Transportation Research Record: Journal of the Transportation Research Board

Streetscape design is increasingly acknowledged as a tool for improving traffic safety and livability in urban settings. While traditional highway safety engineering promotes removing obstacles from and widening roadside clear zones to reduce collision potential, a contrasting framework proposes that smaller, more enclosed streetscapes may encourage slower, less risky driving and therefore improve both livability and safety. Such a strategy may have particular relevance along urban arterials, where large clear zones may be impractical because of complex adjacent land uses and where the promotion of livable spaces is an increasing focus. This study examined streetscape design and traffic safety in urban settings by assessing relationships between crash severity and streetscape design variables in New York City. A method based on a geographic information system was used for the precise capture of streetscape design measurements at the locations of more than 240,000 crashes. Logistic regression models indicated that crashes on smaller, more enclosed streetscapes were less likely to result in injury or death compared with those on larger, more open streetscapes. These results point to in-fill development and street tree planting as safety countermeasures that are consistent with additional livability goals such as walkability, high-quality design of the public realm, and provision of natural amenities.

This study surveyed attitudes, behaviors, social norms, and perceived control among the populations of students at three high schools in downtown Toronto, Ontario, Canada. The results showed a pattern of hesitancy to cycle on the part of female high school students compared with their male counterparts. Young women reported less access to a bicycle, less comfort or confidence in riding, more fear associated with cycling, and less ability to decide independently how to travel to school. The study identified two important variables that were likely associated with young women's smaller participation in cycling to school: overall cycling mode share and ability to decide their travel mode independently. The former variable tracked findings for the general population, and the latter appeared to have been associated with the proximity of immigration, as families might have brought associations of danger to independent female travelers from their countries of origin or perceived new dangers in Canada. While the former association is well established, the latter hypothesis warrants further research.

The parking industry has seen significant changes over the past decade with the infusion of new technology and smart assets. The introduction of networked meters, virtual payment methods (such as pay-by-cell and credit–debit cards at meters), and technology for real-time detection of space occupancy has resulted in better system uptime, proactive maintenance strategies, multiple payment options, real-time information on parking availability, and better use of spaces through dynamic congestion pricing. The new parking assets and payment options have implications for municipalities and vendors supporting their parking programs. Instead of a significant portion of revenue from coins, virtual transactions account for a predominant share of the parking revenue stream. Focusing on Washington, D.C., as a case study, this paper discusses the economic implications of the changes in the context of overall parking revenue and the cost of different revenue streams for parking. The paper also discusses the impact of these changes on program management (such as maintenance, personnel, and contracting models) and program outcomes (such as customer satisfaction and continued innovation). The paper provides agencies with a framework for taking a holistic look at their parking programs and assessing the impacts of various alternative, cost-effective approaches.

AASHTO's functional classification system specifies that arterials should be designed to provide high mobility and low access; however, this narrow view does not fully represent the vitality of many urban streets, which need to maintain high access and high mobility across a variety of modes. Webster Avenue (US-1) in the Bronx, New York City, was an arterial that was focused on providing vehicular mobility but did not support the mobility and accessibility goals of public transit users and pedestrians. This paper describes results of the multimodal redesign of Webster Avenue by the New York City Department of Transportation (DOT) and the Metropolitan Transit Authority's New York City Transit (NYCT) as part of implementing bus rapid transit (BRT) in the corridor. The new arterial street design improves the organization of traffic: buses, which make frequent stops, now travel exclusively in the right travel lane, while general traffic is able to use the left travel lane. Key project results include a 19% to 23% improvement in bus speeds for the new BRT–select bus service route (compared with the former limited-stop route), 11% to 16% improvement in local bus speeds, maintenance of traffic speeds and volumes, and significant pedestrian safety improvements along the corridor. These results were achieved through extensive outreach and coordination with community stakeholders, careful use of different priority treatments on different parts of the corridor, and the strong working partnership between the New York City DOT and NYCT.

