Location: Olsson Hall, Link Lab Room 217 & Zoom
Add to Calendar 2023-12-06T10:00:00 2023-12-06T12:00:00 America/New_York PhD Proposal: Zeyu Mu All Invited Committee Members: Nicola Bezzo (Chairperson) – SIE/ECE Brian Park (Advisor) – CEE/SIE T. Donna Chen –  CEE Shangtong Zhang – CS Sergei Avedisov – Principal Researcher, Toyota InfoTech Labs Note: Please email SIE STUDENT SERVICES for zoom information. Title: Maximizing Benefits of Platooning for Connected Automated Vehicles in Mixed Traffic Olsson Hall, Link Lab Room 217 & Zoom

All Invited

Committee Members:

  • Nicola Bezzo (Chairperson) – SIE/ECE
  • Brian Park (Advisor) – CEE/SIE
  • T. Donna Chen –  CEE
  • Shangtong Zhang – CS
  • Sergei Avedisov – Principal Researcher, Toyota InfoTech Labs

Note: Please email SIE STUDENT SERVICES for zoom information.

Title: Maximizing Benefits of Platooning for Connected Automated Vehicles in Mixed Traffic

Abstract:
Platooning, a key technique for advancing connected automated vehicles (CAVs), is integral to enhancing safety, energy efficiency, and traffic capacity. Leveraging cooperative adaptive cruise control (CACC) through vehicle-to-vehicle (V2V) communication, platooning builds upon adaptive cruise control (ACC). However, as the near future traffic landscape will include a mix of traditional human-driven vehicles (THVs) and a low market penetration rate (MPR) of CAVs, platooning faces challenges. Specifically, a portion of CAVs may follow an unconnected preceding vehicle and cannot utilize platooning. Therefore, this research aims to maximize platooning benefits, including decision-making, planning, and control (i.e., ACC, CACC, and cooperative adaptive cruise control with unconnected vehicles, CACCu), in diverse scenarios under mixed traffic. The proposal addresses three pivotal dimensions. Firstly, the optimization of platooning strategies must accommodate the distinctive traffic characteristics of both urban arterial and highway scenarios. In urban arterials, where congestion is primarily caused by stop-and-go traffic at intersections, investigating platooning becomes imperative for enhancing vehicle safety and overall traffic efficiency. Conversely, on highways, CAVs are more prone to prolonged platooning. However, the initial sparse distribution of CAVs poses challenges to effective platooning utilization, making the organization of CAV platoons a critical challenge in improving vehicle safety and traffic capacity. Secondly, maximizing CAV capabilities in platooning necessitates identifying the correct connected preceding vehicle through V2V communication to ensure platooning effectiveness. Lastly, the research evaluates the reliability of human driver models for platoon assessment in mixed traffic.