An Intelligent Video-Based End of Queue Warning System for Work Zones

One of the main needs when addressing back of queue situations is to understand what drivers are doing so that Queue Warning Systems (QWSs) can get a drivers’ attention. The majority of QWSs provide a visual warning (i.e., message sign, flashing beacon, etc.) to drivers that ideally help them be prepared for congestion or queued traffic. However, a driver needs to be properly monitoring the roadway environment in order to receive the warning and then needs to be prepared to take the appropriate actions when necessary. This includes being alert and slowing to a manageable speed. In many cases, drivers are distracted and fail to recognize warnings. In other cases, drivers receive the warning but fail to comply with appropriate speeds. As a result, one of the main needs when addressing back of queue situations is to understand what drivers are doing so that QWSs can get a drivers’ attention. Additionally, driver behavior may indicate that other countermeasures such as speed management may be as effective as a formal QWS. The team plans to address this knowledge gap through the proposed research by utilizing two different datasets to quantity driver behavior and work zone conditions that lead to back of queue conflicts in work zones. First, the team will build on a current project that is studying work zone behavior using the Second Strategic Highway Research Program (SHRP2) naturalistic driving study (NDS) data. The current project being conducted by the team is using these data to evaluate naïve drivers within actual work zones to assess how they react to different work zone traffic controls and what factors (such as distraction) impact how they react. The current project is focused on freeflow conditions. The proposed research will focus on congested and back of queue situations as described in Task 3. The proposed research will also gather data on driver behavior from video surveillance of back of queue situations in the SWZDI states to supplement the information gained from the NDS data as described in Task 4. Tasks include: Task 1: TAC Formation and Quarterly Reports; Task 2: Literature Review; Task 3: Develop Models for Driver Behavior in Encountering Back of Queue; Task 4: Assess Characteristics of End of Queue Conflicts; Task 5: Evaluate QWSs and Make Recommendations; and Task 6: Develop Final Report.

    Language

    • English

    Project

    • Status: Active
    • Funding: $78206
    • Contract Numbers:

      Add 686

      TPF-5(295)

    • Sponsor Organizations:

      Iowa Department of Transportation

      800 Lincoln Way
      Ames, IA  United States  50010
    • Managing Organizations:

      Iowa State University, Ames

      Center for Transportation Research and Education
      2711 South Loop Drive, Suite 4700
      Ames, IA  United States  50010-8664
    • Project Managers:

      Clute, Khyle

    • Principal Investigators:

      Hallmark, Shauna

    • Start Date: 20190101
    • Expected Completion Date: 20200331
    • Actual Completion Date: 0

    Subject/Index Terms

    Filing Info

    • Accession Number: 01691606
    • Record Type: Research project
    • Source Agency: Iowa Department of Transportation
    • Contract Numbers: Add 686, TPF-5(295)
    • Files: RiP, STATEDOT
    • Created Date: Jan 28 2019 10:39AM