How Differences in Roadways Affect School Travel Safety

Yu, Chia-Yuan

doi:10.1080/01944363.2015.1080599

Cited by 32 publications

(29 citation statements)

References 43 publications

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“…Thus, three- and four-or-more-leg intersection densities needed to be considered separately. Regarding the impact of transit services, some studies have reported that a greater number of transit stops are associated with a reduced number of collisions (Clifton and Kreamer-Fults 2007; Yu 2015b). This study considered the transit stop density of each spatial unit to be a representation of the availability of transit service.…”

Section: Methodsmentioning

confidence: 99%

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Local Variations in the Impacts of Built Environments on Traffic Safety

2017

Journal of Planning Education and Research

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This study examined the influence of built environments on crashes with different levels of injury severity, and employed Geographically Weighted Negative Binomial Regressions to test whether these relationships varied across different neighborhoods in Austin, Texas. The results showed that high-speed roads produced more total and fatal crashes, and their influence was stronger in downtown areas than in peripheral regions. Commercial and office areas experienced more injury crashes, especially in downtown locations. It is crucial to implement programs to reduce vehicle travel demand, retrofit high-speed roads, and design land areas that generate fewer vehicle trips, especially for downtown spaces.

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Section: Methodsmentioning

confidence: 99%

“…In terms of design, nonmotorized infrastructure may provide a separation space for pedestrians/cyclists and vehicles, which could improve safety (Yu 2015b). Thus, this study included the level of sidewalk and bike lane completeness of each spatial unit.…”

Section: Methodsmentioning

confidence: 99%

Local Variations in the Impacts of Built Environments on Traffic Safety

2017

Journal of Planning Education and Research

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“…Studies have shown that the likelihood of pedestrian crashes is impacted by the characteristics of the micro-environment around crash-risk locations (e.g., roadway characteristics and traffic conditions) as well as the characteristics of the macro-environments (e.g., neighborhood characteristics such as development densities and land uses that generate or attract pedestrian travel) [6,7,8,9,10,11]. More specifically, past studies have focused on modelling two types of outcomes: The severity of pedestrian injury and the frequency of pedestrian crashes.…”

Section: Introductionmentioning

confidence: 99%

Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS

Kang

Moudon

Kim

et al. 2019

IJERPH

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Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modelling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.

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“…Certain authors advocate a maximum speed of 30 km/h as a measure for reducing the occurrence of head injuries among child pedestrians involved in road accidents (Liu & Yang, 2003). The other major risk factortraffic volume-was not often mentioned by the children in our discussion groups, despite its importance in road safety research on child pedestrian and cyclist injuries (Bennet & Yiannakoulias, 2015;Ewing & Dumbaugh, 2009;Roberts et al, 1995;Stevenson, 1997;Yu, 2015). This can partially be explained by the fact that most of the schools in our study were located on streets with low traffic volume.…”

Section: Discussionmentioning

confidence: 78%

‘They installed a speed bump’: children’s perceptions of traffic-calming measures around elementary schools

Torres

Cloutier

Bergeron

et al. 2019

Children's Geographies

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Growing scientific literature evaluates the impact of traffic-calming devices in terms of mobility behavior and safety, but little is known about their perceived impact from the point of view of children. Our study asks children about their perceptions of different traffic-calming measures around their schools. It draws on data gathered through eight focus groups, followed by walking tours with Grade 6 children (11-12 years old) (n=65, 27 boys, 38 girls) from elementary schools in different urban contexts in Quebec, Canada. Qualitative analysis of the discussions shows that a) vehicle speed is the main perceived threat for participant children; b) children are confident about the effectiveness of selfenforcing traffic-calming devices that reshape the street geometry; and c) they are skeptical about the effectiveness of "informative" measures such as signs and lines (marked pavement). Our findings inform public policy for a more effective promotion of walking and cycling among children.

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How Differences in Roadways Affect School Travel Safety

Cited by 32 publications

References 43 publications

Local Variations in the Impacts of Built Environments on Traffic Safety

Local Variations in the Impacts of Built Environments on Traffic Safety

Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS

‘They installed a speed bump’: children’s perceptions of traffic-calming measures around elementary schools

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