The Relationship between Community Design and Crashes Involving Older Drivers and Pedestrians

Dumbaugh, Eric; Zhang, Yi

doi:10.1177/0739456x12468771

Cited by 26 publications

(16 citation statements)

References 18 publications

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“…In addition to the preceding contributing factors, road network structures have been identified as important in determining traffic safety, especially for pedestrians (Marshall and Garrick, 2010b;Rifaat et al, 2011Rifaat et al, , 2012Wei and Lovegrove, 2012;Dumbaugh and Zhang, 2013;Zhang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach

Guo

Pei

et al. 2017

Accident Analysis & Prevention

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Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data.

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Section: Introductionmentioning

confidence: 99%

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach

Guo

Pei

et al. 2017

Accident Analysis & Prevention

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“…An alternative framework relating roadside design to traffic safety, potentially better suited to urban settings, posits that drivers are more aware of potential hazards and engage in less risky behavior when their environment is more constrained and offers less design consistency (Figure 2b) (3)(4)(5)(6)(7). It takes advantage of driver agency to respond to environmental conditions with slower speeds, improving a driver's capacity to react to unpredictable events and reducing the severity of crashes when they do take place.…”

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).…”

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confidence: 94%

Urban Streetscape Design and Crash Severity

Harvey

Aultman-Hall

2015

Transportation Research Record: Journal of the Transportation R

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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.

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“…Older drivers were most often associated with low mileage. Dumbaugh and Zhang [16] investigated the causality between urban form and crashes involving senior drivers and found that community design features, such as arterial thoroughfares, commercial strips, and big box stores, were related to crashes for older adults, and that pedestrian-scaled retail areas ensured mobility for older adults. groups.…”

Section: Introductionmentioning

confidence: 99%

Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

2019

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As a characteristic of senior drivers aged 65 +, the low-mileage bias has been reported in previous studies. While it is thought to be a well-known phenomenon caused by aging, the characteristics of urban environments create more opportunities for crashes. This calls for investigating the low-mileage bias and scrutinizing whether it has the same impact on other age groups, such as young and middle-aged drivers. We use a crash database from the Ohio Department of Public Safety from 2006 to 2011 and adopt a macro approach using Negative Binomial models and Conditional Autoregressive (CAR) models to deal with a spatial autocorrelation issue. Aside from the low-mileage bias issue, we examine the association between the number of crashes and the built environment and socio-economic and demographic factors. We confirm that the number of crashes is associated with vehicle miles traveled, which suggests that more accumulated driving miles result in a lower likelihood of being involved in a crash. This implies that drivers in the low mileage group are involved in crashes more often, regardless of the driver’s age. The results also confirm that more complex urban environments have a higher number of crashes than rural environments.

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The Relationship between Community Design and Crashes Involving Older Drivers and Pedestrians

Cited by 26 publications

References 18 publications

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach

Urban Streetscape Design and Crash Severity

Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

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