Automotive Engineering Commons^™

Integrated Energy-Aware Motion Planning And Charge Scheduling Of Unmanned Aerial Vehicles, Hayleyesus Alemayehu

All Theses

The growing demand for unmanned aerial vehicles (UAVs) is driven by their operational convenience, cost-effectiveness, availability, and adaptability to various scenarios. In energy-constrained environments, optimizing energy consumption and ensuring a continuous power supply for UAVs is crucial for mission success. The objective of this thesis is to address this issue by integrating energy-aware motion planning and charge scheduling for UAVs by utilizing a charger hosted on an unmanned ground vehicle (UGV), whose rendezvous locations and routes are jointly computed to minimize overall energy consumption.

This thesis proposes a hierarchical trajectory and control framework comprising local and global planners for each …

Energy-Aware Coordination Of Automated Vehicles, Nathan Goulet

All Dissertations

Energy is an inherently limited resource for two reasons: the sources utilized to obtain energy are limited; and the methods used most often to convert energy also generate pollutants that the planet has a limited capacity to absorb or compensate for without adverse effects. Efficiently utilizing energy is, therefore, an important topic. As around 16% of the energy consumed in the United States is by light vehicles, a significant impact can be made if vehicle energy consumption is reduced. The advent of connected and automated vehicles offers unprecedented opportunities to optimize their behavior with respect to energy consumption through trajectory …

Improved Vehicle-Bridge Interaction Modeling And Automation Of Bridge System Identification Techniques, Omar Abuodeh

All Dissertations

The Federal Highway Administration (FHWA) recognizes the necessity for cost-effective and practical system identification (SI) techniques within structural health monitoring (SHM) frameworks for asset management applications. Indirect health monitoring (IHM), a promising SHM approach, utilizes accelerometer-equipped vehicles to measure bridge modal properties (e.g., natural frequencies, damping ratios, mode shapes) through bridge vibration data to assess the bridge's condition. However, engineers and researchers often encounter noise from road roughness, environmental factors, and vehicular components in collected vehicle signals. This noise contaminates the vehicle signal with spurious modes corresponding to stochastic frequencies, impacting damage monitoring assessments. Thus, an efficient and reliable SI …

An Advanced Simulation Architecture For Testing Autonomous And Connected Vehicles Enabled By Virtual Reality, Defu Cui

Electrical & Computer Engineering Theses & Dissertations

With the advancement of intelligent transportation systems, autonomous driving and connected driving are seen as potential solutions to alleviate traffic congestion, enhance traffic safety, and improve efficiency. Extensive testing and validation of autonomous vehicles (AVs) and connected vehicles (CVs) including connected autonomous vehicles are crucial to ensure their safety and reliability. However, testing and validating AVs and CVs on public roads faces challenges such as high costs, inadequate support from transportation infrastructure with communication technologies, and safety concerns, among others. Simulations have become essential tools for testing autonomous driving and connected driving. As mixed traffic involves multiple domains including traffic …

Topological Interpolation Method For Modeling Dynamic Systems, Isamiddin Xakimovich Siddikov, Dilnoza Maxamadjanovna Umurzakova

Chemical Technology, Control and Management

The method of simulation structural-complex continuous-discrete control systems is discussed. For simulation and calculation of dynamic processes in continuous-discrete systems topological interpolation method is proposed, based on application of hybrid methods of space of state variables and interpolation of signals. The essence of the method is that the dynamics of the investigated system, considered at the final interval, is broken down into subintervals, on each of which the processes are described by linear ordinary system differential equations. The computational efficiency of the proposed method was evaluated by comparison with standard methods such as the Runge-Kutta-Merson method. The use of this …

Thermoplastics Foams: An Automotive Perspective, Sai Aditya Pradeep, Srishti Shukla, Nathaniel Brown, Srikanth Pilla

Publications

The automotive industry has witnessed a massive shift in terms of materials used, ranging from being a metallic heavyweight in the 1950s to employing a hybrid sandwich of multiple material systems. This apparent shift can be attributed to achieving improvements in performance, safety and fuel efficiency, along with responding to the various environmental regulations imposed by different governments. The recent advocacy of Corporate Average Fuel Economy (CAFE) standard of 54.5 MPG by 2025 by the US Environmental Protection Agency (EPA) to reduce greenhouse gas (GHG) emissions [1] has spurred the sector at large towards the use of lightweight materials.

