Estimating the safety benefit of separated cycling infrastructure adjusted for behavioral adaptation among drivers; an application of agent-based modelling

Thompson, Jason; Wijnands, Jasper S.; Savino, Giovanni; Lawrence, Brendan; Stevenson, Mark

doi:10.1016/j.trf.2017.05.006

Cited by 16 publications

(17 citation statements)

References 38 publications

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“…However, much of the success is attributed to substantial investment in public education, behaviour-change, and enforcement activities 52 whose impact now appears to be waning as reductions in aggregate and per capita injuries plateau, or are even beginning to increase again. 17,53,54 The findings from this study suggest that more upstream investment in urban design that supports transport mode shift away from motor vehicles and into lower risk modes such as rail 1,4,55 or safe active transport (ie, where separated or protected infrastructure is provided) 56 can be harnessed to deliver reductions in transport injury.…”

Section: Discussionmentioning

confidence: 91%

A global analysis of urban design types and road transport injury: an image processing study

Thompson

Stevenson

Wijnands

et al. 2020

The Lancet Planetary Health

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Background Death and injury due to motor vehicle crashes is the world's fifth leading cause of mortality and morbidity. City and urban designs might play a role in mitigating the global burden of road transport injury to an extent that has not been captured by traditional safe system approaches. We aimed to determine the relationship between urban design and road trauma across the globe. Methods Applying a combined convolutional neural network and graph-based approach, 1692 cities capturing one third of the world's population were classified into types based on urban design characteristics represented in sample maps. Associations between identified city types, characteristics contained within sample maps, and the burden of road transport injury as measured by disability adjusted life-years were estimated through univariate and multivariate analyses, controlling for the influence of economic activity.

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Section: Discussionmentioning

confidence: 91%

A global analysis of urban design types and road transport injury: an image processing study

Thompson

Stevenson

Wijnands

et al. 2020

The Lancet Planetary Health

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“…In a series of ABMs, Thompson et al [14][15][16] That is, at specific times and locations where cyclist density is high, the movement of motor-vehicles (and potential collisions) is restricted because time gaps between cyclists are smaller and more likely to be rejected by drivers. At specific locations and times when cyclist density is low, time-gaps are larger and more likely to be accepted by drivers, resulting in higher per-capita collision risk as drivers and cyclists more frequently interact.…”

Section: Discussionmentioning

confidence: 99%

“…However, it is possible that the strength of the original findings may have led to a subsequent degree of observer dependence, whereby data collection has largely continued to follow existing theory focused on 'numbers' of cyclists across a system rather than alternative spatial mechanisms as described here. Instead, the synthetic evidence collected from ABMs [14][15][16] has enabled a new perspective on the way we could collect observational data [29] related to cycling safety that has been operationalised in this study.…”

Section: Discussionmentioning

confidence: 99%

“…Recognising these limitations, previous work has attempted to create agent-based models (ABMs) of cyclist vs car interactions within simulated transport systems [14][15][16]. ABMs allow both macro and micro-level behaviour of systems to be observed.…”

Section: Introductionmentioning

confidence: 99%

“…The results of ABMs of car vs cyclist interactions have suggested that the SiN effect can be replicated in simulated transport systems where drivers demonstrate behavioural adaptation in response to exposure to cyclists [15,16]. However, it can also be replicated in circumstances where drivers show no capacity to 'learn' to drive safely around cyclists at all [14].…”

Section: Introductionmentioning

confidence: 99%

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Evidence for the ‘safety in density’ effect for cyclists: validation of agent-based modelling results

et al. 2018

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The safety in numbers (SiN) effect for cyclists is widely observed but remains poorly understood. Although most studies investigating the SiN phenomenon have focused on behavioural adaptation to ‘numbers’ of cyclists in the road network, previous work in simulated environments has suggested SiN may instead be driven by increases in local cyclist spatial density, which prevents drivers from attempting to move through groups of oncoming cyclists. This study therefore set out to validate the results of prior simulation studies in a real-world environment. Time-gap analysis of cyclists passing through an intersection was conducted using 5 hours of video observation of a single intersection in the city of Melbourne, Australia, where motorists were required to ‘yield’ to oncoming cyclists. Results demonstrated that potential collisions between motor vehicles and cyclists reduced with increasing cyclists per minute passing through the intersection. These results successfully validate those observed under simulated conditions, supporting evidence of a proposed causal mechanism related to safety in density rather than SiN, per se. Implications of these results for transportation planners, cyclists and transportation safety researchers are discussed, suggesting that increased cyclist safety could be achieved through directing cyclists towards focused, strategic corridors rather than dispersed across a network.

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On-road bicycle lane types, roadway characteristics, and risks for bicycle crashes

Morrison

Thompson

Kondo

et al. 2019

Accident Analysis & Prevention

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Bicycle lanes reduce real and perceived risks for bicycle vs. motor vehicle crashes, reducing the burden of traffic injuries and contributing to greater cycling participation. Previous research indicates that the effectiveness of bicycle lanes differs according to roadway characteristics, and that bicycle lane types are differentially associated with reduced crash risks. The aim of this study is to combine these perspectives and identify the types of on-road bicycle lanes that are associated with the greatest reductions in bicycle crashes given the presence of specific roadway characteristics. We compiled a cross sectional spatial dataset consisting of 32,444 intersection polygons and 57,285 street segment polygons representing the roadway network for inner Melbourne, Australia. The dependent measure was a dichotomous indicator for any bicycle crash (2014-2017). Independent measures were bicycle lanes (exclusive bicycle lanes, shared bicycle and parking lanes, marked wide kerbside lanes, and kerbside bicycle lanes) and other roadway characteristics (speed limit, bus routes, tram routes, bridges, one-way flow, traffic lane width). In Bayesian conditional autoregressive logit models, bicycle lanes of all types were associated with decreased crash odds where speeds were greater, bus routes and tram stops were present, and traffic lanes were narrower. Only exclusive bicycle lanes were associated with reduced crash odds (compared to the expected odds given the presence of the bicycle lane and the roadway conditions) in all these setting. The extent to which on-road bicycle lanes reduce crash risks depends on the bicycle lane type, the roadway conditions, and the combination of these two factors. Bicycle lanes

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Estimating the safety benefit of separated cycling infrastructure adjusted for behavioral adaptation among drivers; an application of agent-based modelling

Cited by 16 publications

References 38 publications

A global analysis of urban design types and road transport injury: an image processing study

A global analysis of urban design types and road transport injury: an image processing study

Evidence for the ‘safety in density’ effect for cyclists: validation of agent-based modelling results

On-road bicycle lane types, roadway characteristics, and risks for bicycle crashes

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