Navigation, Guidance, Control, and Dynamics Commons^™

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

Deployment Considerations For Autonomous And Integrated Mobility Services Of The Future, Panagiotis Georgakis

CONTROL 2022: 13th United Kingdom Automatic Control Council (UKACC) International Conference

No abstract provided.

Programming An Autonomous Vehicle Ethical Decision Maker Based On Injury Severity, James E. Pickering

CONTROL 2022: 13th United Kingdom Automatic Control Council (UKACC) International Conference

No abstract provided.

Issues Building An Autonomous Vehicle, Paul King

CONTROL 2022: 13th United Kingdom Automatic Control Council (UKACC) International Conference

No abstract provided.

Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy

Theses and Dissertations

The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility …

Control, Decision-Making, And Learning Approaches For Connected And Autonomous Driving Systems With Humans-In-The-Loop, Fangjian Li

All Dissertations

By virtue of vehicular connectivity and automation, the vehicle becomes increasingly intelligent and self-driving capable. However, no matter what automation level the vehicle can achieve, humans will still be in the loop despite their roles. First, considering the manual driving car as a disturbance to the connected and autonomous vehicles (CAVs), a novel string stability is proposed for mixed traffic platoons consisting of both autonomous and manual driving cars to guarantee acceptable motion fluctuation and platoon safety. Furthermore, humans are naturally considered as the rider in the passenger vehicle. A human-centered cooperative adaptive cruise control (CACC) is designed to improve …

Distributed Control And Learning Of Connected And Autonomous Vehicles Approaching And Departing Signalized Intersections, Joshua Onyeka Ogbebor

LSU Master's Theses

This thesis outlines methods for achieving energy-optimal control policies for autonomous vehicles approaching and departing a signalized traffic intersection. Connected and autonomous vehicle technology has gained wide interest from both research institutions and government agencies because it offers immense promise in advancing efficient energy usage and abating hazards that beset the current transportation system. Energy minimization is itself crucial in reducing the greenhouse emissions from fossil-fuel-powered vehicles and extending the battery life of electric vehicles which are presently the major alternative to fossil-fuel-powered vehicles. Two major forms of fuel minimization are studied. First, the eco-driving problem is solved for a …

Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

The Global Positioning System (GPS) has become a foundation for most location-based services and navigation systems, such as autonomous vehicles, drones, ships, and wearable devices. However, it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools. Pervasive tools, such as Fake GPS, Lockito, and software-defined radio, enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected. Furthermore, it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors. To this …

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

Improved Ships Course-Keeping Robust Control Algorithm Based On Backstepping And Nonlinear Feedback, Sirui Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Problem Solving Methods For Synthesis Of Physical Principles Of Mechatronic Module Operations In Intelligent Robotic Systems, Nazarov Khayriddin Nuritdinovich

Chemical Technology, Control and Management

The scientific paper investigates the methods for solving problems of synthesis of physical principles of operation of mechatronic modules of intelligent robotic systems are considered.

In addition, it deals with the specifics of the process of synthesis of the physical principles of the operation of mechatronic modules using predicate models, list models and information matrices of physical and technical effects.

It shows the interpretation of the components of the model of the system for the synthesis of the physical principles of operation of mechatronic modules of intelligent robotic systems and automatic control and the features of the synthesis algorithm for …

Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu

Theses and Dissertations

Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly …

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 …

Implementation Of Fuzzy Logic Control Into An Equivalent Minimization Strategy For Adaptive Energy Management Of A Parallel Hybrid Electric Vehicle, Jared Alexander Diethorn

Graduate Theses, Dissertations, and Problem Reports (ETD)

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Electric vehicles have been introduced by the industry, showing promising signs of reducing emissions production in the automotive sector. However, many consumers may be hesitant to purchase fully electric vehicles due to several uncertainty variables including available charging stations. Hybrid electric vehicles (HEVs) have been introduced to reduce problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in …

Resilience For Multi-Filter All-Source Navigation Framework With Integrity, Jonathon S. Gipson, Robert C. Leishman

Faculty Publications

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters, (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.) do not intrinsically meet this requirement.
This paper presents a novel method to monitor real-time overlapping position state observability and introduces an "observability bank" within the ARMAS framework, known as Stable Observability Monitoring (SOM). SOM …

