Дисертації з теми "Autonomous Vehicle Network"
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BRUCE, WILLIAM, and OTTER EDVIN VON. "Artificial Neural Network Autonomous Vehicle : Artificial Neural Network controlled vehicle." Thesis, KTH, Maskinkonstruktion (Inst.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191192.
Повний текст джерелаDenna rapport har som mal att beskriva hur en Artificiellt Neuronnatverk al- goritm kan anvandas for att kontrollera en bil. Det beskriver teorin bakom neu- ronnatverk och autonoma farkoster samt hur en prototyp, som endast anvander en kamera som indata, kan designas for att testa och utvardera algoritmens formagor. Rapporten kommer visa att ett neuronnatverk kan, med bildupplos- ningen 100 × 100 och traningsdata innehallande 900 bilder, ta beslut med en 0.78 sakerhet.
Moore, Christopher, Dylan Crocker, Garret Coffman, and Bryce Nguyen. "Telemetry Network for Ground Vehicle Navigation." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595750.
Повний текст джерелаThis paper describes a short distance telemetry network which measures and relays time, space, and position information among a group of ground vehicles. The goal is to allow a lead vehicle to be under human control, or perhaps controlled using advanced autonomous path planning and navigation tools. The telemetry network will then allow a series of inexpensive, unmanned vehicles to follow the lead vehicle at a safe distance. Ultrasonic and infrared signals will be relayed between the vehicles, to allow the following vehicles to locate their position, and track the lead vehicle.
Schmiterlöw, Maria. "Autonomous Path Following Using Convolutional Networks." Thesis, Linköpings universitet, Datorseende, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78670.
Повний текст джерелаDarr, Matthew John. "DEVELOPMENT AND EVALUATION OF A CONTROLLER AREA NETWORK BASED AUTONOMOUS VEHICLE." UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/192.
Повний текст джерелаMagnusson, Filip. "Evaluating Deep Learning Algorithms for Steering an Autonomous Vehicle." Thesis, Linköpings universitet, Programvara och system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153450.
Повний текст джерелаGarratt, Matthew Adam, and m. garratt@adfa edu au. "Biologically Inspired Vision and Control for an Autonomous Flying Vehicle." The Australian National University. Research School of Biological Sciences, 2008. http://thesis.anu.edu.au./public/adt-ANU20090116.154822.
Повний текст джерелаMatson, Nathan C. "Communications network design, simulation, and analysis for an autonomous unmanned vehicle system." Thesis, Monterey California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/33993.
Повний текст джерелаIn this thesis, we designed, simulated, and analyzed a wireless communications system for an autonomous unmanned vehicle system. The system used for the design context is the Unmanned Vehicle (UV) Sentry, which is a system of autonomous unmanned vehicles that can be tasked for a variety of missions that involve the patrolling and protecting of a geographical region. Accordingly, the communications network needs to allow for flexibility of the vehicle topography to enable large amounts of delay intolerant sensor data to be transmitted between nodes and a capability that allows vehicles to act as relays for other vehicles. To meet these requirements, a medium access control (MAC) relay protocol based on the IEEE 802.16 standard was developed. To evaluate the performance of the protocol, Simulink was used to model the performance of the protocol as it was implemented in a specific UV Sentry scenario. Several network parameters were chosen as factors for the model, and these factors were systematically varied to yield a full factorial design of experiments. The network quality of service parameters for the tests were then analyzed to determine the best communication network configuration for the UV Sentry scenario and to illuminate the tradeoffs between the factors.
Tekin, Mim Kemal. "Vehicle Path Prediction Using Recurrent Neural Network." Thesis, Linköpings universitet, Statistik och maskininlärning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166134.
Повний текст джерелаYoumans, Elisabeth A. "Neural network control of space vehicle orbit transfer, intercept, and rendezvous maneuvers." Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-06062008-162101/.
Повний текст джерелаFlores, Javier Alejandro. "Autonomous vehicle navigation a comparative study of classical logic and neural network technique /." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.
