Relevant bibliographies by topics / Autonomous Train

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Autonomous Train'

Author: Grafiati
Published: 4 May 2024
Last updated: 14 September 2024

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Journal articles on the topic "Autonomous Train"

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Guo, Yichen. "Design and research of train-centric autonomous control CBTC system." Applied and Computational Engineering 12, no. 1 (September 25, 2023): 260–67. http://dx.doi.org/10.54254/2755-2721/12/20230364.

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Existing CBTC systems suffer from a number of limitations, some of which include convoluted communication between the ground and trains, costly construction, and high costs associated with the installation of ground equipment. The purpose of this study is to further improve the operational efficiency of a train-centric autonomous CBTC system by analyzing the system design, control principles, and module functioning. The planning of ground and onboard equipment will be the main research objects of the novel system. When compared to conventional CBTC systems, the TACS architecture, most notably in the OC and train-train communication modules, changes the control mode from ground-centric to train-centric. This results in an increase in the overall efficiency of the system, and a new train operation scenario of the virtual coupling is introduced to increase the flexibility. The TACS architecture that was designed paves the way for the engineering advancement of the system and establishes the groundwork for it.
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AFANASOV, A., D. LINIK, S. ARPUL, D. BELUKHIN, and V. VASYLYEV. "PROSPECTS OF USING AUTONOMOUS ELECTRIC TRAINS WITH ONBOARD STORAGE STORES." Transport systems and transportation technologies, no. 23 (July 28, 2022): 46. http://dx.doi.org/10.15802/tstt2022/261652.

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Purpose. Improving the efficiency of passenger traffic on non-electrified sections of the railway of Ukraine by optimizing the structure and creating principles for building a traction electric drive of a promising autonomous electric train powered by traction engines from the system of onboard storage of electricity. Methods. The methodological basis of the study are the general theoretical provisions and principles of the system approach of theoretical electrical engineering, theoretical mechanics, theory of electrical machines and converters. The basic principles of management theory and the basics of decision theory are used. Results. The general principles of construction of the traction electric drive of the perspective autonomous electric train with power supply of traction engines from onboard energy storage devices are formulated. The functional scheme of the traction electric drive of the perspective autonomous electric train is offered, the analysis of work of the electric drive in the modes of traction and regenerative braking is carried out. The mass parameters of two types of energy storage devices, namely electrochemical batteries and supercapacitors, have been determined. The basic requirements to the system of automatic control of the traction drive of the electric train are formulated. It is shown that in the future the use of autonomous battery electric trains will be technically possible and economically justified on non-electrified sections of Ukrzaliznytsia.
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Oh, Sehchan, Kyunghee Kim, and Hyeonyeong Choi. "Train interval control and train-centric distributed interlocking algorithm for autonomous train driving control system." Journal of the Korea Academia-Industrial cooperation Society 17, no. 11 (November 30, 2016): 1–9. http://dx.doi.org/10.5762/kais.2016.17.11.1.

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Atherton, Mark, Stuart Hill, David Harrison, and Marco Ajovalasit. "Economic and technical feasibility of a robotic autonomous system for train fluid servicing." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 234, no. 3 (February 20, 2019): 338–50. http://dx.doi.org/10.1177/0954409719830520.

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Rail traffic in passenger miles [in the UK] is projected to increase by 100% over the next 30 years, which presents a considerable challenge for the current infrastructure to perform the regular fluid servicing tasks. Developing robotic autonomous systems for train fluid servicing is a prospect for which no solutions currently exist. Therefore, the economic and technical feasibility of a robotic autonomous system to perform several key fluid servicing tasks on passenger train vehicles is investigated. The fluid servicing tasks chosen include those that to a significant degree are repetitive or hazardous for humans to perform, and therefore if performed by a robotic autonomous system will release service personnel to focus on more suitable tasks. The economic and technical cases presented strongly support the use of a robotic autonomous system for fluid servicing of trains. Generally available robotic autonomous system technology has reached a state of development capable of delivering what is required once reliable couplings and fluid hose technologies have been developed for this application. Overall, the findings are that fluid servicing capacity will at least double for around 15% of the cost of an equivalent manual servicing facility, which represents a substantially attractive business case. There will be modest technical challenges to be overcome that will add unknown cost elements such as modifications to vehicle fluid ports for robotic autonomous system compatibility and development of long power hoses.
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Hadas, Zdenek, Jan Smilek, and Ondrej Rubes. "Energy harvesting from passing train as source of energy for autonomous trackside objects." MATEC Web of Conferences 211 (2018): 05003. http://dx.doi.org/10.1051/matecconf/201821105003.