There is a widespread belief that the available tools for predicting travel impacts of urban development are not as strong as they could be. The implications are that cities (a) may be hindered in developing appropriate travel impact mitigations, (b) lack good information to communicate to existing residents about potential travel impacts of proposed development, and (c) with better tools would be able to make stronger policy on the basis of more reliable understanding of development impacts. The most frequently used tool for estimating travel impacts is the ITE informational report on vehicle trip generation. The ITE report contains information primarily on single-use suburban automobile-oriented environments. As travel characteristics are inherently different in urban areas, a wide body of research has sought to create additional data-driven tools to estimate multimodal trip impacts of developments on the basis of urban-context characteristics. This paper compares the estimated trip generation outputs of the ITE and other models to field counts and surveys conducted for the District Department of Transportation at 16 locations in Washington, D.C. The findings here support the widely held belief that existing tools are not well suited to trip generation estimation in urban contexts. The paper is part of a larger study effort that seeks to develop a robust data set of urban trip generation that will be a foundation in the creation of better models.

Assessments of the impact of new land use development on the transportation network often rely on the ITE Trip Generation Manual informational report. Current ITE rates generally represent travel behavior for separated, single-use developments in low-density suburban areas. However, a more compact urban form, access to transit, and a greater mix of uses are known to generate fewer and shorter vehicle trips—and quite possibly more trips overall, especially in heavily urbanized areas like Washington, D.C. Local and national interest exists for generating data that expand upon existing trip rates (and similar parking generation rates) to include sites in diverse, dense contexts. The lack of adequate data on multimodal urban trip generation led the District Department of Transportation in Washington, D.C., to develop and test a streamlined methodology that meets the needs of practitioners who are evaluating the transportation impacts of new developments in dense, multimodal environments. This methodology focuses on capturing all trips to and from a site and the mode of all travelers, not just personal vehicle trips. The methodology was tested at mixed-use multifamily residential buildings but is intended for future use at a wide range of sites. This paper presents the methodology and rationale for a robust national data collection effort.

In a connected-vehicle environment, wireless subsecond data exchange connects vehicles, the infrastructure, and travelers’ mobile devices. These data have the promise to transform the geographic scope, precision, and latency of transportation system control; fulfillment of that promise could result in significant safety, mobility, and environmental benefits. However, the new data influx also has the potential to overburden legacy computational and communication systems. Although connected-vehicle technology can facilitate ubiquitous system coverage, the existing prediction methods, computational platforms, and data management methods are insufficient to process the data within a reasonable time frame for real-time predictions. An investigation of the ways in which advanced (big-data) analytics might be applied to realize the full potential of connected-vehicle technology is particularly relevant now as this technology evolves from research to deployment. This paper presents an approach combining big-data graph analytics with high-performance computing to predict traffic congestion by analyzing nearly 4 billion basic safety messages generated by the safety pilot model deployment conducted in 2012–2013. This paper provides an alternative approach for predicting congestion in 30.5-m segments anywhere on the network at 1-min intervals 30 to 60 min before actual congestion over a time window of 1 h. Despite sparseness of data, the proposed framework predicted highly congested locations 40% of the time. Severity of congestion was predicted with an accuracy of 77%. This combination of rapid computation and predictive accuracy may provide significant value in future real-time decision support systems that leverage connected-vehicle data.

The built environment, accounting for the building and transportation sectors, is the dominant source of environmental impacts. While significant research has assessed environmental impacts in the built environment, existing research is strongly separated by the scale of analysis: individual buildings or the urban scale. However, assessing buildings as isolated objects ignores their urban context, while concentrating on urban-scale projects does not represent the actual scale of construction: growth within existing cities. As such, environmental impacts resulting from the interplay of individual buildings and their urban context, induced impacts, have yet to be determined. This paper presents a new methodology for capturing induced impacts in the built environment. The new methodology was applied to the urban region of Munich, Germany, at three geographical resolutions (traffic cell, city neighborhood, and district) to illustrate the significance of induced impacts. The research contributes to the literature through the integration of the assessment of the transportation infrastructure in addition to the traditional focus on operational impacts. Transportation embodied impacts were found to account for approximately 25% of greenhouse gas emissions. Furthermore, transportation impacts (embodied and operational) were summarized at three locations: city center, city periphery, and rural. Consequently, the work has identified a missing impact category, expanded the assessment methodology, and provided quantitative analysis for holistic evaluation of the built environment. The inclusion of induced impacts allows for innovative policies to achieve environmental goals within the built environment.

