Hydrogen fuel cell technology has emerged as an efficient and clean alternative to internal combustion engines for powering vehicles, and hydrogen powertrains will aid in addressing key environmental issues such as urban air quality and global warming. This work demonstrates the effectiveness of a „hardware-in-loop‟ (HIL) simulation system for validating the safety and effectiveness of control algorithms for a hydrogen fuel cell hybrid passenger vehicle. A significant amount of the work completed in conjunction with the thesis topic was the design and construction of the fuel cell vehicle for competition. Producing a „rolling test bench‟ that generates data to be used to create HIL simulation models required nearly two years of work before an acceptable level of reliability was reached to produce usable data. Some detail will be given in this thesis regarding the infrastructure modifications required to safely build a hydrogen fuel cell vehicle, as well as the design challenges faced in the integration of a fuel cell power module, two electric drive motors, a nickel metal hydride battery, and required power electronics into a small sport utility vehicle originally designed for an internal combustion powertrain. The virtual control validation performed involved designing dynamic models of the systems of interest and performing real-time simulation to ensure that the appropriate controller response is observed. For this thesis, emphasis was placed on several key vehicle control topics. Communication robustness was evaluated to ensure that the complicated vehicle communication network could effectively handle traffic from the six powertrain sub-controllers. Safety algorithms were tested for appropriate response to fault conditions. Control systems were developed and tuned offline reducing the amount of time required for in-vehicle development and testing. Software-in-the-loop simulation was used to check initial code integrity and to validate the hardware-in-the-loop vehicle models. The methodology presented in this work was found to be sufficient for a thorough safety and rationality evaluation of control strategies for hybrid fuel cell vehicles.

Στόχος της εργασίας είναι η μοντελοποίηση και ο έλεγχος με τη χρήση υπολογιστή του συστήματος της πέδησης του αυτοκινήτου καθώς και της επιτάχυνσης (γκάζι - throttle) του κινητήρα. Για την πέδηση μελετήθηκε και υλοποιήθηκε στο Simulink το μοντέλο που περιγράφεται στην εργασία των Humair Raza, Zhigang Xu, Bingen Yang και Petros A. Ioannou με τον τίτλο “Modeling and Control Design for a Computer-Controlled Brake System”. Για την πέδηση και την επιτάχυνση, ενοποιημένα σε ένα ενιαίο μοντέλο που περιγράφει το όχημα, μελετήθηκε η εργασία των P. Ioannou και Z. Xu με τίτλο “Throttle and Brake Control Systems for Automatic Vehicle Following”, και στη συνέχεια υλοποιήθηκαν στο Simulink τα μοντέλα για την πέδηση και το throttle. Στην συνέχεια δοκιμάσαμε τους ελεγκτές εφαρμόζοντας διάφορες εισόδους (σενάρια φρεναρίσματος) και λάβαμε τις αναμενόμενες από τη θεωρία εξόδους, επαληθεύοντας έτσι την ορθότητά τους. / The aim of this study is to model and control with the computer the car brake system and the engine throttle. For the brake system we studied and implemented in the Simulink the model described in the work of Humair Raza, Zhigang Xu, Bingen Yang and Petros A. Ioannou titled "Modeling and Control Design for a Computer-Controlled Brake System ". For the braking and the acceleration, consolidated into a single model describing the vehicle, we studied the work of P. Ioannou, Z. Xu entitled "Throttle and Brake Control Systems for Automatic Vehicle Following ", and then we implemented the models in Simulink. Then we tried applying different controllers inputs (braking and acceleration scenarios) and we verified the models' correctness.

