Ramp Metering for Minimization of Traffic Emissions

Presenter: Joseph McGuire

Co-Presenter(s):
Jorge Ruiz Gonzalez

Presenter Status: Undergraduate student

Academic Year: 19-20

Semester: Spring

Faculty Mentor: Martha Shott

Department: Mathematics

Funding Source/Sponsor: LSAMP

Screenshot URL: https://drive.google.com/uc?id=1qP2st1s4fskv2WlzSK2UbiJJvcM6nbmt

Abstract:
Stop-and-go traffic is a common phenomenon experienced by freeway drivers. When upstream demand and downstream supply are vastly different, which is often the case at bottlenecks such as lane drops or on-ramp merges, these oscillations in traffic flow and density are likely to occur. Traffic congestion leads to longer commutes, which in turn are associated with an increase in harmful emissions and overall fuel consumption by vehicles. Our research investigates the impact of various traffic patterns on emissions produced and fuel consumed. We integrate an emissions model along with a macroscopic traffic model to understand the connection between congestion type and environmental impact. Our results indicate that persistent stop-and-go traffic leads to greater fuel consumption and emissions in a simple freeway system. We discuss how these results may be used to optimize ramp metering algorithms to reduce emissions and fuel consumption.