Navigation, Guidance, Control, and Dynamics Commons^™

Assessment Of Conventional And Air-Jet Wheel Deflectors For Drag Reduction Of The Drivaer Model, Sandra K. S. Boetcher, Kaloki L. Nabutola

Publications

Aerodynamic drag is a large resistance force to vehicle motion, particularly at highway speeds. Conventional wheel deflectors were designed to reduce the wheel drag and, consequently, the overall vehicle drag; however, they may actually be detrimental to vehicle aerodynamics in modern designs. In the present study, computational fluid dynamics simulations were conducted on the notchback DrivAer model—a simplified, yet realistic, open-source vehicle model that incorporates features of a modern passenger vehicle. Conventional and air-jet wheel deflectors upstream of the front wheels were introduced to assess the effect of underbody-flow deflection on the vehicle drag. Conventional wheel-deflector designs with varying heights …

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

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Data-Driven Based Automatic Routing Planning For Mass, Qingwu Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

In The Context Of Unmanned Vessels : Obstacles To The Application Of Colregs And Suggestions For Its Amendments, Baochuan Sun

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Research On The Methods Of Ship's Autonomous Collision Avoidance In Complex Environment, Hongguang Lyu

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Research On Collision Avoidance And Safety Measures Of Drilling Platform Towing Group, Junpo Liu

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 …

Experimental Research Of The Hydraulic System Of The Unloading Device Of Trailers, Hayrullo Rahimovich Baynazarov, A A. Shermukhamedov

Scientific-technical journal

The article presents the results of an experimental research to substantiate the basic parameters of the unloading device of the trailers.

Autonomous Aerial Vehicle Vision And Sensor Guided Landing, Gabriel Bitencourt, Elijah J. Brown, Cedric Bleimling, Gilbert Lai, Arman Molki, Tolga Kaya

School of Computer Science & Engineering Faculty Publications

The use of autonomous landing of aerial vehicles is increasing in demand. Applications of this ability can range from simple drone delivery to unmanned military missions. To be able to land at a spot identified by local information, such as a visual marker, creates an efficient and versatile solution. This allows for a more user/consumer friendly device overall. To achieve this goal the use of computer vision and an array of ranging sensors will be explored. In our approach we utilized an April Tag as our location identifier and point of reference. MATLAB/Simulink interface was used to develop the platform …

A Deep Learning-Based Automatic Object Detection Method For Autonomous Driving Ships, Ojonoka Erika Atawodi

Master's Theses

An important feature of an Autonomous Surface Vehicles (ASV) is its capability of automatic object detection to avoid collisions, obstacles and navigate on their own.

Deep learning has made some significant headway in solving fundamental challenges associated with object detection and computer vision. With tremendous demand and advancement in the technologies associated with ASVs, a growing interest in applying deep learning techniques in handling challenges pertaining to autonomous ship driving has substantially increased over the years.

In this thesis, we study, design, and implement an object recognition framework that detects and recognizes objects found in the sea. We first curated …

Adaptive Task Allocation In Automated Vehicles, Skye Taylor, Bin Hu, Jing Chen

Psychology: Interdisciplinary Research in Behavioral Sciences of Transportation Issues

Adaptive task allocation is used in many human-machine systems and has been proven to improve operators’ monitoring and/or performance with automated systems. However, there is little knowledge surrounding the benefits of adaptive task allocation in automated vehicles. In this study, participants were presented with media depicting driving scenarios of both low and high workload at two levels of automation. The participants reported which tasks they felt comfortable allocating to themselves or to the automated system in each driving scenario, as well as whether they would conduct the task allocation manually or have the automated system automatically allocate the tasks. The …

Local Climate Action Planning As A Tool To Harness The Greenhouse Gas Emissions Mitigation And Equity Potential Of Autonomous Vehicles And On-Demand Mobility, Serena Alexander, Asha Weinstein Agrawal, Benjamin Y. Clark

Mineta Transportation Institute

This report focuses on how cities can use climate action plans (CAPs) to ensure that on-demand mobility and autonomous vehicles (AVs) help reduce, rather than increase, green-house gas (GHG) emissions and inequitable impacts from the transportation system. We employed a three-pronged research strategy involving: (1) an analysis of the current literature on on-demand mobility and AVs; (2) a systematic content analysis of 23 CAPs and general plans developed by municipalities in California; and (3) a comparison of findings from the literature and content analysis of plans to identify opportunities for GHG emissions reduction and mobility equity.

