Influence of Land Use, Population, Employment, and Economic Activity on Accidents

Kim, Karl; Brunner, I Made; Yamashita, Eric

doi:10.1177/0361198106195300107

Cited by 58 publications

(25 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In particular, workers per residents (WKGD) is associated with C car , C truck , C seg , C peaknight and C day . These results confirm earlier research by Lovegrove et al [15] and Kim et al [39,94]. The difference between C peaknight and C peakday is related to the different activities carried out during the hours of the day.…”

Section: Resultssupporting

confidence: 92%

See 1 more Smart Citation

Development of Macro-Level Safety Performance Functions in the City of Naples

et al. 2019

View full text Add to dashboard Cite

This paper presents macro-level safety performance functions and aims to provide empirical tools for planners and engineers to conduct proactive analyses, promote more sustainable development patterns, and reduce road crashes. In the past decade, several studies have been conducted for crash modeling at a macro-level, yet in Italy, macro-level safety performance functions have neither been calibrated nor used, until now. Therefore, for Italy to be able to fully benefit from applying these models, it is necessary to calibrate the models to local conditions. Generalized linear modelling techniques were used to fit the models, and a negative binomial distribution error structure was assumed. The study used a sample of 15,254 crashes which occurred in the period of 2009–2011 in Naples, Italy. Four traffic analysis zones (TAZ) levels were used, as one of the aims of this paper is to check the extent to which these zoning levels help in addressing the issue. The models were developed by the stepwise forward procedure using explanatory Socio-Demographic (S-D), Transportation Demand Management (TDM), and Exposure variables. The most significant variables were: children and young people placed in re-education projects, population, population aged 65 and above, population aged 25 to 44, male population, total vehicle kilometers traveled, average congestion level, average speed, number of trips originating in the TAZ, number of trips ending in the TAZ, number of total trips and, number of bus stops served per hour. An important result of the study is that children and young people placed in re-education projects negatively affects the frequency of crashes, i.e., it has a positive safety effect. This demonstrates the effectiveness of education projects, especially on children from disadvantaged neighbourhoods.

show abstract

Section: Resultssupporting

confidence: 92%

“…Hbus is a proxy for pedestrian traffic, so the positive sign indicates a growing correlation with crashes. The association between increased collisions and increased bus stops (BS) is consistent with researches of Kim et al [39,94], Wei et al [88] and Rhee et al [98]. A larger number of subway stations were found to increase traffic crashes.…”

Section: Resultssupporting

confidence: 85%

Development of Macro-Level Safety Performance Functions in the City of Naples

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Population density contributes significantly to the number of crashes caused by drivers aged between 24 and 64. These results confirm the results of previous studies [24,31,35,43], except for Dumbaugh and Rae [33], who found that population density had a negative effect on the number of injury crashes. The number of household-occupied housing units has a positive and significant impact on crashes by young drivers.…”

Section: Discussionsupporting

confidence: 92%

“…As a result, we adopted a negative binomial model to control for the problems of overdispersion (presence of greater variability) or under dispersion (presence of less variability) based on the observed variance. This model was the preferred approach used in other crash frequency studies [24,25,[30][31][32][33][34][35][36][37][38]. The Poisson model proved inadequate, but the negative binomial model proved to be appropriate.…”

Section: Statistical Analysesmentioning

confidence: 99%

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

2019

View full text Add to dashboard Cite

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.

show abstract

“…Consistent with previous studies, pedestrian collision rates were nearly doubled in locations with marked crosswalks (Koepsell et al 2002, Zegeer et al 2005, Mitman et al 2008). Locations in areas that likely have higher pedestrian activity due to more businesses (i.e., higher employment and fast food density), higher residential density, and more bus use had higher pedestrian collision rates, similar to findings in previous studies (Lightstone et al 2001, Kim et al 2006, Miranda-Moreno et al 2011, Moudon et al 2011). Areas with higher proportions of non-Hispanic blacks or other races also experienced higher collision rates, which may be the result of greater pedestrian activity in these neighborhoods (Cottrill and Thakuriah 2010).…”

Section: Discussionsupporting

confidence: 86%

Multilevel models for evaluating the risk of pedestrian–motor vehicle collisions at intersections and mid-blocks

Quistberg

Howard

Ebel

et al. 2015

Accident Analysis & Prevention

View full text Add to dashboard Cite

Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian-motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007-2013 pedestrian-motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian-motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity.

show abstract

Influence of Land Use, Population, Employment, and Economic Activity on Accidents

Cited by 58 publications

References 9 publications

Development of Macro-Level Safety Performance Functions in the City of Naples

Development of Macro-Level Safety Performance Functions in the City of Naples

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

Multilevel models for evaluating the risk of pedestrian–motor vehicle collisions at intersections and mid-blocks

Contact Info

Product

Resources

About