Optimized and energy-efficient cooperative platooning for autonomous vehicles

The increasing need for energy in most systems has resulted in the need for efficient energy usage, particularly in vehicle-based systems. This thesis investigates energy-efficient platooning of Connected and Autonomous Vehicles(CAVs) in simulation frameworks using energy modelling. A lightweight physics-based energy model was integrated into a framework to capture kinematics data, such as aerodynamic drag and inertial dynamics in real time. This thesis focuses on evaluating multiple control strategies for energy efficiency under controlled scenarios. Three controllers were evaluated: Adaptive Cruise Control (ACC), Cooperative Adaptive Cruise Control(CACC), and proposed energy-aware controller. The energy-aware controller provided greater energy savings than the other two controllers with savings over 20% along with strongest string stability. This thesis provides insights into energy benefits that can be gained through energy-aware controllers working with information sharing in autonomous platooning, allowing for deeper insights relevant to Canadian transportation decarbonization.

Name thesis:degree_name

Master of Applied Science (MASc)

Discipline thesis:degree_discipline

Software Engineering

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Khalid, Muhammad Zaeem

Advisor dc:contributor.advisor

• Azim, Akramul

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/2053

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/2053