Using GIS to develop a performance-based framework for evaluating urban design and crash incidence

Dumbaugh, Eric; Rae, Robert; Wunneberger, Douglas

doi:10.1057/udi.2010.16

Cited by 7 publications

(15 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such studies have drawn on land use and roadway data as indicators of built-environment design rather than direct measurements of the streetscape. Several papers by Dumbaugh and colleagues have evaluated built environment-safety relationships by using parcel-level land use data aggregated by census units (3,5,8,11,21). He and his coauthors consistently found that streets lined by parcels with strip malls and big-box stores were associated with greater crash risk, while those lined by pedestrian-scale retail were less risky.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Highway engineering in rural environments traditionally stresses the importance of clear zones on either side of a roadway to provide long sight lines and leeway for driver error and recovery (Figure 1a) (1). In contrast, recent studies in urban settings suggest that human-scale streetscapes, which are smaller and more narrowly enclosed by buildings and trees, may reduce crash risk by narrowing drivers' fields of view and encouraging slower, less risky driving behavior (2)(3)(4)(5)(6)(7)(8)(9)(10)(11). Enclosure is the collective effect of large objects surrounding a street, chiefly buildings and trees, to define the spatial extents of a streetscape and restrict long sight lines; it is what some urban designers say makes a street feel like an "outdoor room" (Figure 1b) (12).…”

mentioning

confidence: 94%

See 1 more Smart Citation

Urban Streetscape Design and Crash Severity

Harvey

Aultman-Hall

2015

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

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.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

mentioning

confidence: 94%

Urban Streetscape Design and Crash Severity

Harvey

Aultman-Hall

2015

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…Until now, many studies have integrated some variables of the built environment in their traffic safety research (5,(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23). However, because of the wide range of research purposes, different variables have been used for each D dimension.…”

Section: Built Environment and Crashesmentioning

confidence: 99%

“…Because the demographic data were based on census block or block group, aggregation of the data at block group proved easy. Assignment of crashes to block groups was conducted by following methods in the literature (5,22). A 200-ft buffer was created around each block group, and the buffer area was used to calculate the number of crashes inside the buffered block group.…”

Section: Preparation Of Crash and Built-environment Datamentioning

confidence: 99%

See 1 more Smart Citation

Geographic Information System–Based Community-Level Method to Evaluate the Influence of Built Environment on Traffic Crashes

Bejleri

2014

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Most current research analyzing traffic crashes is done at either the spot level or the regional level. Less attention is placed at the community level. In addition, the effects of changes in land use, population growth, and transportation networks on community traffic safety have not been systematically studied. Although a number of studies have defined some variables to describe the influence of the built environment on traffic crashes, no research has looked at this problem through a comprehensive framework of relevant built-environment variables. This study explored a geographic information system–based community-level method to understand the effects of the built environment on traffic crashes. The census block group was selected as the analysis unit for the study. The framework of D transportation variables, including the dimensions of density, diversity, design, destination accessibility, and distance to transit, was used to characterize the built environment. The crash and built-environment data were processed in a geographic information system, and the negative binomial model was applied. The results showed that density had little influence on any type of crash; however, the mixed land use was positively associated with all crash categories. Furthermore, street length and number of segments under the design variables resulted in positive coefficients. However, the number of intersections was negative to all crash types. Moreover, whereas the number of bus stops showed a positive influence on crashes, the coefficient that designated the distance of crashes from bus stops and commercial sites was negative.

show abstract