L
Luis F. Miranda-Moreno
Researcher at McGill University
Publications - 202
Citations - 6415
Luis F. Miranda-Moreno is an academic researcher from McGill University. The author has contributed to research in topics: Poison control & Pedestrian. The author has an hindex of 39, co-authored 194 publications receiving 5212 citations. Previous affiliations of Luis F. Miranda-Moreno include Université de Montréal & University of Waterloo.
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The link between built environment, pedestrian activity and pedestrian–vehicle collision occurrence at signalized intersections
TL;DR: Results show that a 30% reduction in the traffic volume would reduce the total number of injured pedestrians by 35% and the average risk of pedestrian collision by 50% at the intersections under analysis, and major arterials are found to have a double negative effect on pedestrian safety.
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Risk of injury for bicycling on cycle tracks versus in the street
Anne C. Lusk,Peter G Furth,Patrick Morency,Luis F. Miranda-Moreno,Walter C. Willett,Jack T. Dennerlein +5 more
TL;DR: The data suggest that the injury risk of bicycling on cycle tracks is less than bicycling in streets, and the construction of cycle tracks should not be discouraged.
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The role of built environment on pedestrian crash frequency
TL;DR: In this article, the link of land use and road design on pedestrian safety and the effect of the level of spatial aggregation on the frequency of pedestrian accidents was investigated for New York City based on an extensive dataset collected from different sources over a period of 5 years.
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A clustering regression approach: A comprehensive injury severity analysis of pedestrian–vehicle crashes in New York, US and Montreal, Canada
TL;DR: In this article, the authors combine data mining and statistical regression methods to identify the main factors associated with the levels of pedestrian injury severity outcomes and provide recommendations for policy makers, traffic engineers, and law enforcement in order to reduce the severity of pedestrian-vehicle collisions.
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A latent class modeling approach for identifying vehicle driver injury severity factors at highway-railway crossings.
TL;DR: This research effort attempts to address the issue of risk segmentation within the affected grade crossing population by applying an innovative latent segmentation based ordered logit model to evaluate the effects of various factors on the injury severity of vehicle drivers.