Повний текст джерелаBauman, Cheryl Lynn. "Autonomous Navigation of a Ground Vehicle to Optimize Communication Link Quality." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/36302.
Повний текст джерелаMaster of Science
Freudinger, Lawrence C., Filiberto Macias, and Harold Cornelius. "Frequency Agile Transceiver for Advanced Vehicle Data Links." International Foundation for Telemetering, 2009. http://hdl.handle.net/10150/605968.
Повний текст джерелаEmerging and next-generation test instrumentation increasingly relies on network communication to manage complex and dynamic test scenarios, particularly for uninhabited autonomous systems. Adapting wireless communication infrastructure to accommodate challenging testing needs can benefit from reconfigurable radio technology. Frequency agility is one characteristic of reconfigurable radios that to date has seen only limited progress toward programmability. This paper overviews an ongoing project to validate a promising chipset that performs conversion of RF signals directly into digital data for the wireless receiver and, for the transmitter, converts digital data into RF signals. The Software Configurable Multichannel Transceiver (SCMT) enables four transmitters and four receivers in a single unit, programmable for any frequency band between 1 MHz and 6 GHz.
Lindberg, Jonas, and Källman Isak Wolfert. "Vehicle Collision Risk Prediction Using a Dynamic Bayesian Network." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273629.
Повний текст джерелаDetta arbete behandlar problemet att förutsäga kollisionsrisken för fordon som kör i komplexa trafikscenarier för några sekunder i framtiden. Metoden är baserad på tidigare forskning där dynamiska Bayesianska nätverk används för att representera systemets tillstånd. Vanliga riskprognosmetoder kategoriseras ofta i tre olika grupper beroende på deras abstraktionsnivå. De mest komplexa av dessa är interaktionsmedvetna modeller som tar hänsyn till förarnas interaktioner. Dessa modeller lider ofta av hög beräkningskomplexitet, vilket är en svår begränsning när det kommer till praktisk användning. Modellen som studeras i detta arbete tar hänsyn till interaktioner mellan förare genom att beakta förarnas avsikter och trafikreglerna i scenen. Tillståndet i trafikscenen som används i modellen innehåller fordonets fysiska tillstånd, förarnas avsikter och förarnas förväntade beteende enligt trafikreglerna. För att möjliggöra riskbedömning i realtid görs en approximativ inferens av tillståndet givet den brusiga sensordatan med hjälp av sekventiell vägd simulering. Två olika mått på risk studeras. Det första är baserat på förarnas avsikter, närmare bestämt att ta reda på om de inte överensstämmer med den förväntade manövern, vilket då skulle kunna leda till en farlig situation. Det andra riskmåttet är baserat på ett prediktionssteg som använder sig av time to collision (TTC) och time to critical collision probability (TTCCP). Den implementerade modellen kan tillämpas i komplexa trafikscenarier med många fordon. I detta arbete fokuserar vi på scerarier i korsningar och rondeller. Modellen testas på simulerad och verklig data från dessa scenarier. I dessa kvalitativa tester kunde modellen korrekt identifiera kollisioner några få sekunder innan de inträffade. Den kunde också undvika falsklarm genom att lista ut vilka fordon som kommer att lämna företräde.
Тарасов, О. Є. "Інтелектуальна система автоматичного керування автомобілем у віртуальній моделі навколишнього середовища". Thesis, Чернігів, 2021. http://ir.stu.cn.ua/123456789/25133.