With the growing complexity of vehicle control systems it is becoming increasingly important to understand the interaction between drivers and vehicles. Existing driver models do not adequately characterise limitations resulting from drivers’ physical systems. In particular, sensory dynamics limit the ability of drivers to perceive the states of real or simulated vehicles. Therefore, the aim of this thesis is to understand the impact of sensory dynamics on the control performance of a human driver in real and virtual environments. A new model of driver steering control is developed based on optimal control and state estimation theory, incorporating models of sensory dynamics, delays and noise. Some results are taken from published literature, however recent studies have shown that sensory delays and noise amplitudes may increase during an active control task such as driving. Therefore, a parameter identification procedure is used to fit the model predictions to measured steering responses of real drivers in a simulator. The model is found to fit measured results well under a variety of conditions. An initial experiment is designed with the physical motion of the simulator matching the motion of the virtual vehicle at full scale. However, during more realistic manoeuvres the physical motion must be scaled or filtered, introducing conflicts between measurements from different sensory systems. Drivers are found to adapt to simple conflicts such as scaled motion, but they have difficulty adapting to more complicated motion filters. The driver model is initially derived for linear vehicles with stochastic target and disturbance signals. In later chapters it is extended to account for transient targets and disturbances and vehicles with nonlinear tyres, and validated once again with experimental results. A series of simulations is used to demonstrate novel insights into how drivers use sensory information, and the resulting impact on control performance. The new model is also shown to predict difficulties real drivers have controlling unstable vehicles more reliably than existing driver models.

<p>This thesis describes the development of a low-cost, low-power, accurate sensor designed for precise, feedback control of an autonomous vehicle to a hitch. Few studies have been completed on the hitching problem, yet it is an important challenge to be solved for vehicles in the agricultural and transportation industries. Existing sensor solutions are high cost, high power, and require modification to the hitch in order to work. Other potential sensor solutions such as LiDAR and Digital Fringe Projection suffer from these same fundamental problems. </p> <p>The solution that has been developed uses an active stereo vision system, combining classical stereo vision with a laser speckle projection system, which solves the correspondence problem experienced by classic stereo vision sensors. A third camera is added to the sensor for texture mapping. As a whole, the system cost is $188, with a power usage of 2.3 W.</p> <p>To test the system, a model test of the hitching problem was developed using an RC car and a target to represent a hitch. In the application, both the stereo system and the texture camera are used for measurement of the hitch, and a control system is implemented to precisely control the vehicle to the hitch. The system can successfully control the vehicle from within 35⁰ of perpendicular to the hitch, to a final position with an overall standard deviation of 3.0 mm of lateral error and 1.5⁰ of angular error. Ultimately, this is believed to be the first low power, low cost hitching system that does not require modification of the hitch in order to sense it. </p>