Findings indicate that maximizing …

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 …

Experimental Evaluation And Simulation Of Torque Transmissibility Frequency Response Functions Of Vibration Isolators And Absorbers For Drivetrain Applications, Luke Jurmu

Dissertations, Master's Theses and Master's Reports

Four studies involving torsional vibration isolation performance of automotive drivetrain components, make up this dissertation. One study features a prototype planetary torsional vibration absorber, a unique device that targets low frequency torsion modes in automotive drivetrains. Two studies feature experiments on several torque converters, clutch locked and open, to validate models of the hardware. The last study details experiments on a centrifugal pendulum absorber in a torque converter, to characterize the viscous friction while submerged in automatic transmission fluid (ATF). The enclosed studies improve the state of the art of drivetrain vibration absorbers and isolators, by introducing a new vibration …

Development And Validation Of Dynamic Programming Algorithm For Eco Approach And Departure, Vasu Goyal

Dissertations, Master's Theses and Master's Reports

Eco Approach and Departure (Eco-AnD) is a Connected and Automated Vehicle (CAV) technology developed to reduce energy for crossing a signalized intersection or set of intersections in a corridor that features vehicle to infrastructure (V2I) communication capability. Eco-AnD technology uses the information of the signal phase and timings (SPaT) received from the V2I communication to optimize the vehicle’s speed profile and produce an energy-efficient maneuver to cross the intersection.

The Eco-AnD algorithm is devised for two vehicles (GM-Volt Gen II & GM-Bolt), both with different powertrain architectures but capable of working in electric-only mode. In simulations, the developed algorithm showed …

Less Commute Miles. Decreased Tire Wear. What Would You Do?, Dylan Schwarz, Brendon M. Ford, Brandon D. Hadinger, Abbie N. Pearce, Jacinta M. Pikunas

Williams Honors College, Honors Research Projects

With the flagrant recognition of the coronavirus as one of those most impactful viruses in the history of the world, it is important to study how the effects of such a disease can create troublesome ripple effects in the world. Covid-19 has caused the death of hundreds of thousands of individuals and has negatively impacted the lives of American’s all across the country during the nationwide lockdown. Decreased work commuters, minimal road travel, and little need for car repairs hit the Goodyear Tire and Rubber Company hard. The University of Akron has teamed up with Goodyear to explore such effects …

Planning Algorithms Under Uncertainty For A Team Of A Uav And A Ugv For Underground Exploration, Matteo De Petrillo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Robots’ autonomy has been studied for decades in different environments, but only recently, thanks to the advance in technology and interests, robots for underground exploration gained more attention. Due to the many challenges that any robot must face in such harsh environments, this remains an challenging and complex problem to solve.

As technology became cheaper and more accessible, the use of robots for underground ex- ploration increased. One of the main challenges is concerned with robot localization, which is not easily provided by any Global Navigation Services System (GNSS). Many developments have been achieved for indoor mobile ground robots, making …

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 …

Powertrain Fuel Consumption Modeling And Benchmark Analysis Of A Parallel P4 Hybrid Electric Vehicle Using Dynamic Programming, Aaron Robert Mull

Graduate Theses, Dissertations, and Problem Reports (ETD)

