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.Master of Science (Computer Control and Automation