Autonomous vehicle technology has seen remarkable advancements in recent years, yet significant challenges remain in ensuring robust, adaptive, and efficient control algorithms for diverse operational scenarios. This dissertation aims to address these challenges by developing and validating a generic control framework that is applicable to both independent autonomous vehicles and connected vehicle systems such as automated platoons. The versatility of the proposed framework ensures its applicability to a wide range of vehicles, including automobiles, light trucks, and rigid and articulated commercial trucks, under high-speed and complex driving conditions. The first major contribution is the development of a longitudinal control algorithm based on a nested PID structure. Designed for computational efficiency and stability, the algorithm simultaneously regulates vehicle speed and inter-vehicle distance. Its adaptability is extended to curved trajectories using an arc length-based error calculation, making it suitable for real-world scenarios. A rigorous simulation study is undertaken to demonstrate the algorithm's stability and robustness to parametric uncertainties. The second major contribution is the development of a high-speed lateral control algorithm based on a modified clothoid controller. This lateral control framework is designed to minimize lateral acceleration (improving passenger comfort and safety) and reduce cross-track errors (CTEs) across various vehicle configurations, including articulated trucks. Simulation results confirmed the superiority of the clothoid-based controller in minimizing CTEs and maintaining smooth steering profiles, even for complex vehicle configurations. Notably, tracking the steer axle center was found to significantly improve performance across all trajectory segments. The final contribution integrates the longitudinal and lateral control frameworks, enabling seamless operation in automated platooning scenarios. This integration requires adapting the longitudinal controller to curved trajectories using arc length-based calculations. Comprehensive simulations, including challenging trajectories such as dual lane changes, and actual roadways like sections of the Blue Ridge Parkway in Virginia and South Grade Road in California, validated the integrated framework. Despite minor anomalies in high-stress conditions, the results demonstrate acceptable performance in terms of spacing errors, relative velocities, lateral accelerations, and CTEs, highlighting the robustness and resilience of the proposed system. The study presents a unified control framework that bridges the gap between independent autonomous vehicles and connected vehicle systems. The generic nature of the algorithms ensures their applicability to a wide variety of vehicles and scenarios, making them a strong candidate for future deployment in autonomous systems. The findings represent significant advances toward safer, more efficient, and versatile autonomous vehicle technologies, addressing critical challenges in the path to commercial implementation / Doctor of Philosophy / Autonomous vehicles are transforming the way we think about transportation, but challenges remain in making these systems adaptable, efficient, and safe across different driving conditions. This research focuses on creating a versatile control system that works for both individual autonomous vehicles, like self-driving cars, and connected systems, such as a platoon (group) of automated trucks traveling together, in a synchronized manner. The framework is designed to handle a wide range of vehicles, including both cars, light trucks, and large trucks with trailers, even in high-speed and complex scenarios. The first contribution is a computationally efficient and robust longitudinal control algorithm to control vehicle speed and spacing between vehicles. It efficiently regulates the vehicle speed and inter-vehicle distance and is extended to handle the trajectory that the vehicle takes on curved roadways, using arc length-based error calculations. The simulation results show that this approach is both reliable and robust, even when faced with uncertainties like changing vehicle loads or road conditions. The second contribution is a high-speed lateral control algorithm using a modified clothoid controller. This controller minimizes lateral acceleration for improved safety and comfort while reducing cross-track errors (CTEs) for both rigid-body and articulated vehicles. It is discovered that tracking the steer axle center, as opposed to other points of reference on the vehicle, significantly enhances performance across all trajectory types. Finally, the longitudinal and lateral controllers are integrated for automated platooning, with adaptations for curved trajectories. This integrated system is tested on challenging road layouts, including sharp turns and steep inclines, showing it can maintain safe distances and smooth paths even under difficult conditions. The roadways selected for evaluating the control scheme include a section of the Blue Ridge Parkway in Virginia and a section of the South Grade Road in California. In summary, this research provides a flexible and efficient control system that bridges the gap between self-driving cars and larger connected vehicle systems. By making it adaptable to various vehicles and scenarios, it lays the foundation for safer and more reliable autonomous vehicle technology in the future

With the introduction of electronic control units to automotive vehicles, system complexity has increased. With this change in complexity, new standards have been created to ensure safety at the system level for these vehicles. Furthermore, vehicles have become increasingly complex with the push for electrification of automotive vehicles, which has resulted in the creation of hybrid electric and battery electric vehicles. The goal of this thesis is to provide an example of a hazard and operability analysis as well as a hazard and risk analysis for a hybrid electric vehicle. Additionally, the safety standards developed do not align well with educational prototype vehicles because the standards are designed for corporations. The hybrid vehicle supervisory controller example within this thesis demonstrates how to define a system and then perform system-level analytical techniques to identify potential failures and associated requirements. Ultimately, through this analysis suggestions are made on how best to reduce system complexity and improve system safety of a student built prototype vehicle. / Master of Science / With the introduction of electronic control units to automotive vehicles, system complexity has increased. With this change in complexity, new standards have been created to ensure safety at the system level for these vehicles. Furthermore, vehicles have become increasingly complex with the push for electrification of automotive vehicles, which has resulted in the creation of hybrid electric and battery electric vehicles. There are different ways for corporations to demonstrate adherence to these standards, however it is more difficult for student design projects to follow the same standards. Through the application of hazard and operability analysis and hazard and risk analysis on the hybrid vehicle supervisory controller, an example is provided for future students to follow the guidelines established by the safety standards. The end result is to develop system requirements to improve the safety of the prototype vehicle with the added benefit of making design changes to reduce the complexity of the student project.