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This paper deals with an energy harvesting review and analysis of an ambient mechanical energy on a trackside during a passing of a train. Trains provide very high level of vibration and deformation which could be converted into useful electricity. Due to maintenance and safety reasons a rail trackside includes sensing systems and number of sensor nodes is increased for modern transportation. Recent development of modern communication and ultra-low power electronics allows to use energy harvesting systems as autonomous source of electrical energy for these trackside objects. Main aim of this paper is model-based design of proposed vibration energy harvesting systems inside sleeper and predict harvested power during the train passing. Measurements of passing train is used as input for simulation models and harvested power is calculated. This simulation of proposed energy harvesting device is very useful for future design.
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Hwang, Jong-Gyu, Sung-Yoon Chae, Byung-Hun Lee, and Rag-Gyo Jeong. "Design of Train Driving Control System for SITL-based Autonomous Train Control Simulator." Journal of Korean Institute of Information Technology 21, no. 11 (November 30, 2023): 71–79. http://dx.doi.org/10.14801/jkiit.2023.21.11.71.

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Kim, Kyung Min, and Suk-Joon Ko. "Path Search for Autonomous Train via Dial Algorithm." Journal of Korean Institute of Communications and Information Sciences 43, no. 4 (April 30, 2018): 775–83. http://dx.doi.org/10.7840/kics.2018.43.4.775.

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Lee, Dong-Jin, Ilmu Byun, and Rag-Gyo Jeong. "Integrated Antenna Design for Autonomous Train Control System." Journal of the Korean Society for Railway 27, no. 6 (June 30, 2024): 492–502. http://dx.doi.org/10.7782/jksr.2024.27.6.492.

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Kim, Hyunkun, Hyeongoo Pyeon, Jong Sool Park, Jin Young Hwang, and Sejoon Lim. "Autonomous Vehicle Fuel Economy Optimization with Deep Reinforcement Learning." Electronics 9, no. 11 (November 13, 2020): 1911. http://dx.doi.org/10.3390/electronics9111911.

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The ever-increasing number of vehicles on the road puts pressure on car manufacturers to make their car fuel-efficient. With autonomous vehicles, we can find new strategies to optimize fuels. We propose a reinforcement learning algorithm that trains deep neural networks to generate a fuel-efficient velocity profile for autonomous vehicles given road altitude information for the planned trip. Using a highly accurate industry-accepted fuel economy simulation program, we train our deep neural network model. We developed a technique for adapting the heterogeneous simulation program on top of an open-source deep learning framework, and reduced dimension of the problem output with suitable parameterization to train the neural network much faster. The learned model combined with reinforcement learning-based strategy generation effectively generated the velocity profile so that autonomous vehicles can follow to control itself in a fuel efficient way. We evaluate our algorithm’s performance using the fuel economy simulation program for various altitude profiles. We also demonstrate that our method can teach neural networks to generate useful strategies to increase fuel economy even on unseen roads. Our method improved fuel economy by 8% compared to a simple grid search approach.
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Jing, Chunhui, Haohong Dai, Xing Yao, Dandan Du, Kaidi Yu, Dongyu Yu, and Jinyi Zhi. "Influence of Multi-Modal Warning Interface on Takeover Efficiency of Autonomous High-Speed Train." International Journal of Environmental Research and Public Health 20, no. 1 (December 25, 2022): 322. http://dx.doi.org/10.3390/ijerph20010322.

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As a large-scale public transport mode, the driving safety of high-speed rail has a profound impact on public health. In this study, we determined the most efficient multi-modal warning interface for automatic driving of a high-speed train and put forward suggestions for optimization and improvement. Forty-eight participants were selected, and a simulated 350 km/h high-speed train driving experiment equipped with a multi-modal warning interface was carried out. Then, the parameters of eye movement and behavior were analyzed by independent sample Kruskal–Wallis test and one-way analysis of variance. The results showed that the current level 3 warning visual interface of a high-speed train had the most abundant warning graphic information, but it failed to increase the takeover efficiency of the driver. The visual interface of the level 2 warning was more likely to attract the attention of drivers than the visual interface of the level 1 warning, but it still needs to be optimized in terms of the relevance of and guidance between graphic–text elements. The multi-modal warning interface had a faster response efficiency than the single-modal warning interface. The auditory–visual multi-modal interface had the highest takeover efficiency and was suitable for the most urgent (level 3) high-speed train warning. The introduction of an auditory interface could increase the efficiency of a purely visual interface, but the introduction of a tactile interface did not improve the efficiency. These findings can be used as a basis for the interface design of automatic driving high-speed trains and help improve the active safety of automatic driving high-speed trains, which is of great significance to protect the health and safety of the public.
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Dissertations / Theses on the topic "Autonomous Train"

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Chelouati, Mohammed. "Contributions to safety assurance of autonomous trains." Electronic Thesis or Diss., Université Gustave Eiffel, 2024. http://www.theses.fr/2024UEFL2014.

