Controller design and simulation for heavy duty vehicle platooning

Driving Heavy Duty Vehicles (HDVs) as a platoon has potential to significantly reduce the fuel consumption and human labor, meanwhile increasing the safety. A suitable controller which can maintain the platoon moving in a certain topology plays a pivotal role in HDV platooning. In this dissertati...

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Bibliographic Details
Main Author: Zhang, Rongkai
Other Authors: Justin Dauwels
Format: Theses and Dissertations
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/76039
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Institution: Nanyang Technological University
Language: English
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Summary:Driving Heavy Duty Vehicles (HDVs) as a platoon has potential to significantly reduce the fuel consumption and human labor, meanwhile increasing the safety. A suitable controller which can maintain the platoon moving in a certain topology plays a pivotal role in HDV platooning. In this dissertation, first a conventional PID controller for a longitudinal HDV platoon is designed and tuned for controlling the heavy duty vehicles moving in a constant distance topology or a constant distance & headway time topology. Further, an attempt is performed to design a controller using Model Predictive Control(MPC) which has the same control objectives as the PID controller for two scenarios, namely unconstrained and constrained optimization problem. Comparative simulation studies were carried out to test the performance of both the controllers with the help of MATLAB and VISSIM 8. A U.S. freeway I5 is built in VISSIM 8 and a 14-vehicle platoon is generated on this road network. VISSIM 8 gives the information of each vehicle to MATLAB, and using all the information, MATLAB calculates the desired acceleration and feeds it back to VISSIM 8 using these two control methods. Based on the simulation results, a comparison between the PID controller and MPC controller is given. The PID controller need less computational time but cannot handle with constrains. The MPC controller needs more time to solve the optimization problem, but a systematic handling of constraints yields significant improvements in the performance of the proposed MPC over PID controller. Moreover, the proposed MPC can have a good performance without too much tuning, which is better than the PID controller. Hence, according to the above mentioned advantages and disadvantages a Shiftable hybrid-controller is generalized in the end.