Повний текст джерелаКваліфікаційна робота передбачає дослідження сучасного стану розвитку галузі безпілотних автомобілів, а також основних технологій, які в ній застосовуються; дослідження можливостей використання віртуальних середовищ для перевірки ефективності роботи систем автоматичного керування автомобілем; розробку системи автоматичного керування автомобілем та оцінку ефективності її роботи у віртуальній моделі навколишнього середовища. Віртуальне середовище повинно являти собою модель реального світу зі змінними довколишніми умовами: погодою, ландшафтом, часом доби. При виборі перевага має надаватися тим варіантам, в яких дорожня інфраструктура реалізована більш детально та реалістично. Розроблювана система має складатися з частин, що повинні виконувати наступні функції: - підсистема збору даних: отримання даних з віртуального середовища, їх зберігання у сховищі даних; - підсистема обробки даних: підготовка зібраних даних для реалізації системи автоматичного керування; реалізація обраних технологій на основі зібраних даних; - підсистема керування: інтеграція реалізованої системи автоматичного керування до віртуального середовища.
Qualification work involves the study of the current state of development of the unmanned vehicle industry, as well as the main technologies used in it; research of possibilities of use of virtual environments for check of efficiency of work of systems of automatic control of the car; development of an automatic car control system and evaluation of its efficiency in a virtual model of the environment. The virtual environment should be a model of the real world with changing environmental conditions: weather, landscape, time of day. When choosing, preference should be given to those options in which the road infrastructure is implemented in more detail and realistically. The developed system should consist of parts that must perform the following functions: - data collection subsystem: obtaining data from the virtual environment, storing them in the data warehouse; - data processing subsystem: preparation of collected data for the implementation of automatic control system; implementation of selected technologies based on collected data; - control subsystem: integration of the implemented automatic control system into the virtual environment.
Jönsson, Jonatan, and Felix Stenbäck. "Monte-Carlo Tree Search in Continuous Action Spaces for Autonomous Racing : F1-tenth." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42442.
Повний текст джерелаStepien, Hubert, and Martin Bilger. "Diverse Time Redundant Triplex Parallel Convolutional Neural Networks for Unmanned Aerial Vehicle Detection." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54596.
Повний текст джерелаSilva, Joelson Coelho da. "Uma proposta de controle neural adaptativo para a navegação de veículos autônomos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1999. http://hdl.handle.net/10183/18631.
Повний текст джерелаThe robotic equipments were created initially to actuate in closed industrial environments. Improvements have been acquieved in this area. Nowadays, they are no longer limited to perform simple and repetitive tasks in controlled places. New equipments, capable of acting in open environments and doing the most several activities, are being developed. For so much, it is necessary that its control systems accomplish an effective interaction with the world where they are inserted. Therefore, new systems controllers with capacity of a continuous adaptation to the dynamic environments are essential. Artificial neural networks, due to their capacity of dealing wit non-linear problems – mathematically difficult to be solved – are being used to control these kind of processes. Guide a mobile vehicle through an open or controlled environments is a highly non-linear procedure; therefore, the use of an artificial neural nets is quite promising. In spite of its great versatility, they have just been used as mapping systems. Most of them need a training phase so that they can store the diversity of system’s possible states. When they actuate, they simply map their input values (current state) to the solutions previously stored. However, this is not the best approach for open systems, i.e. systems whose situations and possibilities cannot be totally enumerated and that can change in time. This work presents an adaptive neural control methodology to guide a mobile vehicle to its target in environments with fixed or mobile obstacles. Differently from the traditional approaches, the need of a previous training phase of the neural network doesn't exist. The chosen model of artificial neural net promotes a continuous adaptation of the system while it actuates. Sensors are used to provide informations to the net. This way it generates partial solutions that makes the autonomous vehicle gets closer of its goal, until, finally, reach it.
Rahman, Quazi Marufur. "Performance monitoring of deep learning vision systems during deployment." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/229733/1/Quazi%20Marufur_Rahman_Thesis.pdf.
Повний текст джерелаBerggren, Filip, and Jakob Engström. "Autonoma fordon – En jämförelse av tekniker för identifiering av utryckningsfordon." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264433.