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Le déploiement des trains autonomes soulève de nombreuses questions et défis, notamment ceux liés au niveau de sécurité visé, qui doit être globalement au moins équivalent à celui du système existant, ainsi que les moyens à mettre en œuvre pour l'atteindre. Conventionnellement, la mise en sécurité d'un système ferroviaire global ou d'un sous-système défini comprend une phase d'analyse des risques et une phase de maîtrise des situations dangereuses. Ainsi, pour tout système technique ferroviaire, qu'il soit classique, automatique ou autonome, un niveau de sécurité acceptable doit être assuré. Dans le contexte des trains autonomes, les défis liés à leur sécurité incluent les aspects émergents de l'intelligence artificielle, le transfert de tâches et de responsabilités du conducteur vers des systèmes décisionnels automatiques, ainsi que les aspects liés à l'autonomisation, tels que la transition entre les modes et la gestion des modes dégradés. La méthodologie de démonstration de sécurité des trains autonomes, doit ainsi prendre en compte les risques engendrés par l'ensemble de ces aspects. Autrement dit, elle doit définir l'ensemble les activités de sécurité (liées à l'introduction de l'autonomie et des Systèmes d'Intelligence Artificielle), complémentaires à la démonstration de sécurité conventionnelle. Dans ce cadre, l'objectif de cette thèse est de contribuer à l'élaboration d'une démarche d'assurance de sécurité pour les trains autonomes. Concrètement, cette thèse propose trois contributions principales. Premièrement, nous proposons une méthodologie globale de haut niveau pour la structuration et la présentation de l'argumentation de sécurité pour les trains autonomes. La méthodologie est basée sur une approche orientée objectifs de sécurité (goal-based safety) en utilisant le formalisme graphique GSN (Goal Structuring Notation). Ensuite, nous proposons une modélisation de la conscience de situation (situational awareness) d'un système de conduite autonome d'un train, intégrant le processus de l'analyse dynamique des risques ferroviaires. Ce modèle permettra au système de conduite autonome de percevoir, de comprendre, d'anticiper et de s'adapter à des situations inconnues dans son environnement tout en prenant des décisions sûres. Le modèle est illustré à travers un cas d'étude concernant la détection et l'évitement d'obstacles sur la voie ferroviaire. Dernièrement, nous élaborons une approche de prise de décision basée sur l'évaluation dynamique des risques. L'approche utilise le Processus Décisionnel de Markov Partiellement Observable (POMDP) et vise à assurer une surveillance continue de l'environnement pour garantir la sécurité opérationnelle, en particulier la prévention des collisions. L'approche repose sur le maintien d'un niveau de risque acceptable grâce à une estimation et une actualisation continues de l'état opérationnel du train et des données de perception de l'environnement
The deployment of autonomous trains raises many questions and challenges, particularly concerning the required safety level, which must be globally at least equivalent to that of the existing systems, along with how to achieve it. Conventionally, ensuring the safety of a global railway system or a defined subsystem includes analyzing risks and effectively handling dangerous situations. Therefore, for any technical railway system, whether it is conventional, automatic, or autonomous, an acceptable level of safety must be ensured. In the context of autonomous trains, safety challenges include aspects related to the use of artificial intelligence models, the transfer of tasks and responsibilities from the driver to automatic decision-making systems, and issues related to autonomy, such as mode transitions and management of degraded modes. Thus, the safety demonstration methodology for autonomous trains must take into account the risks generated by all these aspects. In other words, it must define all the safety activities (related to the introduction of autonomy and artificial intelligence systems), complementary to conventional safety demonstration. In this context, this dissertation proposes three main contributions towards the development of a safety assurance methodology for autonomous trains. Firstly, we establish a high-level framework for structuring and presenting safety arguments for autonomous trains. This framework is based on a goal-based approach represented by the graphical modeling Goal Structuring Notation (GSN). Then, we propose a model for the situational awareness of the automated driving system of an autonomous train, that integrating the process of dynamic risk assessment. This model enables the automated driving system to perceive, understand, anticipate and adapt its behavior to unknown situations while making safe decisions. This model is illustrated through a case study related to the obstacle detection and avoidance. Finally, we develop a decision-making approach based on dynamic risk assessment. The approach is based on Partially Observable Markov Decision Processes (POMDP) and aims to ensure continuous environmental monitoring to guarantee operational safety, particularly collision prevention. The approach is based on maintaining an acceptable level of risk through continuous estimation and updating of the train's operational state and environmental perception data
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Wedberg, Magnus. "Detecting Rails in Images from a Train-Mounted Thermal Camera Using a Convolutional Neural Network." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138523.