Control Of Mr Damper Using Anfis And Pid Controller For Optimum Vehicle Ride Comfort, Mohammad Faisal Yakhni, Mohamad Ali, Mohamed El-Gohary

BAU Journal - Science and Technology

Suspension system design is an important challenging duty that facing car manufacturers, so the challenge has become to design the best system in terms of providing ride comfort and handling ability under all driving situations. The goal of this paper is to provide assistance in enhancing the effectiveness of the suspension system. A full car model with eight Degrees Of Freedom (DOF) was developed using MATLAB/Simulink. Validation of the Simulink model was obtained. The model was assumed to travel over a speed hump that has a half sine wave shape and amplitude that changing from 0.01 to 0.2 m. The …

Performance Testing Of Aero-Naut Camfolding Propellers, Or D. Dantsker, Robert W. Deters, Marco Caccamo, Michael S. Selig

Publications

The increase in popularity of unmanned aerial vehicles (UAVs) has been driven by their use in civilian, education, government, and military applications. However, limited on-board energy storage significantly limits flight time and ultimately usability. The propulsion system plays a critical part in the overall energy consumption of the UAV; therefore, it is necessary to determine the most optimal combination of possible propulsion system components for a given mission profile, i.e. propellers, motors, and electronic speed controllers (ESC). Hundreds of options are available for the different components with little performance specifications available for most of them. By examining a variety of …

Optimized System For On-Route Charging Of Battery Electric Buses And High-Fidelity Modelling And Simulation Of In-Motion Wireless Power Transfer, Yogesh Bappasaheb Jagdale

Masters Theses

Electrifying cars, buses and trucks is an attractive means to reduce energy use and emissions, because it involves minimal restructuring of the transportation network. Transit buses drive fixed routes, minimizing driver range anxiety by properly sizing energy storage system but the major challenge to fully electrifying transit buses, is the amount of energy they consume in a day of driving. To enable a full day of operation, batteries need to be large, which is expensive and heavy. This work utilizes real-world transit bus data fed to a battery electric drive-train model to co-optimize charger locations, charger power levels, and vehicle …

Conducted And Radiated Emi Measurements Of Parallel Buck Converters Under Varying Spread Spectrum Parameters, Elena Postupalskaya, Nathan Wang

Electrical Engineering

The Conducted and Radiated EMI Measurements with Parallel Buck Converters Under Varying Spread Spectrum Parameters research senior project aims to explore the effects from Spread Spectrum Frequency Modulation (SSFM) on the input electromagnetic interference (EMI) or noise of a switching power supply, specifically with LM53601MAEVM hardware. The input EMI is important as the main input bus needs to be clean to provide a reliable source for other sensitive devices connected to it. SSFM can replace a conventional EMI filter and save weight, space, and cost. This project provides a basis in terms of the impacts of variable SSFM in simulation …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

Control And Locomotion Of Inertially And Magnetically Actuated Multi-Scale Robotic Systems, Ehab Al Khatib

Mechanical Engineering Research Theses and Dissertations

In this research, two actuation systems were introduced, inertial and magnetic actuation. In the inertial actuation, the robot used the transfer of momentum to navigate, and this momentum could be generated by spinning masses and wheels. Recent studies in our System Laboratory proved that a wide range of inertially actuated locomotion systems could be generated. This can be achieved by using a family tree approach, starting from a very simple system, and progressively evolving it to more complex ones. The motion diversity of these robots inspired us to extend their locomotion from a macro scale to millimeter and micro scales. …

Vehicle Velocity Prediction Using Artificial Neural Networks And Effect Of Real-World Signals On Prediction Window, Tushar Dnyaneshwar Gaikwad

Masters Theses

Prediction of vehicle velocity is essential since it can realize improvements in the fuel economy/energy efficiency, drivability, and safety. Many publications address velocity prediction problems, yet there is a need for the understanding effect of different signals for the prediction. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain comprehensive datasets. Several references considered deterministic and stochastic approaches that use the datasets as input to determine future operation predictions. These approaches include different traffic models and artificial neural networks such as Markov chain, nonlinear autoregressive model, Gaussian function, and recurrent …

