4.7 Article

Effectiveness of light-reflecting devices: A systematic reanalysis of animal-vehicle collision data

Journal

ACCIDENT ANALYSIS AND PREVENTION
Volume 97, Issue -, Pages 242-260

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.aap.2016.08.030

Keywords

Animal-vehicle collision; Cervids; Wildlife warning reflector; Systematic review; Road ecology

Funding

  1. foundation Dr. Joachim und Hanna Schmidt Stiftung fur Umwelt und Verkehr

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Every year, approximately 500 human fatalities occur due to animal-vehicle collisions in the United States and Europe. Especially heavy-bodied animals affect road safety. For more than 50 years, light-reflecting devices such as wildlife warning reflectors have been employed to alert animals to traffic when crossing roads during twilight and night. Numerous studies addressed the effectiveness of light-reflecting devices in reducing collisions with animals in past decades, but yielded contradictory results. In this study, we conducted a systematic literature review to investigate whether light-reflecting devices contribute to. an effective prevention of animal-vehicle collisions. We reviewed 53 references and reanalyzed original data of animal-vehicle collisions with meta-analytical methods. We calculated an effect size based on the annual number of animal-vehicle collisions per kilometer of road to compare segments with and without the installation of light-reflecting devices for 185 roads in Europe and North America. Our results indicate that light-reflecting devices did not significantly reduce the number of animal-vehicle collisions. However, we observed considerable differences of effect sizes with respect to study duration, study design, and country. Our results suggest that length of the road segment studied, study duration, study design and public attitude (preconception) to the functioning of devices may affect whether the documented number of animal-vehicle collisions in- or decrease and might in turn influence whether results obtained were published. (C) 2016 Elsevier Ltd. All rights reserved.

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