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Now and then train accidents occur. Collisions between trains and objects such as animals, humans, cars, and fallen trees can result in casualties, severe damage on the train, and delays in the train traffic. Thus, train collisions are a considerable problem with consequences affecting society substantially. The company Termisk Systemteknik AB has on commission by Rindi Solutions AB investigated the possibility to detect anomalies on the railway using a trainmounted thermal imaging camera. Rails are also detected in order to determine if an anomaly is on the rail or not. However, the rail detection method does not work satisfactory at long range. The purpose of this master’s thesis is to improve the previous rail detector at long range by using machine learning, and in particular deep learning and a convolutional neural network. Of interest is also to investigate if there are any advantages using cross-modal transfer learning. A labelled dataset for training and testing was produced manually. Also, a loss function tailored to the particular problem at hand was constructed. The loss function was used both for improving the system during training and evaluate the system’s performance during testing. Finally, eight different approaches were evaluated, each one resulting in a different rail detector. Several of the rail detectors, and in particular all the rail detectors using crossmodal transfer learning, perform better than the previous rail detector. Thus, the new rail detectors show great potential to the rail detection problem.
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Boussik, Amine. "Apprentissage profond non-supervisé : Application à la détection de situations anormales dans l’environnement du train autonome." Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2023. http://www.theses.fr/2023UPHF0040.

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La thèse aborde les défis du monitoring de l’environnement et de détection des anomalies, notamment des obstacles, pour un train de fret autonome. Bien que traditionnellement, les transports ferroviaires étaient sous la supervision humaine, les trains autonomes offrent des perspectives d’avantages en termes de coûts, de temps et de sécurité. Néanmoins, leur exploitation dans des environnements complexes pose d’importants enjeux de sûreté. Au lieu d’une approche supervisée nécessitant des données annotées onéreuses et limitées, cette recherche adopte une technique non supervisée, utilisant des données non étiquetées pour détecter les anomalies en s’appuyant sur des techniques capables d’identifier les comportements atypiques.Deux modèles de surveillance environnementale sont présentés : le premier, basé sur un autoencodeur convolutionnel (CAE), est dédié à l’identification d’obstacles sur la voie principale; le second, une version avancée incorporant le transformeur de vision (ViT), se concentre sur la surveillance générale de l’environnement. Tous deux exploitent des techniques d’apprentissage non supervisé pour la détection d’anomalies.Les résultats montrent que la méthode mise en avant apporte des éléments pertinents pour le monitoring de l’environnement du train de fret autonome, ayant un potentiel pour renforcer sa fiabilité et sécurité. L’utilisation de techniques non supervisées démontre ainsi l’utilité et la pertinence de leur adoption dans un contexte d’application pour le train autonome
The thesis addresses the challenges of monitoring the environment and detecting anomalies, especially obstacles, for an autonomous freight train. Although traditionally, rail transport was under human supervision, autonomous trains offer potential advantages in terms of costs, time, and safety. However, their operation in complex environments poses significant safety concerns. Instead of a supervised approach that requires costly and limited annotated data, this research adopts an unsupervised technique, using unlabeled data to detect anomalies based on methods capable of identifying atypical behaviors.Two environmental surveillance models are presented : the first, based on a convolutional autoencoder (CAE), is dedicated to identifying obstacles on the main track; the second, an advanced version incorporating the vision transformer (ViT), focuses on overall environmental surveillance. Both employ unsupervised learning techniques for anomaly detection.The results show that the highlighted method offers relevant insights for monitoring the environment of the autonomous freight train, holding potential to enhance its reliability and safety. The use of unsupervised techniques thus showcases the utility and relevance of their adoption in an application context for the autonomous train
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Bouchama, Hiba Fawzia. "Synthèse d’observateurs continus-discrets pour les systèmes non linéaires : Application au Train Autonome." Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2024. http://www.theses.fr/2024UPHF0005.

