Explore the USDOT / Leidos CAVe-In-A-Box Tool

Ground transportation has one of the most significant impacts on human life. In the blink of an eye, valuable lives of humankind and wildlife could be lost without either of their fault. Intelligent Surface Transportation Management Systems (ISTMS) are aimed at solving these catastrophes to provide comfortable and safe transit to humans while saving infrastructure and nature. To provide safer transportation to the public, for instance, the United States Department of Transportation (USDOT) has prioritized several applications of artificial intelligence (AI) to develop intelligent transportation systems (ITS). Naturally, AI had made its way into transportation in two diverse ways. First, the connected and automated vehicles (CAVs) to solve transportation complexities in driving passenger cars and supplying trucking services. Second, the existing and highly sophisticated transportation infrastructure such as freeways, roadways, traffic signs, intersections, and roundabouts. As cyber-physical systems such as CAVs evolve to intersect with the existing transportation infrastructure, there is a huge risk of potential security threats to humans and wildlife. Specifically, due to limited historical data, access to advanced technology innovations powered by AI and potential exploitation of cyber security vulnerabilities, the risks are significantly raised to cause loss of life. The CAVs are transforming the ISTMS due to their ability to communicate through Vehicle to Everything (V2X) to send and receive data with other Vehicles (V2V), Devices (V2D), Pedestrians (V2P), Cloud (V2C), and Infrastructure (V2I), at the same time. To support the education about the evolution of CAVs in ISTMS, the Federal Highway Administration (FHWA) has developed a connected and automated vehicles education (CAVe)-In-A-box which allows the transportation researchers to access and test the data models used in the ISTMS such as basic safety messages (BSM), signal phase and timing (SPaT), traveler information messages (TIM), and personal safety messages. The goals and objectives of this research are to acquire, assemble, research, design, prototype, test, implement, and deliver a toolbox of software routines with capabilities necessary to assist Ohio Department of Transportation (ODOT) Traffic Monitoring personnel in processing video to detect a pedestrian crossing with or without ASC in the loop. A specific outreach program will also be developed to engage grades 5-12 at schools in the Greater Cincinnati area and undergraduate students in a 1-day workshop to educate and engage in demonstration and testing of the pedestrian crossing use case with the assembled CAVe-In-A-Box tool.

• Record URL:
  https://www.dot.state.oh.us/Divisions/Planning/SPR/Research/reportsandplans/Lists/Final%20Reports%20All/AllItems.aspx?View={7D4D0273-6FC5-48A5-AD17-9CC3A7E83DA0}&FilterField1=State%5fx0020%5fJob%5fx0020%5f%5fx0023%5f&FilterValue1=136689#InplviewHash7d4d0273-6fc5-48a5-ad17-9cc3a7e83da0=

Language

• English

Project

• Status: Active
• Funding: $100000
• Contract Numbers:

  38585

  136689

  118509

• Sponsor Organizations:

  Federal Highway Administration

  Office of Planning, Environment and Realty (HEP)
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Managing Organizations:

  Ohio Department of Transportation

  Research Program
  1980 West Broad Street
  Columbus, OH  United States  43223
• Project Managers:

  Fout, Vicky

• Performing Organizations:

  University of Cincinnati

  Civil Engineering Department, P.O. Box 210071, 741 Baldwin Hall
  Cincinnati, OH  United States  45221-0071
• Principal Investigators:

  Helmicki, Arthur

• Start Date: 20230201
• Expected Completion Date: 20240801
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Artificial intelligence; Autonomous vehicles; Connected vehicles; Detection and identification system applications; Image processing; Intelligent transportation systems; Pedestrian movement; Software; State departments of transportation; Traffic surveillance
• Geographic Terms: Ohio
• Subject Areas: Data and Information Technology; Education and Training; Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01875093
• Record Type: Research project
• Source Agency: Ohio Department of Transportation
• Contract Numbers: 38585, 136689, 118509
• Files: RIP, STATEDOT
• Created Date: Feb 28 2023 10:58AM