On The Measurement Of Nakazima Testing Based Out-Of-Plane Forming Limit Curves Using 2d Digital Image Correlation, Akshat Agha, Fadi Abu-Farha

Publications

The strain compensation method for measuring in-plane forming limit curves (FLCs) using 2D digital image correlation developed previously [A method of measuring in-plane forming limit curves using 2D Digital Image Correlation, SAE Int. J. Mater. Manf., 2023] was modified and extended to more versatile and popular out-of-plane FLCs. The current study introduces a straightforward strain compensation technique for measuring Nakazima testing based out-of-plane FLCs utilizing an affordable single-camera (2D) DIC system. In this study, forming tests are performed on two automotive-grade sheet metal alloys: DP980 steel and a 6xxx series aluminum alloy using the Nakazima test method. The experiments are …

Composites 4.0: Enabling The Modernization Of Legacy Manufacturing Assets In South Carolina, Amit Makarand Deshpande, Gayatri Keskar, Sai Aditya Pradeep, Saeed Farahani, Srikanth Pilla

Publications

Composites 4.0 is the implementation of Industry 4.0 concepts to plastics and composites manufacturing with the goal to overcome the complexities associated with these materials. Due to very complex process-structure-property relationships associated with plastics and composites, a wide range of process parameters need to be tracked and monitored. Furthermore, these parameters are often affected by the tool and machinery, human intervention and variability and should thus, be monitored by integrating intelligence and connectivity in manufacturing systems. Retrofitting legacy manufacturing systems with modern sensing and control systems is emerging as one of the more cost-effective approaches as it circumvents the substantial …

Improving Autonomous Vehicles Operational Performance Using Resilience Engineering, Johan Fanas Rojas

Dissertations

Autonomous vehicles are expected to revolutionize the transportation industry by providing a safer and more efficient means of transportation. However, as autonomous vehicles are deployed on public roads, they are exposed to significant risks, both in terms of safety and system performance. Recent studies have highlighted a range of errors and accidents associated with autonomous vehicles, underscoring the need for a systematic approach to improve their operational resilience. Resilience engineering, a discipline focused on designing and analyzing complex systems to better cope with unexpected events and disruptions, offers a promising framework for addressing these challenges. Despite the potential benefits of …

Enabling Energy Efficiency In Connected And Automated Vehicles Through Predictive Control Techniques, Farhang Motallebiaraghi

Dissertations

The transportation sector is a significant contributor to global energy consumption and emissions, necessitating the development of sustainable transportation systems. In this regard, connected and automated vehicles (CAVs) have emerged as a potential solution to transform the transportation industry. By harnessing advanced mapping and location technologies, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, CAVs offer the promise of improving efficiency, reducing traffic congestion, and enhancing safety and comfort. However, the adoption of CAVs also brings about various challenges, including energy efficiency concerns that need to be addressed to fully realize their potential benefits. This dissertation investigates energy-efficient control techniques for transportation …

Sensor Updates For Bigheaded Carp-Tracking Autonomous Boat, Jordan Kaufmann

Honors College Theses

Bigheaded carp are an invasive species that overpopulate and compete with the native species of Kentucky Lake as well as many other North American aquatic ecosystems. The movement patterns of Bigheaded carp are being studied nationwide by the United States Geological Survey and multiple universities. These studies ultimately seek to control their spread and reduce or reverse the ecosystem destabilization caused by this invasive species. Such studies are currently conducted manually on Kentucky Lake by graduate students affiliated with the Murray State University (MSU) Biology Department and Hancock Biological Station, and these manual studies are an arduous and time-consuming effort. …

Risk Assessments And Modeling Of Driver By Using Risk Potential Theory, Riku Kikuta