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Ce travail de thèse contribue au projet collaboratif "Train de Fret Autonome'' porté par la SNCF et a pour but d’automatiser la conduite du train de Fret afin de garantir une conduite autonome fiable et sécurisée dans toutes conditions environnementales. Dans ce contexte, nos contributions concernent le développement d’estimateurs permettant de reconstruire avec précision la position et la vitesse longitudinale du train dans des conditions variables d’adhérence roue-rail. La difficulté majeure provient du fait que les capteurs odométriques embarqués fournissent une mesure de la rotation des roues au niveau des essieux mais ne détectent pas directement le phénomène de glissement des roues, ce qui entraîne une grande imprécision au niveau de l’estimation de la vitesse longitudinale du train. Pour faire face à ce problème, il est nécessaire de faire un recalage précis en utilisant la position du train mesurée par des radio-balises installées sur le rail. Néanmoins, cette mesure est discrète avec une période d’échantillonnage variable. L’un des challenges est de considérer les mesures du train qui combinent à la fois des mesures considérées continues et des mesures apériodiquement échantillonnées. Ainsi, la principale contribution théorique de cette thèse est la conception d’un observateur continu-discret pour une classe de systèmes multi-entrées/multi-sorties avec des sorties continues entachées de bruits de mesures et des sorties apériodiquement échantillonnées. Cet observateur est conçu pour répondre au cahier de charge du projet ``Train de Fret Autonome'' afin d’estimer la vitesse du train dans des conditions variables d’adhérence. Les performances de cet observateur sont montrées en simulation et comparées avec d’autres approches d’estimation de la vitesse du train puis ensuite validées expérimentalement via une campagne d’essais réalisée au Centre d’Essai Ferroviaire de Tronville-en-Barrois
This thesis contributes to the collaborative project "Train de Fret Autonome'' led by the SNCF and aims to control autonomous freight trains in order to guarantee reliable and safe autonomous driving in all environmental conditions. In this context, our contributions concern the development of estimators for accurately reconstructing the train position and longitudinal speed under variable wheel-rail adhesion conditions. The major difficulty arises from the fact that on-board odometric sensors provide a measurement of wheel rotation at axle level, but do not directly detect the phenomenon of wheel slippage, resulting in inaccurate estimation of the longitudinal speed of the train. To overcome this problem, it is necessary to make a precise recalibration using the position of the train measured by radio beacons installed on the rail. Nevertheless, this measurement is discrete with a variable sampling period. One of the challenges is to consider train measurements that combine both continuous and aperiodically sampled measurements. Thus, the main theoretical contribution of this thesis is the design of a continuous-discrete observer for a class of multi-input/multi-output systems with continuous noisy outputs and aperiodically sampled outputs. This observer is designed to meet the specifications of the "Autonomous Freight Train" project, in order to estimate train speed under variable adhesion conditions. The performance of this observer is shown in simulation and compared with other approaches to train speed estimation, then validated experimentally via an experimental test program carried out at the Centre d'Essai Ferroviaire of Tronville-en-Barrois
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Mosskull, Albin, and Arfvidsson Kaj Munhoz. "Solving the Hamilton-Jacobi-Bellman Equation for Route Planning Problems Using Tensor Decomposition." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289326.

