneapolis, Minnesota. We completed an inventory of the built environment on every street segment to measure the characteristics of routes taken and not taken. Route-level variables covering four key conceptual built environment domains (Aesthetics, Destinations, Functionality, and Safety) were used in the analysis of route choice. Shorter distance had the strongest positive association with route choice, whereas the presence of a greenway or trail, higher safety, presence of sidewalks, and availability of destinations along a route were also consistently positively associated with route choice at both sites. The results suggest that it may be possible to encourage pedestrians to walk farther by providing high-quality and stimulating routes.

This report and the conference it summarizes are an examination of how we, as academics, practice our craft; how we work to make it more relevant to broader publics and responsive to pressing societal problems. In May 2015, more than 40 speakers (including 4 University Presidents) and 225 registrants attended a three day conference at the University of Michigan to focus on four key themes: (1) What is engagement and should we do it? (2) What are the ground rules for public and political engagement? (3) What models have worked, and what can we learn from them? (4) What are the obstacles to engagement, and how can they be overcome? The contents of this report are about the kinds of research we conduct, but even more, it is about the public meaning and goals of that work. Ultimately, it is about who we are as a university and what it means to be an academic in a society facing complex scientific, technological, and social challenges. We come to this discussion driven by a deep concern that the academy is facing a crisis of relevance.