Walkability and bikeability indices are used to succinctly quantify how conducive an environment is to walking and cycling, often including factors related to comfort and perceived safety. The potential assumption that “walkable” and “bikeable” mean safe for walking and cycling (i.e., the association with objective safety or crash risk) has not yet been examined. This study investigates the association between two widely used measures (walk score and bike score) and pedestrian and cyclist crashes in Vancouver, Canada, to determine whether more walkable and bikeable areas of the city are also safer for walking and biking, after controlling for exposure. Multivariate Bayesian crash models with random and spatial effects are developed for pedestrian–motor-vehicle and cyclist–motor-vehicle crashes in 134 traffic analysis zones using 5 years of crash data with walking, cycling, and motor-vehicle traffic volume controls for exposure. Results indicate that areas of the city with higher walkability and bikeability can be potentially associated with greater pedestrian and cyclist crash risk, respectively, even after controlling for exposure. While the clear answer is that neighborhood walkability and bikeability does not indicate safety for pedestrians and cyclists, questions remain as to whether they should, and if so, how they could be modified to better incorporate objective risk.
Cyclist noise exposure has implications for health, comfort, and safety. Methods used for in situ measurement of on-road noise levels for cyclists vary, and the effects of key study design factors have not been investigated. To enable reliable research into cyclist noise exposure, this study aims to determine the accuracy of smartphone noise measurements in comparison with a sound level meter (SLM) reference instrument, and how noise levels are affected by travel speed, air speed, sensor placement, and use of a windscreen. Field data were collected with paired instruments in a typical urban cycling scenario, and comparisons made varying one design factor at a time (smartphone versus SLM, with versus without windscreen, handlebar versus shoulder placement, etc.). Results show that smartphones can generate reliable measurements (compared with SLM) of high-resolution (1-s) cyclist exposure for C-weighted noise, but not A-weighted noise. Sensor placement and windscreen have small effects on noise readings, but air speed and travel speed greatly affect measured noise levels. Future studies measuring on-road noise must consider the effects of wind- and bicycle-generated noise to ensure internal validity. Studies should also consider both study objectives and instrumentation when selecting a noise measure (frequency weighting). Research is needed into bicycle noise generation and perception of traffic noise by cyclists to enhance the reliability of future studies.
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