Theses and Dissertations

Recently, various self-driving and driving assistance systems such as Advanced Driver Assistance System (ADAS) have been developed with the intent to reduce the number of motor vehicle accidents. While self-driving systems have been proven to reduce traffic accidents, the systems sometimes make other drivers confused because of their mechanical behavior. To avoid confusion and possible error, it is necessary to construct self-driving systems that exhibit human-like behaviors. Risk Potential theory has been used to construct models that successfully represent driver behavior, especially expert behavior. This project uses Risk Potential theory to construct and evaluate a collision avoidance driver model which …

A Modeling Framework To Develop Materials With Improved Noise And Vibration Performance For Electric Vehicles, Javad Baqersad, Seyed Jamaleddin Mostafavi Yazdi, Seongchan Pack, Foroogh Rouhollahi

Mechanical Engineering Publications

The automotive and aerospace industries increasingly use lightweight materials to improve performance while reducing fuel consumption. Lightweight materials are frequently used in electric vehicles (EVs). However, using these materials can increase airborne and structure-borne noise. Furthermore, EV noise occurs at high frequencies, and conventional materials have small damping. Thus, there is an increasing need for procedures that help design new materials and coatings to reduce the transferred and radiated noise at desired frequencies. This study pioneered new techniques for microstructure modeling of coated and uncoated materials with improved noise, vibration, and harshness (NVH) performance. This work uses the microstructure of …

Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks

Faculty Publications

Machine learning and computational processing have advanced such that automated driving systems (ADSs) are no longer a distant reality. Many automobile manufacturers have developed prototypes; however, there exist numerous decision support issues requiring resolution to ensure mass ADS adoption. In the coming decades, it is likely that production ADSs will only be partially autonomous. Such ADSs operate within predetermined conditions and require driver intervention when they are violated. Since forecasts of their 20-year market penetration are relatively low, ADSs will likely operate in heterogeneous traffic characterized by vehicles of varying autonomy levels. Under these conditions, effective decision support must consider …

Accelerating The Derivation Of Optimal Powertrain Control Strategies Using Reinforcement Learning And Virtual Prototypes, Daniel Egan

All Dissertations

The push for improvements in fuel economy while reducing tailpipe emissions has resulted in significant increases in automotive powertrain complexity, subsequently increasing the resources, both time and money, needed to develop them. Powertrain performance is heavily influenced by the quality of their controller/calibration with modern powertrains reaching levels of complexity where using traditional design of experiment-based methodologies to develop them can take years. Recently, reinforcement learning (RL), a machine learning technique, has emerged as a method to rapidly create optimal controllers for systems of unlimited complexity directly which creates an opportunity to use RL to reduce the overall time and …

Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi

All Dissertations

Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …

Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim

All Dissertations

In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …

Improving Quality Of Life Using Ict, Iot And Ai (Honet), Charles Koduru

Symposium of Student Scholars

Autonomous robots can be assigned with various tasks such as moving payload, analyzing terrain, and capturing data in an environment. For an Autonomous Mobile Robot (AMR) to execute such tasks the robot (Hussarion ROSbot) will require efficient algorithms and techniques to reference its current location. The robot is relative to surrounding obstacles in its predetermined path. The conducted research study explains the coordinated method used to successfully allow a robot to identify its position in the environment (Gazebo Simulation) and avoid obstructions with increasing velocity - contingent on nearby surroundings. The results show multiple robots individually tasked with distinct roles, …

Development Of Detection And Tracking Systems For Autonomous Vehicles Using Machine Learning, Tyler Ward

Morehead State Theses and Dissertations

A thesis presented to the faculty of the Elmer R. Smith College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the degree of Master of Science by Tyler Ward April 25, 2023.

Optimization Of A Simultaneous Localization And Mapping (Slam) System For An Autonomous Vehicle Using A 2-Dimensional Light Detection And Ranging Sensor (Lidar) By Sensor Fusion, Shaen Mehrzed

Honors College Theses

Fully autonomous vehicles must accurately estimate the extent of their environment as well as their relative location in their environment. A popular approach to organizing such information is creating a map of a given physical environment and defining a point in this map representing the vehicle’s location. Simultaneous Mapping and Localization (SLAM) is a computing algorithm that takes inputs from a Light Detection and Ranging (LiDAR) sensor to construct a map of the vehicle’s physical environment and determine its respective location in this map based on feature recognition simultaneously. Two fundamental requirements allow an accurate SLAM method: one being accurate …