Dashboard-Mounted Driver Monitoring System, Daniel Lein, Prahlad Sarma, William Roussell, Nathan Nuñez, Elvis Manzanares

ENGS 89/90 Reports

The objective of this project is to deliver safe DMS hardware and interfacing/preprocessing software on which Toyota can run its drowsiness detection neural net. The system shall: securely house all necessary imaging, electronic, and computer hardware to output facial recognition data to the car’s computer, without data input from any other car system; obscure less than 10% of the driver’s field of view out of a standard windshield; be able to capture and process images such that the image classification neural net recognize the images, meeting the top-1 benchmark accuracy statistic across static and dynamic car-cabin lighting conditions; and meet …

Techniques To Solve Decision-Making Problems, Dilnoz Tulkunovna Muhamediyeva, Bekmuratov Fayzievich Tulkun

Chemical Technology, Control and Management

Solving decision-making problems in poorly formalized systems only with the help of deterministic and probabilistic methods is insufficient. To do this, it is necessary to widely apply the methods of hybrid intelligent systems and, especially, the methods of “soft” calculations (SoftCalculation, SoftComputing) and the directions of ComputationalIntelligence — intelligent computing technologies that are emerging on this theoretical and methodological base. An immune - fuzzy algorithm for the synthesis of fuzzy inference systems (FIS) is proposed. A two-stage adaptive FIS synthesis algorithm is described. At the first stage, the initial fuzzy parameters are clustered in order to reduce the number of …

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 …

Filtered-Dynamic-Inversion Control For Unknown Minimum-Phase Systems With Unknown Relative Degree, Sumit Suryakant Kamat

Theses and Dissertations--Mechanical and Aerospace Engineering

We present filtered-dynamic-inversion (FDI) control for unknown linear time-invariant systems that are multi-input multi-output and minimum phase with unknown-but-bounded relative degree. This FDI controller requires limited model information, specifically, knowledge of an upper bound on the relative degree and knowledge of the first nonzero Markov parameter. The FDI controller is a single-parameter high-parameter-stabilizing controller that is robust to uncertainty in the relative degree. We characterize the stability of the closed-loop system. We present numerical examples, where the FDI controller is implemented in feedback with mathematical and physical systems. The numerical examples demonstrate that the FDI controller for unknown relative degree …

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, …

Zips Racing Electric Can Communications, Andrew Jordan, Adam Long, Susanah Kowalewski, Rami Nehme

Williams Honors College, Honors Research Projects

The CAN protocol has been a standard of electronic communication networks of automotive vehicles since the early 2000s due to its robust reliability in harsh environments. For the 2020 competition year, the Zips Racing Electric design team will be building an entirely new, fully-electric vehicle with CAN communication implemented rather than communicating via pure analog signals. Hardware and software can be utilized to read analog electrical signals from a source, such as accelerator and brake sensors, and encode them into a digital message that meets the CAN 2.0B communication protocol standard. Likewise, software can be used to extract data from …

Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many future robotic applications such as the operation in large uncertain environment depend on a more autonomous robot. The robotics long term autonomy presents challenges on how to plan and schedule goal locations across multiple days of mission duration. This is an NP-hard problem that is infeasible to solve for an optimal solution due to the large number of vertices to visit. In some cases the robot hardware constraints also adds the requirement to return to a charging station multiple times in a long term mission. The uncertainties in the robot model and environment require the robot planner to account …

Implementation Of Radial Basis Function Artificial Neural Network Into An Adaptive Equivalent Consumption Minimization Strategy For Optimized Control Of A Hybrid Electric Vehicle, Thomas P. Harris

Graduate Theses, Dissertations, and Problem Reports (ETD)

Continued increases in the emission of greenhouse gases by passenger vehicles has accelerated the production of hybrid electric vehicles. With this increase in production, there has been a parallel demand for continuously improving strategies of hybrid electric vehicle control. The goal of an ideal control strategy is to maximize fuel economy while minimizing emissions. The design and implementation of an optimized control strategy is a complex challenge. Methods exist by which the globally optimal control strategy may be found. However, these methods are not applicable in real-world driving applications since these methods require a priori knowledge of the upcoming drive …