Повний текст джерелаThe demand for safety and effectivity continuously increases within the automotive industry. One way to meet these demands is to achieve a higher level of autonomy, but to achieve the highest levels of autonomy there is a few problems to be solved along the way. This report treats one of these, an autonomous vehicle’s ability to identify emergency vehicles. The report, based on a pilot study, analyses the ITS G5 standard, IEEE 802.11g, Zigbee and mobile networks based on their technological specifications. From the analysis three situations are identified where the technologies are considered limited. These limitations are, but not limited to, reach, latency, data rates and ability to communicate vehicle to vehicle (V2V). The four technologies are then compared by these limitations in a matrix. The result shows that ITS G5 and ZigBee has the best performance by its own but the combination of mobile networks and ITS G5 shows the highest possible performance.
Strandell, Erstorp Elias. "Evaluation of the LSTS Toolchain for Networked Vehicle Systems on KTH Autonomous Maritime Vehicles." Thesis, KTH, Marina system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-185273.
Повний текст джерелаLebre, Marie-Ange. "De l'impact d'une décision locale et autonome sur les systèmes de transport intelligent à différentes échelles." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI007/document.
Повний текст джерелаIn this thesis we present vehicular applications across different scales: from small scale that allows real tests of communication and services; to larger scales that include more constraints but allowing simulations on the entire network. In this context, we highlight the importance of real data and real urban topology in order to properly interpret the results of simulations. We describe different services using V2V and V2I communication. In each of them we do not pretend to take control of the vehicle, the driver is present in his vehicle, our goal is to show the potential of communication through services taking into account the difficulties outlined above. In the small scale, we focus on a service with a traffic light that improves travel times, waiting times and CO2 and fuel consumption. The medium scale is a roundabout, it allows, through a decentralized algorithm, to improve the same parameters. It also shows that with a simple and decentralized decision-making process, the system is robust to packet loss, density, human behavior or equipment rate. Finally on the scale of a city, we show that local and decentralized decisions, with only a partial access to information in the network, lead to results close to centralized solutions. The amount of data in the network is greatly reduced. We also test the response of these systems in case of significant disruption in the network such as roadworks, terrorist attack or natural disaster. Models, allowing local decision thanks to information delivered around the vehicle, show their potential whatsoever with the V2I communication or V2V
Hallqvist, Erik, and Sebastian Håkansson. "Networked control of autonomous ground vehicles." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199347.
Повний текст джерелаEhrlin, E., and M. Törnqvist. "Networked control of autonomous ground vehicles." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199313.
Повний текст джерелаAthari, Kayvan. "Networked control of autonomous ground vehicles." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199389.
Повний текст джерелаBakutis, Vladas, and Qiao Jin. "Networked Control of Autonomous Ground Vehicles." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200572.
Повний текст джерелаOrihuela, Swartling Johanna, and Magnus Pontusson. "Cooperative networked control of autonomous ground vehicles." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199264.
Повний текст джерелаLycke, Jens, and Fredrik Svensson. "Cooperative networked control of autonomous ground vehicles." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199265.
Повний текст джерелаBsaybes, Sahar. "Models and algorithms for fleet management of autonomous vehicles." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAC114/document.
Повний текст джерелаThe VIPAFLEET project aims at developing a framework to manage a fleet of IndividualPublic Autonomous Vehicles (VIPA). We consider a fleet of cars distributed at specifiedstations in an industrial area to supply internal transportation, where the cars can beused in different modes of circulation (tram mode, elevator mode, taxi mode). The goalis to develop and implement suitable algorithms for each mode in order to satisfy all therequests either under an economic point aspect or under a quality of service aspect, thisby varying the studied objective functions.We model the underlying online transportation system as a discrete event basedsystem and propose a corresponding fleet management framework, to handle modes,demands and commands. We consider three modes of circulation, tram, elevator andtaxi mode. We propose for each mode appropriate online algorithms and evaluate theirperformance, both in terms of competitive analysis and practical behavior by computationalresults. We treat in this work, the pickup and delivery problem related to theTram mode and the Elevator mode the pickup and delivery problem with time windowsrelated to the taxi mode by means of flows in time-expanded networks
Smart, Royce Raymond, and roycesmart@hotmail com. "Evolutionary Control of Autonomous Underwater Vehicles." RMIT University. Aerospace, Mechanical and Manufacturing Engineering, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20090331.143104.
