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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Assessing the Effectiveness of Bicycle Infrastructure Treatments through a Large-Scale Trajectories collected with Drones</title>
      <link>https://rip.trb.org/View/2325391</link>
      <description><![CDATA["Assessing the Effectiveness of Bicycle Infrastructure Treatments through a Large-Scale Trajectories collected with Drones" is a comprehensive study designed to evaluate the safety implications of various bicycle infrastructure treatments, such as bike lanes, protected bike lanes, bike boxes, and two-stage turn queue boxes in urban environments. Recognizing the limitations of current research methods that either focus on single intersections or rely on simulations and underreported crash data, this project proposes a novel approach using drones to collect extensive trajectories of all road users in signalized urban arterials. The two-fold objective of the study is to implement a large-scale experiment with drones to gather detailed modal trajectories and to utilize these data to develop surrogate safety measures for evaluating the impact of bicycle infrastructure treatments on bicyclist and motorist safety.

The research plan is structured around two primary questions: identifying effective surrogate safety metrics for bicycle treatments along arterials and understanding the influence of the continuity and density of bicycle infrastructure on road user behavior. The study will utilize drones to monitor areas with various bicycle infrastructure treatments, capturing the behavior of motorists and vulnerable road users, especially bicyclists. The drone flights, conducted by MobiLysis, will record traffic during peak periods on selected signalized arterials with diverse socioeconomic characteristics and bicycle demand. Trajectories extracted from drone footage will be analyzed to develop surrogate safety measures, correlating them with factors such as infrastructure type, connectivity, density, and road geometry.]]></description>
      <pubDate>Fri, 19 Jan 2024 10:43:37 GMT</pubDate>
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      <title>Evaluation of Surrogate Measures for Pedestrian Safety in Various Road and Roadside Environments</title>
      <link>https://rip.trb.org/View/1250658</link>
      <description><![CDATA[Most analyses of pedestrian traffic safety measure safety in terms of police-reported traffic accidents. For pedestrian safety, it may be more useful to observe surrogate measures of safety, such as a "severe conflict" between a pedestrian and a motor vehicle in order to offer a broader picture of the safety at a particular road location than just considering police-reported accidents. This could help planners and designers learn how to select road and roadside elements to make pedestrians feel safer and thus increase the effectiveness of strategies or development patterns aimed at increasing the livability of communities. The objective of this project is thus to investigate the relationship between roadway and roadside design elements and traffic incidents involving pedestrians. Specifically, the researchers will select a set of intersections known to have substantial pedestrian volumes and with targeted roadway and roadside characteristics, such as the pedestrian crossing distance, presence or absence of on-street parking, type of traffic control, 85th percentile traffic speed, and the surrounding land use type and density. At these intersections, the team will count the flow of pedestrians and motor vehicles and the conflicts between pedestrians and vehicles over a period of several hours using the Swedish Traffic Conflict Technique. Appropriate and accurate statistical models will then be fitted in order to predict conflict counts as a function of these road and roadside features. The researchers will also gather from a crash database reported pedestrian accident counts at the locations over several years, and estimate statistical models relating the occurrence of incidents with the crash counts, to learn more about the relevance of the incident count as a surrogate for accidents in safety analysis.]]></description>
      <pubDate>Fri, 17 May 2013 01:00:31 GMT</pubDate>
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