Housing affordability has been one of the most persistent national concerns in the United States, mainly because housing costs are the biggest item in most household budgets. Urban sprawl has been proved by previous studies to be a driver of housing affordability. Previous studies, however, were structurally flawed because they considered only costs directly related to housing and ignored the transportation costs associated with a remote location. This study sought to determine whether, after transportation costs were taken into account, urban sprawl was still affordable for Americans. Multilevel modeling and the recently released location affordability indexes (LAIs) and metropolitan compactness indexes tested the relationship between sprawl and housing affordability. By controlling for covariates, this study found that in compact areas, the portion of household income spent on housing was greater but the portion of income spent on transportation was lower. Each 10% increase in a compactness score was associated with a 1.1% increase in housing costs and a 3.5% decrease in transportation costs relative to income. The combined cost of housing and transportation declined as the compactness score rose. As metropolitan compactness increased, transportation costs decreased faster than housing costs increased, creating a net decline in household costs. This is a novel finding, conditioned only on the quality of the data on which the LAI is based.

Jobs–residence balance is believed to be an important way to reduce commuting distance and related externalities. Although literature on jobs–residence balance is rich, relatively few studies investigate it in relation to employment industry sectors. However, consideration of the unique features of different industry sectors, such as workers’ ability and working hours, is necessary to gain useful knowledge. In addition, variability in commuting distance is an important factor often neglected in previous studies. Low variability implies a high potential for car sharing and for use of transportation services. This paper fills the voids of existing literature by investigating three employment industry sectors in relation to both averages and standard deviations of commuting distances. A seemingly unrelated regression model with spatial error was applied to examine the relationship between jobs–residence balance and commuting patterns. The investigation also considered the effects of urban forms, which had been found to be influential in commuting patterns. Two groups of cities, compact and sprawled, were used as the cases of different urban forms. Results showed that jobs–residence balance was more sensitive to the goods-producing sector and to compact regions. Meanwhile, an efficient commuting pattern was associated with a high jobs–residence ratio, clustered industry distribution, and dense road networks with few intersections.

This study examined the links between attitudes, the built environment, and travel behavior on the basis of data from the Ohio State University's 2012 Campus Transportation Survey. The analysis results indicated that attitudes might have explained travel behavior better than the built environment. Survey respondents were asked questions about their attitudes on public transit use, and their answers were grouped into new attitudinal factors by using principal component analysis. Then, new neighborhood categories were created by K-means cluster analysis by means of built-environment and land use variables (population density, employment density, housing density, median age of structures, percentage of single-family housing, and intersection density). As a result of this analysis, discrete neighborhood categories, such as urban high-density and residential neighborhoods, and urban low-density and mixed-use neighborhoods, were created. Then, differences in attitudes toward public transit were analyzed across these new neighborhood categories. Binary logit models were estimated to determine the influence of these neighborhood categories as well as personal attitudes on public transit use after sociodemographic characteristics were controlled for. The results indicated that attitudes were more strongly associated with travel behavior than with neighborhood characteristics. The findings of this study will aid in the formation of a better understanding of public transit use by highlighting the effects of attitudes and neighborhood characteristics in transit use as well as differences in attitudes between neighborhood types.

While voluminous empirical studies have examined the impact of land use on travel behavior, few have relied on longitudinal data and an analytical approach. With data from two activity travel surveys (1997 and 2006) conducted in Austin, Texas, this paper develops a longitudinal multilevel model for estimating the change in the effect of land use on vehicle miles of travel (VMT) over time and the long-range land use effect on VMT reduction. Results suggest that the influences of land use mixture and street density on VMT would vary between 2 years. The effects of VMT reduction on land use policies by raising population and street densities are salient in the short run but insignificant in the long run, whereas those of mixed-use policies are even larger in the long run. These findings validate the importance of longitudinal data and analysis in land use–travel studies and suggest that the short-run elasticity of land use derived from cross-sectional analyses may be inappropriate for assessing the long-run effect of land use–based mobility strategies for reducing VMT.

It seems an article of faith that because ridership catchment receives the largest share of riders within the first 0.5 mi (0.80 km), the design of transit-oriented development should be limited to 0.5 mi (0.80 km). But design of transit-oriented development requires another consideration: how the commercial real estate market responds. Unfortunately, much of the research into the commercial real estate value or rent premiums associated with transit station proximity is designed to reinforce the 0.5-mi (0.80 km) presumption. This paper reviews the literature and implications of ridership studies and research into commercial value and rent premiums with respect to distance from a transit station. The paper then reports research into transit station–related office rent premiums in the Dallas, Texas, metropolitan area. To the authors' knowledge, this study is the largest of its type undertaken on this question. Among the findings are that the premium extends 1.85 mi (2.98 km) from transit stations, with 25% of the premium—not a trivial amount— existing to 0.93 mi (1.50 km), with higher shares closer to the stations. The paper offers a reconsideration of both worker-based ridership and research on commercial real estate premiums to suggest that planning areas for transit-oriented development may extend beyond 0.5 mi (0.80 km), perhaps to 1 mi (1.61 km).

