CAV Systems Incorporating Air Pollution Information from Traffic Congestion

Through CCAT center, CSU proposes to study air pollutants under different traffic congestion scenarios along selected freeways in Ohio. The study captures pollution intensities in different seasons of the year representing different atmospheric stabilities and concentration of criteria air pollutants and greenhouse gases as a function of hold up times and traffic densities. Our prior work has determined typical hot spots in Ohio along freeways that are prone to high traffic densities and possible congestion. MOVES will be used to generate these scenarios to determine emissions from vehicles in a simulated traffic congestion scenario across interstate intersections. ODOT traffic data will be used for these scenarios. Resulting air pollutants and greenhouse gases from emissions will be determined using a dispersion model. Concentrations of the air pollutants will be compared with NAAQS. A model will be developed to assess severity of air pollution and calibrated using emission measurements from the Engine Exhaust Analyzer. It will be used to forecast air quality index for the congested areas (primarily interstate intersections) on freeways. CAV technology will then be deployed to communicate the information to travelers on freeways on radio channels approaching these congested areas.

Language

• English

Project

• Status: Completed
• Funding: $299,754
• Contract Numbers:

  69A3551747105

• Sponsor Organizations:

  Department of Transportation

  Intelligent Transportation Systems Joint Program Office
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Connected and Automated Transportation

  University of Michigan Transportation Research Institute
  Ann Arbor, MI  United States  48109
• Project Managers:

  Tucker-Thomas, Dawn

• Performing Organizations:

  Central State University

  111 C.J. McLin Center
  1400 Brush Row Road
  Wilberforce, OH  United States  45384-1004
• Principal Investigators:

  Kandiah, Ramanitharan

  Nedunuri, Krishnakumar

  Cao, Deng

• Start Date: 20180611
• Expected Completion Date: 20240229
• Actual Completion Date: 20240319
• USDOT Program: University Transportation Centers Program
• Subprogram: Research

Subject/Index Terms

• TRT Terms: Air pollution; Automated vehicle control; Autonomous vehicles; Connected vehicles; Emissions testing; Freeways; Pollutants; Traffic; Traffic congestion
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Planning and Forecasting; Policy; Research; Safety and Human Factors;

Filing Info

• Accession Number: 01742580
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: Jun 17 2020 4:48PM