As regulations on the emission of greenhouse gasses continue to tighten on the automotive industry, the production of hybrid electric vehicles has gained significant popularity in recent years. With the increase in production, there has been a parallel demand in the advancement of both mechanical hardware and control system implementation used in these vehicles. A critical factor in the efficient operation of a hybrid electric vehicle is the energy management strategy where the goal is to maximize the efficient use of fuel energy to propel the vehicle. Designing a fuel-efficient control system is a complex challenge due to the degrees …

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 …

Modeling Intangible Assets Of A Logistic Organization, S. Yadgarov Nomozovich Yadgarov

Acta of Turin Polytechnic University in Tashkent

Abstract—The article presents the results of It will be relevant to fill this gap, presumably arising from insufficient elaboration of ap- proaches to the assessment of scientific knowledge, which, along with managerial knowledge and practical competencies of manage- ment in the field of logistics, generates intangible assets. In other words, it is required to show that the "science intensity" of the lo- gistics business is a capitalized asset.

Efficient End-To-End Autonomous Driving, Hesham Eraqi

Theses and Dissertations

Steering a car through traffic is a complex task that is difficult to cast into algorithms. Therefore, researchers turn to train artificial neural networks from front-facing camera data stream along with the associated steering angles. Nevertheless, most existing solutions consider only the visual camera frames as input, thus ignoring the temporal relationship between frames. In this work, we propose a Convolution Long Short-Term Memory Recurrent Neural Network (C-LSTM), which is end-to-end trainable, to learn both visual and dynamic temporal dependencies of driving. Additionally, We introduce posing the steering angle regression problem as classification while imposing a spatial relationship between the …

Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki

Mechanical Engineering Undergraduate Honors Theses

Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the great achievements of deep reinforcement learning in various domains including finance,medicine, healthcare, video games, robotics and computer vision.Deep neural network was started with multi-layer perceptron (1stgeneration) and developed to deep neural networks (2ndgeneration)and it is moving forward to spiking neural networks which are knownas3rdgeneration of neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically-realistic models of neurons to carry out computation. In this thesis, we first provide a comprehensive review …

Intelligent Roadside Unit Deployment In Vehicular Network, Xiangyu Xu

Masters Theses

Intelligent Transportation System (ITS) has been an important research area in building the foundational infrastructures of self-driving vehicles and improving traffic efficiency of future transportation systems. Scientists have been hoping to incorporate intelligence into traditional transportation systems to help reduce the risks, accident rates, traffic congestion, and even environmental emissions.

There are many research works that have been focused on the communication part of ITS, such as vehicular networks, which collect data from vehicles and send it to the cloud for analysis. In the vehicular networks, Roadside Unit (RSU) is a key infrastructure as an intermediate layer between the vehicles …

As The Role Of The Driver Changes With Autonomous Vehicle Technology, So, Too, Must The Law Change, Nanci K. Carr

St. Mary's Law Journal

Getting a driver’s license is a highly anticipated rite of passage for most teenagers. Being alone behind the wheel, in control of a 3,000-pound machine, is an honor, a privilege, and a sign of adult responsibility. How will that change when driver’s licenses become licenses “to cause technology to engage” with the increased use of autonomous cars? Will driver’s education courses, with their focus on safety rules and defensive driving techniques, be eliminated if all a vehicle operator needs to do is push a button and the vehicle does the rest? While arguably autonomous cars are safer, they will not …

Development Of An Improved Arterial Roadway Performance Reliability Methodology, Ernest Tufuor

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

The need for reliable performance measures of urban arterial roadways is increasing because of the rise in traffic congestion and the high value of travel time. Consequently, travel time reliability (TTR), which combines components of measures of central tendency and measures of dispersion of travel times, has recently received considerable research interest.

The basis of all TTR metrics is the travel time distribution (TTD). Estimating and forecasting arterial TTDs for TTR analysis is the focus of this dissertation. This dissertation proposes a new TTR methodology that is a marked improvement on recent TTR estimation and forecasting methodologies including the current …

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 …