Повний текст джерелаSchennings, Jacob. "Deep Convolutional Neural Networks for Real-Time Single Frame Monocular Depth Estimation." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-336923.
Повний текст джерелаStenberg, Josefin, and Sabina Syed. "Optimal Multi-Commodity Network Flow of Autonomous Vehicles in Urban Traffic." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297491.
Повний текст джерелаManara, Luca. "Investigating Antenna Placement on Autonomous Mining Vehicle." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204908.
Повний текст джерелаFramtidens gruvor kommer att gynnas av sammankopplade, intelligenta transportsystem. Autonoma gruvfordon kommer att förbättra säkerhet och produktivitet, och samtidigt minska bränslekonsumtion. Därför är det nödvändigt för Scania att öka kunskapen om design av kommunikationssystem för fordon i hård gruvmiljö. Målet för detta projekt är att undersöka kraven för antennplacering hos ett framtida autonomt gruvfordon och att ge förslag på passande antenntyper och -positioner. Det elektromagnetiska simuleringsverktyget CST Microwave Studio används för att uppskatta påverkan från en förenklad fordonsgeometri på grundläggande antennstrålningsmönster. Utvalda antennkonfigurationer utvärderas genom undersökningar av dess strålningsmönster. För att kunna stråla ut tillräcklig effekt i området kring fordonet och garantera tillförlitlig kommunikation krävs centralt placerade runtstrålande antenner, eller alternativt en patchantenn till varje sida. Problemlösningsmetoden utvärderas också: Flexibiliteten simuleringsmetoden ger betonas, medan några relevanta begränsningar diskuteras. Hårdvarukrav, tillgängligheten av modeller och begränsade resultat från mjukvaran kan bidra till att göra simuleringen olämplig för att utvärdera antennplaceringen.
ANDERSSON, SANTIAGO GABRIEL, and MARTIN FAVRE. "Analysis and Evaluation of Recurrent Neural Networks in Autonomous Vehicles." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217336.
Повний текст джерелаTraditionellt har bilar körts av antsändiga människor. Teknologin har idag dock kommit till den punkten då komplexa system kan köra med minimal eller full avsaknad av mänsklig interaktion. Medan det visserligen tar bort den trevliga söndagsturen så måste man tänka på fördelarna. I över 90% av alla fordonsolyckor är orsaken grundad i föraren. Stadstrafik kan bli optimerad för att undvika trafikstockningar. Dessutom att förlämga ens morgontur med hela bilresan till jobbet är verkligen något att sträva efter. Ett av sätten man kan uppnå autonom körning är genom artificiella neurala nätverk. Dessa system lär en modell hur man kör med hjälp av stora mängder data som består av ett tillstånd och dess korrekta handling. Minimal mängd manuell design krävd. En av de flera problem som Artificiella Neurala Nätverk har är att de inte har något minne, utan tar bara en stor mängd individuella beslut. Detta kan skapa problem i situationer som omkörning då det kräver en längre plan för att säkert ta sig runt andra bilen. Den här uppsatsen undersöker `Recurrent´ Neurala Nätverk som är designade för att analysera sekvenser av tillstånd iställer för ett enkelt tillstånd med hopp om att det kommer lindra de skventiella problemen. Detta är gjort genom att modifiera en 1/12 i skala radiostyrd bil med en kamera på framsidan. Dessa bilder används för att kontrollera både styrning eller hastighet i tre separata experiment som simulerar vanliga körningsscenarion i vilka sekvensen av tillstånd innehåller information. I alla tre experiment testades tre olika nätverk. Dessa analyserar respektibe 1, 5 och 25 tillstånd. Utöver dessa gjordes även experiment med en mänsklig förare som grundreferens. Resultaten jämfördes och evaluerades kvalitativt. Slutresultatet visade att det fanns tillfällen då det var bättre att analysera flera tillstånd, men att fler och mer repeterbara tester behövs för att kunna slå fast när och varför.