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Optimizing routes for multiple autonomous vehiclesin complex traffic situations can lead to improved efficiency intraffic. Attempting to solve these optimization problems centrally,i.e. for all vehicles involved, often lead to algorithms that exhibitthe curse of dimensionality: that is, the computation time andmemory needed scale exponentially with the number of vehiclesresulting in infeasible calculations for moderate number ofvehicles. However, using a numerical framework called tensordecomposition one can calculate and store solutions for theseproblems in a more manageable way. In this project, we investi-gate different tensor decomposition methods and correspondingalgorithms for solving optimal control problems, by evaluatingtheir accuracy for a known solution. We also formulate complextraffic situations as optimal control problems and solve them.We do this by using the best tensor decomposition and carefullyadjusting different cost parameters. From these results it canbe concluded that the Sequential Alternating Least Squaresalgorithm used with canonical tensor decomposition performedthe best. By asserting a smooth cost function one can solve certainscenarios and acquire satisfactory solutions, but it requiresextensive testing to achieve such results, since numerical errorsoften can occur as a result of an ill-formed problem.
Att optimera färdvägen för flertalet au-tonoma fordon i komplexa trafiksituationer kan leda till effekti-vare trafik. Om man försöker lösa dessa optimeringsproblemcentralt, för alla fordon samtidigt, leder det ofta till algorit-mer som uppvisar The curse of dimensionality, vilket är då beräkningstiden och minnes-användandet växer exponentielltmed antalet fordon. Detta gör många problem olösbara för endasten måttlig mängd fordon. Däremot kan sådana problem hanterasgenom numeriska verktyg så som tensornedbrytning. I det här projektet undersöker vi olika metoder för tensornedbrytningoch motsvarandes algoritmer för att lösa optimala styrproblem,genom att jämföra dessa för ett problem med en känd lösning.Dessutom formulerar vi komplexa trafiksituationer som optimalastyrproblem för att sedan lösa dem. Detta gör vi genom attanvända den bästa tensornedbrytningen och genom att noggrantanpassa kostnadsparametrar. Från dessa resultat framgår det att Sequential Alternating Least Squaresalgoritmen, tillsammans medkanonisk tensornedbrytning, överträffade de andra algoritmersom testades. De komplexa trafiksituationerna kan lösas genomatt ansätta släta kostnadsfunktioner, men det kräver omfattandetestning för att uppnå sådana resultat då numeriska fel lätt kan uppstå som ett resultat av dålig problemformulering.
Kandidatexjobb i elektroteknik 2020, KTH, Stockholm
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Fagerström, Malin. "Autonomous Sensory Meridian Response and State-Trait Anxiety in Adults." Thesis, Umeå universitet, Institutionen för psykologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184030.

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Autonomous Sensory Meridian Response (ASMR) is a rapidly emerging but understudied sensory concept which according to earlier studies can help relieve symptoms of for exampledepression, anxiety, pain and stress while creating feelings of relaxation. The experience begins with a triggering audio or audio-visual stimulus which causes a physical reaction described as a tingling sensation beginning at the back of the head and further towards the periphery of the body. A previous study suggested that ASMR and neuroticism are related. Anxiety is a subfacet of neuroticism, which is why this study explored the relationship between State- and Trait-anxiety (S- and T-Anxiety) and ASMR to investigate if and in what way they are related. The research questions were “Is the level of State and Trait Anxiety associated with the level of ASMR experience?” and “Are there certain ASMR stimuli that are stronger related to State and Trait Anxiety than other ASMR stimuli?”. A total of 35 participants completed the questionnaires, of which the majority were between the ages 25-34, female, employed, coliving and answered that their highest level of education were studies at college/university. The results from the current self-report correlational study showed that ASMR and T-Anxiety are significantly negatively correlated, however, it failed to show any significant correlation between S-Anxiety and ASMR. Results also showed that one ASMR stimulus, finger flutters, significantly correlated negatively with T-Anxiety. The rest of the individual stimuli failed to show significant correlations with either S- or T-Anxiety. This suggests that anxiety may not be the driving sub-facet when searching for explanations for what makes ASMR and neuroticism associated. It also raises the question whether or not ASMR could be suitable as a therapeutic method for managing high T-Anxiety. Finally, it seems that individual ASMRstimulus vary in their connection to anxiety. However, it is only possible to draw conclusions on this sample, not the population, due to the small sample size. Further studies are needed to at least verify these results.
Autonomous Sensory Meridian Response (ASMR) är ett snabbt växande men understuderatsensoriskt koncept som enligt tidigare studier kan underlätta symptom av exempelvis depression, ångest, smärta och stress samtidigt som det skapar en avslappnande känsla. Upplevelsen börjar med ett triggande audio eller audiovisuellt stimuli som orsakar en fysisk reaktion beskrivet som en pirrig känsla med början vid bakhuvudet och vidare mot kroppens periferi. En studie om ämnet föreslog att ASMR och neuroticism är relaterade. Ångest är en del av neuroticism, varför den här studien undersöker relationen mellan ASMR och State- och Trait-Anxiety (S- och T-Anxiety) för att undersöka hur och på vilket sätt de är relaterade. Forskningsfrågorna var ”Är nivån av State och Trait Anxiety associerad med nivån av ASMRupplevelse?” och ”Finns det specifika ASMR stimuli som är starkare relaterade till State och Trait Anxiety än andra ASMR stimuli?”. Totalt slutförde 35 deltagare enkäterna, av vilka majoriteten var mellan åldrarna 25–34, kvinnor, anställda, sammanlevande och rapporterade att studier på universitet/högskola var deras högsta nivå av utbildning. Resultaten från den här självrapporterings-korrelationsstudien visade att ASMR och T-Anxiety är signifikant negativt korrelerade, men det kunde inte visas att S-Anxiety och ASMR är signifikant korrelerade. De visade också att ett ASMR stimuli, finger flutters, är signifikant negativt korrelerad med TAnxiety. Resterande individuella ASMR stimuli hade ingen signifikant korrelation med vare sig S- eller T-Anxiety. Det här tyder på att ångest kanske inte är den drivande underkategorin i jakt på förklaring till vad som gör ASMR och neuroticism associerade. Det väcker också frågan om ASMR verkligen hade varit en lämplig terapeutisk metod för hantering av hög T-Anxiety. Till sist verkar det som att individuella ASMR stimuli varierar i sin relation till ångest. Viktigt att tillägga är dock att det bara är möjligt att dra slutsatser om urvalet, inte populationen, på grund av storleken på urvalet. Ytterligare studier behövs för att åtminstone verifiera dessa resultat.
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Bouibed, Kamel. "Contribution à la gestion de défaillances d’un train de véhicules électriques légers autonomes." Thesis, Lille 1, 2010. http://www.theses.fr/2010LIL10030/document.

