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Date of Award
2017
Document Type
Campus Access Master's Thesis
Degree Name
Master of Science in Mechanical Engineering (MS)
Administrative Home Department
Department of Mechanical Engineering-Engineering Mechanics
Advisor 1
Bo Chen
Committee Member 1
Mahdi Shahbakhti
Committee Member 2
Darrell L. Robinette
Abstract
Connected and Automated Vehicles (CAVs) coupled with Intelligent Transportation Systems (ITS) have been able to impact significantly to the transportation and automotive sector by improving traffic mobility, increasing fuel efficiency and reducing emissions. The research intends to develop optimization algorithms by utilizing the velocity bounds provided by a traffic simulation program and generate an optimal velocity trajectory to reduce power-losses and improve drivability in vehicles.
The developed optimal velocity trajectory algorithms are modified for the applications of Eco –Approach and Departure (Eco A/D) at signalized intersections and Co-operative Adaptive Cruise Control (CACC). The fuel consumption during Eco-A/D is minimized by reducing idling times at traffic intersections. The CACC algorithm allows vehicles in a platoon to maintain a closer inter-vehicular gap and improve the efficiency of the platoon.
Lastly, the simulation results generated by test cases are presented and future work is discussed to translate the simulation-based results to real-world improvement.
Recommended Citation
Barik, Biswajit, "Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles", Campus Access Master's Thesis, Michigan Technological University, 2017.