Current methods of traffic impact analysis, which rely on rates and adjustments from ITE, are believed to understate the traffic benefits of mixed-use developments (MXDs) and therefore to lead to higher exactions and development fees than necessary and to discourage otherwise desirable developments. The purpose of this study was to improve methodology for predicting the traffic impacts of MXDs. Standard protocols were used to identify and generate data sets for MXDs in 13 large and diverse metropolitan regions. Data from household travel surveys and geographic information system databases were pooled for these MXDs, and travel and built-environment variables were consistently defined across regions. Hierarchical modeling was used to estimate models for internal capture of trips within MXDs and for walking, biking, and transit use on external trips. MXDs with diverse activities on site were shown to capture a large share of trips internally, so that the traffic impacts of the MXDs were reduced relative to conventional suburban developments. Smaller MXDs in walkable areas with good transit access generated significant shares of walk, bike, and transit trips and thus also mitigated traffic impacts.

This paper examines the influence of the built environment and individual lifestyle choices on weekly frequency of active transportation (AT) for home-based nonwork trips in the Halifax Regional Municipality, Nova Scotia, Canada. The growing trend of auto-oriented lifestyle choices and dependency not only intensifies environmental emissions and energy use but leads to decreased AT use for daily activities. Studies show that the built environment plays a significant role in active mode choice for nonwork trips, which are more flexible in time and location. However, research investigating the effect of lifestyle and attitudes combined with built-environment attributes for AT use has been limited, particularly for weeklong nonwork trips. Accordingly, this study investigated weekly active travel for nonwork trips on the basis of data from the Halifax Household Mobility and Travel Survey. Factor analysis captured the effects of lifestyle choices and attitudes, which were categorized by individuals' attitudes toward (a) travel modes and (b) land use and the environment. From loading the factors of the lifestyle choice variables, nine attitudinal variables were obtained. The study employed an ordered probit modeling framework to examine relative contributions of relevant socioeconomic characteristics, built-environment attributes, and attitudinal factors. Model results revealed that attitudes and factors of lifestyle choice played important roles in weekly AT frequency for nonwork trips. For example, individuals with prowalk–probike and protransit attitudes were likely to use AT more frequently for non-work-related trips than their counterparts. Although the impact of individuals' attitudes on AT trips was evident, this model also demonstrated that the built environment significantly influences the frequency of AT trips.

Inefficiencies in the process of acquiring and managing real property have a significant impact on transportation agencies' ability to develop and deliver projects effectively. Acquisition of real property is frequently on the critical path of those projects. Delays in acquiring real property are one of the main reasons for project delays and cost overruns. Federal and state agencies are interested in developing strategies for streamlining practices for acquisition of real property. In 2010, NCHRP sponsored a research study to develop improved, integrated real property procedures and business practices within the process of transportation project development and delivery, as well as to develop recommendations for best practices in property management. This paper presents some of the results of that effort and focuses on the improvement and optimization of the current state of practice in acquiring real property by negotiation and condemnation. The analysis resulted in the following research products: (a) an integrated model of the process of transportation project development and delivery, (b) a model for real property acquisition and relocation assistance in accordance with 42 USC 4601 et seq. (not constrained by regulatory encumbrances), and (c) a discussion of issues and challenges affecting project development and delivery that typically involve real property components as well as strategies for addressing those issues and challenges. The discussion includes an analysis of 20 negotiation and condemnation issues and challenges that practitioners identified via a national survey and follow-up interviews as well as 20 corresponding strategies for improvement or optimization.

The regulation and the management of urban transport services are often fragmented across multiple institutions. The need for a lead institution to take comprehensive responsibility for urban transport is well recognized. However, attempts in some developing countries to establish effective institutions have not proved successful. This paper seeks to highlight the causes of this lack of success in two cities—Metropolitan Manila, Philippines, and Dakar, Senegal—across two continents. The paper argues that several challenges, even beyond establishing the institutions themselves, need to be addressed if these institutions are to prove effective. Inadequate definition of their role and overlap of responsibilities with other agencies, coupled with inadequate power over financial resources, can render them ineffective.