Macro-level collision prediction models for evaluating neighbourhood traffic safety

Lovegrove, Gord; Sayed, Tarek

doi:10.1139/l06-013

Cited by 119 publications

(55 citation statements)

References 7 publications

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“…The literature is replete with studies showing that areas with more residents, more employment and more arterial lane miles experience more crashes (Hadayeghi et al, 2003(Hadayeghi et al, , 2006Kmet et al, 2003;Ladro´n de Guevara et al, 2004;Levine et al, 1995aLevine et al, , 1995bLovegrove and Sayed, 2006). Such studies may be useful for crash prediction on individual facilities.…”

Section: Crash Risk Factorsmentioning

confidence: 99%

Urban sprawl as a risk factor in motor vehicle crashes

2014

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A decade ago, compactness/sprawl indices were developed for metropolitan areas and counties which have been widely used in health and other research. In this study, we first update the original county index to 2010, then develop a refined index that accounts for more relevant factors, and finally seek to test the relationship between sprawl and traffic crash rates using structural equation modelling. Controlling for covariates, we find that sprawl is associated with significantly higher direct and indirect effects on fatal crash rates. The direct effect is likely due to the higher traffic speeds in sprawling areas, and the indirect effect is due to greater vehicle miles driven in such areas. Conversely, sprawl has negative direct relationships with total crashes and non-fatal injury crashes, and these offset (and sometimes overwhelm) the positive indirect effects of sprawl on both types of crashes through the mediating effect of increased vehicle miles driven. The most likely explanation is the greater prevalence of fender benders and other minor accidents in the low speed, high conflict traffic environments of compact areas, negating the lower vehicle miles travelled per capita in such areas.

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Section: Crash Risk Factorsmentioning

confidence: 99%

Urban sprawl as a risk factor in motor vehicle crashes

2014

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“…This very important additional attribute of these models provides some extra information as it takes the spatial location of a crash into consideration. Lovegrove and Sayed (2006) concluded that quantifying the relationship between the zonal characteristics such as exposure, network, socio-demographic and TDM variables and crashes at a zonal level provides a predictive tool to predict the NOCs in a TAZ. They used GLM techniques to develop ZCPMs for both urban and rural areas across the Greater Vancouver Regional District (GVRD).…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating the road safety effects of a fuel cost increase measure by means of zonal crash prediction modeling

Pirdavani

Brijs

Bellemans

et al. 2013

Accident Analysis & Prevention

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Travel Demand Management (TDM) consists of a variety of policy measures that affect the transportation system's effectiveness by changing travel behavior. The primary objective to implement such TDM strategies is not to improve traffic safety, although their impact on traffic safety should not be neglected. The main purpose of this study is to evaluate the traffic safety impact of conducting a fuel-cost increase scenario (i.e. increasing the fuel price by 20%) in Flanders, Belgium. Since TDM strategies are usually conducted at an aggregate level, Crash Prediction Models (CPMs) should also be developed at a geographically aggregated level. Therefore Zonal Crash Prediction Models (ZCPMs) are considered to present the association between observed crashes in each zone and a set of predictor variables. To this end, an activitybased transportation model framework is applied to produce exposure metrics which will be used in prediction models. This allows us to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models unlike traditional models in which the impact of TDM strategies are assumed. The crash data used in this study consist of fatal and injury crashes observed between 2004 and 2007. The network and socio-demographic variables are also collected from other sources. In this study, different ZCPMs are developed to predict the Number of Injury Crashes (NOCs) (disaggregated by different severity levels and crash types) for both the null and the fuel-cost increase scenario. The results show a considerable traffic safety benefit of conducting the fuel-cost increase scenario apart from its impact on the reduction of the total Vehicle Kilometers Travelled (VKT). A 20% increase in fuel price is predicted to reduce the annual VKT by 5.02 billion (11.57% of the total annual VKT in Flanders), which causes the total NOCs to decline by 2.83%.

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“…However, recent area-level studies have reported that traffic volume and urban arterial roads are independently associated with a greater incidence of road injuries within neighbourhoods. 3,8,9 In Montréal, the presence of arterial roads at intersections significantly increases the number of injured pedestrians, cyclists and motor-vehicle occupants, even when other intersection characteristics are taken into account. 10 By definition, an urban arterial road has more traffic lanes and is consequently wider, has higher average vehicle speeds and longer emergency stopping distances.…”

mentioning

confidence: 99%

Major urban road characteristics and injured pedestrians: A representative survey of intersections in Montréal, Quebec

Martineau

Archambault

Cloutier

et al. 2015

Can J Public Health

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OBJECTIVES:In urban settings, pedestrian fatalities and injuries are concentrated on major roads. This study aims to describe urban intersections with major roads (arterials and collector roads) and explore the association between intersection characteristics and injured pedestrians. METHODS:From a stratified random sampling in Montréal, Quebec, 512 intersections were selected and their characteristics collected. The number of injured pedestrians from 1999 to 2008 was obtained from ambulance services. Binomial negative regression models (including IRR: incidence rate ratios) were calculated to determine associations between intersection characteristics and injured pedestrians: i) at all intersections; ii) at intersections with multi-lane roads and iii) at signalized intersections with available vehicle and pedestrian counts. RESULTS:Major intersections had more traffic lanes (3.8 vs. 1.7, p < 0.01) and longer pedestrian crossings (18.8 m vs. 12.7 m, p < 0.01) than minor intersections. Bus stops were also more frequent at these intersections (75% vs. 6%, p < 0.01). Overall, each additional traffic lane was associated with a 75% increase in the number of injured pedestrians (IRR = 1.75; 95% confidence interval [CI] = 1.41-2.18). At intersections with multi-lane roads, a fourth branch (IRR = 2.40; 95% CI = 1.53-3.77), vehicles parked within 5 m of the intersection (IRR = 2.40; 95% CI = 1.64-3.51), and marked crosswalks (IRR = 1.79; 95% CI = 1.08-2.95) significantly increased the number of injured pedestrians. Raised medians had no significant protective effect. CONCLUSIONS:The results show that besides traffic and pedestrian volumes, intersection characteristics contribute to pedestrian injuries. The reduction of traffic lanes, parking prohibition near intersections and implementation of appropriate pedestrian refuge areas would improve pedestrian safety.KEY WORDS: Injuries; pedestrian; major roads; intersections; urban health La traduction du résumé se trouve à la fin de l'article.

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Macro-level collision prediction models for evaluating neighbourhood traffic safety

Cited by 119 publications

References 7 publications

Urban sprawl as a risk factor in motor vehicle crashes

Urban sprawl as a risk factor in motor vehicle crashes

Evaluating the road safety effects of a fuel cost increase measure by means of zonal crash prediction modeling

Major urban road characteristics and injured pedestrians: A representative survey of intersections in Montréal, Quebec

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