Lyu, Yiru. "Behavior Prediction of Surrounding Vehicles in a Road Network for Autonomous Driving." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263236.
Повний текст джерелаFör att säkerställa hög säkerhet i vägnätverket, ska ett autonomt fordon ha en god förståelse för sin omgivande miljö samt kunna resonera om hur den kommer utvecklas med tiden. Detta arbete innefattar ett ramverk för rörelsemönsterprediktion för omgivande fordon i ett motorvägssystem baserat på deras historik, såsom tidigare positioner, hastigheter och närliggande fordon. Ramverket består av ett långoch korttidsminnesbaserat neuralt nätverk (Long Short Term Memory, LSTM) med en kodaroch avkodarstruktur som hanterar detta sekvens-till-sekvens-prediktionsproblem. För att ta hänsyn till osäkerhet associeras osäkerhetsvärden till de olika predikterade rörelsemönstren baserat på ett manöver-klassificeringsnätverk, så att ramverkets slutliga utdata är flera möjliga framtida banor med associerade sannolikheter. Experimenten är baserade på data från NGSIM US-101 och I-80 och resultaten visar att detta ramverk överträffar ett enkelt staplat LSTM nätverk. Utöver detta analyseras även indatat till nätverket för att utvärdera de olika insignalernas påverkan på prediktionernas prestanda.
Richard, Mark G. "Cooperative control of distributed autonomous systems with applications to wireless sensor networks." Thesis, Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Jun/09Jun%5FRichard.pdf.
Повний текст джерелаThesis Advisor(s): Lee, Deok Jin ; Kaminer, Issac I. "June 2009." Description based on title screen as viewed on 13 July 2009. Author(s) subject terms: Unmanned Aerial Vehicle, UAV, extremum seeking, simulink, high bandwidth communication links, SNR Model, coordinated control, cooperative control, decentralized control, wireless sensor network. Includes bibliographical references (p. 51). Also available in print.
Sparrenhök, Jonny. "Influential Learning : Knowledge Sharing between Artificial Neural Networks for Autonomous Vehicles." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301643.
Повний текст джерелаAutonoma fordon kan komma att bli en del av vår framtid oavsett om vi så önskar eller inte. Den teknik som har utvecklats för ändamålet är redan idag bättre i flertalet aspekter på att hantera fordon än vad människor är. Implementationer av autonoma fordon bygger ofta på maskininlärning där en modell lär sig att manövrera fordonet med hjälp av data som samlas in genom inbyggda system. En vanligt tillvägagångssätt för att förbättra dessa autonoma fordon är att använda sig av kameror, där de insamlade bilderna kan behandlas och utvärderas av modeller skapade för att främja datorseende. Det finns många användningsområden där datorseende kan appliceras inom autonoma fordon bland annat objektigenkänning, lokalisering, rörelseuppskattning och scenförståelse. Åtskilliga implementationer har föreslagits med ambitionen att optimera dessa modeller och utnyttja deras fulla potential så att autonoma system kan mönvrera ett fordon på bästa möjliga sätt. Det är inte bara styrning och hastighet som är viktigt för dessa modeller, det är också av stor betydelse att dessa system agerar snabbt då fordonen ofta rör sig i höga hastigheter. Den här uppsatsen utvärderar ett tillvägagångssätt som involverar en kombination av några av de främsta maskininlärnings modellerna inom optiskt flöde och bildsegmentering. Samtidigt som en av dessa modeller lär sig att manövrera styrning av fordonet så lär den sig att imitera modeller som tidigare har visat väldigt bra resultat inom andra uppgifter som är relaterade till datorseende i autonoma fordon. De modeller som är involverade är faltningsnätverk och imitationen sker med avsikten att den modell som är avsedd att lära sig styra fordonet ska ta del av den kunskap som indikerar styrvinkel ifrån de andra nätverken. Projektet som utförs i samband med den här uppsatsen visar att modellen blir signifikant förbättrad på att utvärdera styrvinkel för de fallen där alla faltningsnätverk klarar av att hantera datan. Efter träning förkastar modellen hjälpnätverken och uppnår därför samma behandlingstid och minnesanvändning som ett nätverk där dessa inte involveras.