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Ce travail de thèse concerne la conception d'un système de supervision appliqué aux véhicules tout électriques autonomes à quatre roues motrices. Deux méthodes de surveillance à base de modèle sont développées en utilisant le modèle non linéaire du véhicule électrique: La première est basée sur La technique de multi observateurs pour détecter et isoler les défauts. La deuxième approche est la génération des relations de redondance analytique non linéaires (espace de parité non linéaire). En plus de la génération des résidus par la méthode de l'espace de parité, des observateurs différentiels à modes glissants sont intégrés pour l'estimation des dérivées successives des entrées et des sorties. Pour réaliser un train de trois véhicules, une commande longitudinale (commande de l'inter-distance) basée sur la mesure de l'écart inter véhiculaire est développée. La commande latérale est basée sur un suivi de trajectoire de référence qu'on impose pour tous les véhicules. Une commande de braquage est alors calculée en fonction de la différence entre la trajectoire mesurée et celle désirée. Enfin, quelques stratégies de reconfiguration sont développées pour le train de véhicules. Le principe de la reconfiguration est le choix de la stratégie à adopter pour le train de véhicules en fonction de type de défaut détecté
This work concerns the design of a supervision system applied to autonomous electric vehicle. Two based model monitoring methods are developed using the nonlinear model of electric vehicle: The first is based on multiple observers to detect and to isolate faults. The second approach is the generation of nonlinear analytical redundancy relations (nonlinear parity space). In addition to the generation of residuals by the method of parity space, differential sliding mode observers are integrated to estimate the successive derivatives of inputs and outputs. To make a train of three vehicles, a longitudinal control (control of the safety space) based on measuring the distance between vehicles is developed. The lateral control is based on a reference path tracking imposed for all vehicles. A steering command is then calculated based on the difference between the measured and the desired trajectory. Finally, some strategies are developed for the reconfiguration of the train of vehicles. The principle of the reconfiguration is the choice of strategy for the train of vehicles according to kind of detected fault
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Frenette, Patrick. "Architecture décisionnelle pour la conduite collaborative de véhicules autonomes." Mémoire, Université de Sherbrooke, 2010. http://savoirs.usherbrooke.ca/handle/11143/1548.

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L'automobile est un moyen de transport de prédilection puisqu'elle confère beaucoup de liberté aux utilisateurs. Cependant, les coûts sociaux et économiques reliés aux accidents de la route, ainsi que les émissions polluantes produites par la combustion des hydrocarbures, représentent une problématique à laquelle le Réseau de centres d'excellence AUTO21 s'intéresse. Notamment, AUTO21 finance ce projet qui porte sur les architectures décisionnelles appliquées aux trains de véhicules. Un train de véhicule est un système de transport intelligent regroupant un ensemble de véhicules qui se suivent les uns derrière les autres, conservant une faible distance entre eux.L'architecture DCD est une architecture décisionnelle complète avec communication bidirectionnelle responsable de la prise de décision distribuée d'un groupe de véhicules opérant au sein d'un train de véhicules.L'architecture réalise la plupart des manoeuvres réalisables dans les trains de véhicules tels l'insertion ou le retrait d'un véhicule dans le train, ainsi que la gestion des situations d'urgences telles les collisions et la défaillance de certains capteurs. La validation de l'architecture est effectuée avec un groupe de quatre robots mobiles équipés d'un système de positionnement relatif qui permet de localiser les véhicules les uns par rapport aux autres. Un ensemble de 18 scénarios de tests, couvrant un large éventail des situations susceptibles de survenir dans les trains de véhicules, est réalisé. Les résultats obtenus indiquent que la prise de décision des véhicules, ainsi que la coordination des véhicules via la communication sont robustes et permettent l'exécution des manoeuvres attendues.
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Armstrong, Lindsay Faye. "Thaw Slump Activity Via Close-range ‘Structure from Motion’ in Time-lapse Using Ground-based Autonomous Cameras." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/36885.

