Concerns about Methodology Used in Real-World Experiments on Transport and Transport Safety

Hutchinson, T. P.

doi:10.1061/(asce)0733-947x(2007)133:1(30)

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…Researchers can collaborate with municipal agencies to plan staged, and even randomized, introduction of bicycle lanes or other infrastructure, and can collect pre-and post-intervention crash data. This would allow us not only to demonstrate the value of bicycle lanes, but also to examine differential impact of bicycle infrastructure design innovation (Hutchinson, 2007). Intersection exit counts and stop types.…”

Section: Discussionmentioning

confidence: 99%

Where do bike lanes work best? A Bayesian spatial model of bicycle lanes and bicycle crashes

et al. 2018

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US municipalities are increasingly introducing bicycle lanes to promote bicycle use, increase roadway safety and improve public health. The aim of this study was to identify specific locations where bicycle lanes, if created, could most effectively reduce crash rates. Previous research has found that bike lanes reduce crash incidence, but a lack of comprehensive bicycle traffic flow data has limited researchers' ability to assess relationships at high spatial resolution. We used Bayesian conditional autoregressive logit models to relate the odds that a bicycle injury crash occurred on a street segment in Philadelphia, PA (n = 37,673) between 2011 and 2014 to characteristics of the street and adjacent intersections. Statistical models included interaction terms to address the problem of unknown bicycle traffic flows, and found bicycle lanes were associated with reduced crash odds of 48% in streets segments adjacent to 4-exit intersections, of 40% in streets with oneor two-way stop intersections, and of 43% in high traffic volume streets. Presence of bicycle lanes was not associated with change in crash odds at intersections with less or more than 4 exits, at 4way stop and signalized intersections, on one-way streets and streets with trolley tracks, and on streets with low-moderate traffic volume. The effectiveness of bicycle lanes appears to depend most on the configuration of the adjacent intersections and on the volume of vehicular traffic. Our approach can be used to predict specific street segments on which the greatest absolute reduction in bicycle crash odds could occur by installing new bicycle lanes.

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Section: Discussionmentioning

confidence: 99%

Where do bike lanes work best? A Bayesian spatial model of bicycle lanes and bicycle crashes

et al. 2018

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“…Before-and-after surveys are well recognized for their role in supporting rigorous evaluations of transport interventions (12), with this approach most commonly adopted for travel plans at existing sites (13). The before survey can provide a baseline estimate of travel patterns and also inform the development of the travel plan, whereas the after surveys can be used to assess changes in travel behavior that may have occurred.…”

Section: Methods For Evaluating Travel Plans At New Developmentsmentioning

confidence: 99%

Understanding Travel Plan Effectiveness for New Residential Developments

Gruyter

Rose

Currie

2015

Transportation Research Record: Journal of the Transportation R

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Travel plans can be required for new or expanded buildings as part of the process of land use planning and approval. The purpose of these plans is to manage car use of future building occupants and support access by more sustainable forms of transport. Although the effectiveness of travel plans is generally well established at preexisting sites, there is very little evidence of the impacts when they are applied to new developments, particularly residential sites. In response to this situation, a series of multi modal person trip counts and parking surveys was undertaken at four case sites (residential developments with travel plans) and four control sites (similar residential developments without travel plans) in Melbourne, Australia. Results indicated that the average weekday (7:00 a.m. to 9:00 a.m.) mode share for car driver trips was 14 percentage points lower at the case sites than at the control sites. The findings also highlighted issues with relying solely on comparisons with secondary data sources, such as published vehicle trip generation rates and regional travel survey data, to assess travel plan effectiveness. Such reliance was shown to lead to an overestimation of travel plan impacts because of inconsistencies in the geographical locations and data collection periods of the secondary data sources. This finding highlights the importance of using suitable control sites to account for such factors. Further work is needed to strengthen the evidence base through evaluating travel plans at other residential developments and also accounting for residential self-selection effects.

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Safety effects of blue cycle crossings: A before-after study

Jensen¹

2008

Accident Analysis & Prevention

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Concerns about Methodology Used in Real-World Experiments on Transport and Transport Safety

Cited by 5 publications

References 25 publications

Where do bike lanes work best? A Bayesian spatial model of bicycle lanes and bicycle crashes

Where do bike lanes work best? A Bayesian spatial model of bicycle lanes and bicycle crashes

Understanding Travel Plan Effectiveness for New Residential Developments

Safety effects of blue cycle crossings: A before-after study

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