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City Traffic as a Reservoir System (In Progress)

Description

Funded in Spring 2020, this project will introduce and test a method of inferring traffic accumulation (number of vehicles circulating in an area) from the measured flow of traffic in, out, and around major parking facilities.

Researchers will combine traffic theory, traffic detection, data science, and statistics to reduce the amount of time cars spend idling — and thus transportation-related emissions. The team will use uncertainty quantification methods in its modeling to help more accurately count vehicles in one of three “reservoirs”: outside the zone, parked, and circulating on streets near the parking facility.

Background

Purpose of the Work: Campus Connection

Using iSEE seed funding, the team is working with Facilities & Services (F&S) to select a major parking facility zone on the U of I campus, place traffic detectors (cameras) along its periphery and at its entrances and exits, and feed the data into computer vision algorithms to measure traffic accumulation (number of vehicles circulating) and flow. This accumulation and flow data can be used for transportation planning and interventions to traffic signals that reduce time idling, thus reducing greenhouse gas (GHG) emissions related to driving.

The team expects to attract external funding through the National Science Foundation Cyber Physical Systems (CPS) program.

Project Team

  • Project Leader:

    Lewis Lehe, Assistant Professor, Civil and Environmental Engineering

    Team Members:

    • Co-PL: Alireza Talebpour, Assistant Professor, Civil and Environmental Engineering
    • Co-PL: Hadi Meidani, Assistant Professor, Civil and Environmental Engineering

Themes