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https://nap.nationalacademies.org/catalog/27432/critical-issues-in-transportation-for-2024-and-beyond

Development of a Connected Smart Vest for Improved Roadside Work Zone Safety (04-104) [supporting dataset]

Project Description: Roadside work zones (WZs) present imminent safety hazards for roadway workers as well as passing motorists. In 2016, 764 fatalities occurred in work zones in the United States due to motor vehicle traffic crashes. A number of factors (aging highway infrastructure, increased road work, increased levels of traffic and more nighttime WZs) have led to an increase in WZ crashes in the past few years. Consequently, WZs are becoming increasingly dangerous for workers as well as passing motorists. The standard work zone safety signage and personal protective equipment (PPE) worn by workers at roadside WZs have not been completely effective in controlling work zone crashes. A viable solution to this problem is to design a wearable device to accurately localize, monitor, and predict potential collisions between WZ actors based on their movements and activities, and communicate potential collisions to workers, passing drivers, and connected and automated vehicles (CAVs). This project aims to develop a wearable worker localization and communication device (i.e., Smart Vest) that utilizes the previously developed Threat Detection Algorithm (Safe-D project 03-050) to communicate workers’ locations to passing CAVs and proactively warn workers and passing motorists of potential collisions. As a result, this research is expected to significantly improve the safety conditions of roadside WZs through prompt detection and communication of hazardous situations to workers and drivers. The Smart Vest work zone system allows to monitor worker’s location on a deployed work zone who are wearing the Smart Vest device by reading their global positioning system (GPS) data and provide two-level alert patterns when they are approaching to a dangerous location defined by a virtual polygon using the Smart Vest Geo Plotter. Smart Vest computing system allows to gather, log and process GPS data for each Smart Vest device deployed on a work zone. Along with a Geo-Plotter device which is used to create a virtual polygon around the work zone by taking 3 or more points, the system collects the GPS position data for each device, process and determine if the location is inside the virtual polygon. To classify the location, the system determines 3 different location types: “Safe Zone”, “Low Level Warning Zone” and “High Level Warning Zone”. The Low level and safe zones are inside the virtual polygon. Each time the computing system determines a Smart Vest device is crossing between zones, an alert (HMI) is transmitted to the specific device. This alert is auditory/visual and tactor based. Data Scope: A total of 39286 datapoints were collected on a field test work zone setup at VTTI – Automation HUB. The collected data set includes data entries for three Smart Vest devices while moving around a virtual polygon area defined by the Smart Vest Geo Plotter device. The virtual polygon area was defined using 4 point polygon (square shape) and the three Smart Vest were worn inside and outside the virtual polygon and their GPS location was processed to calculate their classification and trigger the proper HMI warnings accordingly when crossing between Safe Zone, Low-level warning area and High-level warning area. Three log files are being provided: GPS Log which contains the Device ID, GPS position, Speed. Every single entry has a timestamp field with date and time. Polygon Log which contains the entries (GPS Latitude/Longitude and Counter) to determine the virtual polygon using the Geo-Plotter device. Work zone Log which contains the classification for each GPS location received by the system using 0,1,2 as Safe Zone, Low Level Alert Zone and High-Level Alert zone respectively.

Language

  • English

Media Info

  • Media Type: Dataset
  • Dataset: Version: 1.0 Integrity Hash:
  • Dataset publisher:

    Dataverse

    ,    

Subject/Index Terms

Filing Info

  • Accession Number: 01784928
  • Record Type: Publication
  • Contract Numbers: 69A3551747115/04-104
  • Files: UTC, NTL, TRIS, ATRI, USDOT
  • Created Date: Oct 18 2021 5:21PM