Controls and Control Theory Commons^™

Development Of Autonomous Vehicle Motion Planning And Control Algorithm With D* Planner And Model Predictive Control In A Dynamic Environment, Somnath Mondal

Dissertations, Master's Theses and Master's Reports

The research in this report incorporates the improvement in the autonomous driving capability of self-driving cars in a dynamic environment. Global and local path planning are implemented using the D* path planning algorithm with a combined Cubic B-Spline trajectory generator, which generates an optimal obstacle free trajectory for the vehicle to follow and avoid collision. Model Predictive Control (MPC) is used for the longitudinal and the lateral control of the vehicle. The presented motion planning and control algorithm is tested using Model-In-the-Loop (MIL) method with the help of MATLAB® Driving Scenario Designer and Unreal Engine® Simulator by Epic Games®. Different …

Development Of An Eco Approach And Departure Application To Improve Energy Consumption Of A Plug-In Hybrid Vehicle In Charge Depleting Mode, Brandon Narodzonek

Dissertations, Master's Theses and Master's Reports

A recent study at Michigan Technological University as part of the NEXTCAR DOE APRA-E Project was conducted to determine the potential energy savings of a plug-in hybrid electric vehicle (PHEV) equipped with various Connected and Automated Vehicle (CAV) Technologies. One aspect of this study focused on the development of an Eco Approach and Departure (Eco AnD) Application that would further reduce the energy consumed around a signalized intersection.

Many modern intersections are equipped with traffic signals that can broadcast Basic Safety (BSM), MAP, and Signal Phase and Timing (SPaT) message sets that contain intersection ID, location, current phase, and cyclic …

Sensor Fusion And Non-Linear Mpc Controller Development Studies For Intelligent Autonomous Vehicular Systems, Ahammad Basha Dudekula

Dissertations, Master's Theses and Master's Reports

The demand for safety and fuel efficiency on ground vehicles and advancement in embedded systems created the opportunity to develop Autonomous controller. The present thesis work is three fold and it encompasses all elements that are required to prototype the autonomous intelligent system including simulation, state handling and real time implementation. The Autonomous vehicle operation is mainly dependent upon accurate state estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, …

Effect Of Sensor Errors On Autonomous Steering Control And Application Of Sensor Fusion For Robust Navigation, Shuvodeep Bhattacharjya

Dissertations, Master's Theses and Master's Reports

Autonomous steering control is one the most important features in autonomous vehicle navigation. The nature and tuning of the controller decides how well the vehicle follows a defined trajectory. A poorly tuned controller can cause the vehicle to oversteer or understeer at turns leading to deviation from a defined path. However, controller performance also depends on the state–feedback system. If the states used for controller input are noisy or has bias / systematic error, the navigation performance of the vehicle is affected irrespective of the control law and controller tuning. In this report, autonomous steering controller analysis is done for …