Research Projects

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Research Projects

METRANS
STATUS: In Progress YEAR: 2020 TOPIC AREA: Sustainability, energy, and health Transportation planning, policy, and finance CENTER: PSR

Using artificial intelligence to improve traffic flows, with consideration of data privacy principles

Project Summary

Funding source: U.S. Department of Transportation
Contract number: 69A3551747109
Funding amount: $100,000
Start and end dates: 08/16/20 to 08/15/21

Project description

In areas adjacent to major ports, traffic is impacted by the presence of heavy trucks transporting goods between marine terminals and warehouses. As compared to passenger vehicles, trucks have much lower acceleration rates, take a longer time to stop, require a longer stopping distance, and have bigger turning ratios. For these reasons, the presence of trucks creates delays at city intersections, which affect both passenger cars and trucks. The delays propagate throughout the traffic network, and have a negative impact on the environment because of the high pollution rates due to idle or slow-moving vehicles. A previous METRANS project (Ioannou, 2015) showed via simulations that using intelligent control techniques to control the traffic lights at city intersections can result in reduction of traffic delays in the range of 20%-40% as compared to the fixed-time actuated signal controllers currently in use.

In this project, we propose to collaborate with the City of Long Beach to collect data from selected city intersections, and use the actual data to develop a traffic light controller similar to the one presented in the previous METRANS project (Ioannou, 2015) and evaluate the controller's effectiveness to reduce traffic delays. A future long-term goal is to physically implement a smart traffic light control system to a selected intersection, and subsequently expand the implementation to a local network of intersections in the vicinity of the ports.

Since the intelligent traffic signal control methods involve technologies that collect, store and analyze data associated with vehicles passing through busy intersections, there is a need to incorporate data protections into the project design, and to ensure personally identifiable information does not violate digital rights and personal privacy. Carefully designed surveys and questionnaire responses from the city's residents will be used to identify and address privacy concerns and recommendations for implementation of the intelligent control techniques.

P.I. NAME & ADDRESS

Gwen Shaffer
Associate Professor
1250 Bellflower Boulevard
Long Beach, CA 90840
United States
[email protected]

CO-P.I.

Anastasios Chassiakos
Professor, Computer Engineering Computer Science Department; College of Engineering
1250 Bellflower Blvd.
ET-116Long Beach, CA 90840
United States
[email protected]