Janet, Jason Andre. "Pattern analysis, tracking and control for autonomous vehicles using neural networks." Raleigh, NC : North Carolina State University, 1998. http://www.lib.ncsu.edu/etd/public/etd-45309999852811/etd.pdf.
Повний текст джерелаWineman, Patrick L. "Technical benefits and cultural barriers of networked Autonomous Undersea Vehicles." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79538.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (p. 44-45).
The research presented in this thesis examines the technical benefits to using a collaborative network of Autonomous Undersea Vehicles (AUVs) in place of individual vehicles. Benefits could be achieved in the areas of reduced power consumption, improved positional information and improved acoustic communication bandwidth. However, current culture of AUV development may impede this approach. The thesis uses the Object Process Methodology (OPM) and principles of System Architecture to trace the value of an AUV system from the scientist who benefits from the data to the vehicle itself. Sections 3 and 4 outline the needs for an AUV system as they currently exist and describe the key physics-based limitations of operations. Section 5 takes a broader look at the system goal as data delivery, not just the deployment of a vehicle, and introduces the concept of networked AUV. Section 6 describes a potential evolution of networked AUVs in increasing autonomy and collaboration. Finally, Section 7 examines AUV development cultures that could impede, or foster, networked vehicles.
by Patrick L. Wineman.
S.M.
Risan, Øyvind. "Virtual (floating) Context Sharing between Vehicles : Generating and Sharing Context Information within an Autonomous Network of Vehicles." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11319.
Повний текст джерелаEze, Elias Chinedum. "Achieving reliable and enhanced communication in vehicular ad hoc networks (VANETs)." Thesis, University of Bedfordshire, 2017. http://hdl.handle.net/10547/622523.
Повний текст джерелаDoolittle, Daniel Foster. "Automated Fish Species Classification using Artificial Neural Networks and Autonomous Underwater Vehicles." W&M ScholarWorks, 2003. https://scholarworks.wm.edu/etd/1539617813.
Повний текст джерелаWegener, Jan-Thierry. "Redeployment in Convoys of Fleets of Shared Vehicles." Thesis, Clermont-Ferrand 2, 2016. http://www.theses.fr/2016CLF22722/document.
Повний текст джерелаCarsharing is a modern way of car rental, attractive to customers who make only occasional use of a car on demand. In a carsharing system, a fleet of cars is distributed at specified stations in an urban area, customers can take a car at any time and station and return it at any time and station, provided that there is a car available at the start station and a free place at the destination station. To ensure the latter, customers have to book their demands in advance. For operating such a system in a satisfactory way, the stations have to keep a good ratio between the total number of places and the number of cars in each station, in order to serve as many requests as possible. This leads to the problem of balancing the load of the stations, called Relocation Problem: an operator has to monitor the load and to decide when and how to move cars from “overfull” stations to “underfull” ones. We consider an innovative carsharing system, where the cars are partly autonomous, which allows to build wireless convoys of cars leaded by a special vehicle, such that the whole convoy is moved by only one driver. This setting is similar to bikesharing, where trucks can simultaneously move several bikes during the relocation process. In this thesis, we address the dynamic and static aspects of the Relocation Problem. The “Dynamic Relocation Problem” describes the situation when cars can be moved between stations during the working hours in order to satisfy the needs of the customers. Hereby, the operator has to make decisions dynamically according to the current situation. In the “Static Relocation Problem” we assume that there is no (or only little) interaction by customers with the system. This situation occurs when the carsharing system is prepared for the next day, i.e., the relocation process is performed during the night. We model the Relocation Problem in the framework of a metric task system. Afterwards, we theoretically analyze both problems and give strategies to solve them. Finally, we perform some computational experiments to examine the applicability of the presented algorithms in practice
Puttige, Vishwas Ramadas Engineering & Information Technology Australian Defence Force Academy UNSW. "Neural network based adaptive control for autonomous flight of fixed wing unmanned aerial vehicles." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43736.
