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Enhancing Vulnerable Road User Detection and Volume Data Through Advanced Imaging Techniques

Sector: Advanced Electronics • Location: Washington, United States of America (USA)

Source: Federal Highway Administration (FHWA)

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Active

Vulnerable road users (VRUs) are those individuals who are more at risk for serious injury or death if they are involved in a traffic crash, including (but are not limited to) pedestrians, bicyclists, scooters, and other micromobility device users. The Federal Highway Administration (FHWA) developed a vehicle to pedestrian (V2P) test bed on the Turner-Fairbank Highway Research Center (TFHRC) campu

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The project “Enhancing Vulnerable Road User Detection and Volume Data Through Advanced Imaging Techniques” is an infrastructure initiative in the Advanced Electronics sector, located in Washington, United States of America (USA). Taiyo aggregates data on it from Federal Highway Administration (FHWA).

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Description

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Vulnerable road users (VRUs) are those individuals who are more at risk for serious injury or death if they are involved in a traffic crash, including (but are not limited to) pedestrians, bicyclists, scooters, and other micromobility device users. The Federal Highway Administration (FHWA) developed a vehicle to pedestrian (V2P) test bed on the Turner-Fairbank Highway Research Center (TFHRC) campus. V2P technology involves “vehicles that can sense the environment around them and communicate that information to other […] personal mobile devices.”[1] The test bed serves as a testing ground for V2P technologies and sensors to support pedestrian and bicyclist system concepts, standards, applications, and innovative products. As part of the V2P test bed, FHWA recently installed FLIR Systems, Inc. TrafiSense2 sensors on the TFHRC campus that are forward looking infrared (FLIR) integrated thermal sensors and detectors for vehicle, pedestrian, and bike detection. The objectives of this task order are to conduct a study to evaluate the capabilities of the TrafiSense2 alone and in combination with the LiDAR on the TFHRC campus for detecting and collecting pedestrian, bicycle, and scooter data, specifically to: test the technologies’ ability to detect pedestrians, bicyclists, and scooters at the intersections and marked mid-block crossing at TFHRC in different conditions (e.g., light, dark, rain, wind, congestion, heavy clothing), evaluate the technologies’ appropriateness and applicability for collecting bicycle, pedestrian, and scooter count data that can be used to provide information for measuring exposure, and establish the capability to use the two technologies in combination.

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100%

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