Повний текст джерелаAugustsson, Louise. "Study and Analysis of Convolutional Neural Networks for Pedestrian Detection in Autonomous Vehicles." Thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353608.
Повний текст джерелаDabboussi, Abdallah. "Dependability approaches for mobile environment : Application on connected autonomous vehicles." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCA029.
Повний текст джерелаConnected and Autonomous vehicles (CAV) must have adequate reliability and safety requirements in uncertain environments with complex circumstances. Sensor technology, actuators and artificial intelligence (AI) are constantly and rapidly evolving, thus enabling further development of self-driving vehicles, and increasing the automation of driving. CAV shows many benefits in human life such as increasing road safety, reducing pollution, and providing independent mobility to non-drivers. However, these advanced components create a new set of challenges concerning safety and dependability. Hence, it is necessary to evaluate these technologies before implementation.We study in this thesis the reliability of CAV as a whole, focusing on sensors and the communication system. For that purpose, a functional analysis was done for the CAV system.Our scientific approach for the analyzing the CAV reliability, was structured with methods that combine quantitative and qualitative approaches such as functional analysis for both internal and external, Preliminary Risk Analysis (PRA), and failure modes and effects criticality analysis (FMECA), in addition to other analysis techniques.To prove our results, a simulation was done using the Fault Tree analysis (FTA) probability in order to validate the proposed approach. The data (Failure ratio) used were from a professional database related to the type of components presented in the system. Using this data, a probabilistic model of degradation was proposed. A probability calculation was performed in relation to a reference time of use. Thereafter a sensitivity analysis was suggested concerning the reliability parameters and redesign proposals developed for the components.CAV provide several communication models: vehicles to vehicle (V2V), or with Road Side Infrastructure: vehicle to infrastructure (V2I). Dedicated Short Range Communication (DSRC) employs a multichannel approach to cater for a variety of safety and non-safety applications. Safety applications necessitate appropriate and reliable transmissions, while non-safety applications require performance and high speed. Broadcasting of Basic Safety Messages (BSM) is one of the fundamental services in today’s connected vehicles. For that, an analytical model to evaluate the reliability of IEEE 802.11 based V2V safety-related broadcast services in DSRC system on highway was proposed. Finally, an enhancement on the proposed model was made in order to increase the reliability of the V2V connection, taking into consideration many factors such as transmission range, vehicle density, and safety headway distance on highway, packet error rate, noise influence, and failures rates of communication equipment.Evaluating these problems leads to a sensitivity analysis related to reliability parameters, which helps further innovation in CAV and automobile engineering
Ekinci, Murat. "Computer vision applied to the navigation of an autonomous road vehicle in complex road networks." Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361132.
Повний текст джерелаKaygisiz, Huseyin Burak. "Intelligent Methods For Dynamic Analysis And Navigation Of Autonomous Land Vehicles." Phd thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605112/index.pdf.
Повний текст джерелаMostafa, Ahmad A. "Packet Delivery Delay and Throughput Optimization for Vehicular Networks." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367924037.
Повний текст джерелаMarsilio, Alan M. "Use of Hopfield networks for system identification and failure detection in autonomous underwater vehicles." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/28628.
Повний текст джерелаLivianu, Mathew Joseph. "Human-in-the-loop neural network control of a planetary rover on harsh terrain." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26576.
Повний текст джерелаCommittee Chair: Dr. Ayanna Howard; Committee Member: Dr. Patricio Vela; Committee Member: Dr. Yoria Wardi. Part of the SMARTech Electronic Thesis and Dissertation Collection.