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Northwestern Arctic Canada is one of the most rapidly warming regions in the Arctic (Serreze et al., 2009). Retrogressive thaw slumps (RTS) are one of the most dramatic thermokarst features in permafrost terrain (Kokelj et al., 2013). Many studies have focused on describing the distribution of thermokarst landscapes (i.e., Olefeldt et al., 2016), as well as change in thermokarst terrain over the historical record (i.e., Kokelj and Jorgenson, 2013). However, improved high temporal and spatial resolution monitoring of thaw slump activity is required to enhance our understanding of factors governing their growth. Recent advances in aerial and ground-based Structure from Motion (SfM), a photogrammetry application, allow for temporal and spatial high-resolution characterization of landscape changes. This thesis explores two methods in SfM photogrammetry: 1) aerial imaging using an unmanned aerial vehicle (UAV) and 2) ground-based imaging using stationary multi-camera time-lapse installations, to derive high-resolution temporal and spatial data for change detection. A trend in mean elevation change was produced, and agrees with the RTS behaviour over the study period, which supports the viability of the proposed capture method. The lack of congruency in data range suggests need for further development in terms of analyses and differencing algorithms employed. The proposed method may be feasible for employment in other fields of science in which high temporal resolution change detection is desired. This proof of concept study was conducted at a small slump on the Peel Plateau, NWT, Canada, and aims to enhance understanding of the development and perpetuation of thaw slumps, to better anticipate landscape and ecosystem responses to future climate change.
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Poline, Marie. "Contribution aux méthodes de conception et de gestion des systèmes énergétiques multi-sources par optimisation systémique : application aux trains hybrides électrique autonomes." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT099/document.

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En France, il existe deux modes de traction pour les trains : la traction diesel ou la traction électrique. Chaque mode fait face à des problématiques qui lui sont propres. Dans le cas du diesel, les émissions de gaz à effet de serre étant de plus en plus contrôlées, il devient nécessaire de faire évoluer ce type de train vers une solution moins polluante. Dans le cas de la traction électrique, la consommation d’énergie entraine une chute de tension qui peut imposer un ralentissement des trains, empêchant ainsi le développement du trafic. La solution étudiée par la SNCF est l’hybridation des trains (ajout de systèmes de stockage en embarqué).Ces travaux de thèse ont pour objectif de mettre en place une méthode permettant de faire le pré-dimensionnement des systèmes de stockage embarqués dans le train. De plus, afin de tenir compte de l’influence réciproque de la gestion sur le dimensionnement, celle-ci est incluse dans le modèle de dimensionnement. La résolution du modèle global se fait à l’aide d’un algorithme d’optimisation.La méthode a été mise en place sur les deux modes de traction ferroviaire (diesel et électrique) et l’optimisation a été faite avec l’algorithme SQP (Sequential Quadratic Programming)
In France, there are two traction modes for railway: the diesel and electric traction. Each mode has its own issues. For diesel, the increasing control of the greenhouse gas emissions imposes to evolve this type of train to a less polluting solution. For electric traction, the energy consumption creates a voltage drop which can cause a traffic slowdown, which will limit the traffic development. The studied solution by SNCF is the hybridization of the train (adding storage system).Thus, these works have the objective to build a method to do the pre-sizing of storage systems embedded in trains. Moreover, to take into account the mutual influence of the sizing and the energy management, this last one is included in the sizing model. An optimization algorithm solves the global model.The method has been developed for the two traction modes (diesel and electric) and the optimization has been made with SQP algorithm (Sequential Quadratic Programming)
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Books on the topic "Autonomous Train"

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Hedin, Sven Anders. The trail of war: On the track of 'Big Horse' in Central Asia. London: Tauris Parke Paperbacks, 2009.

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Snibbe, Scott. How to Train a Happy Mind: A Skeptic's Path to Enlightenment. Watkins Media Limited, 2023.

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Lustgarten, Abrahm. China's Great Train: Beijing's Drive West and the Campaign to Remake Tibet. Holt & Company, Henry, 2009.

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Lustgarten, Abrahm. China's Great Train: Beijing's Drive West and the Campaign to Remake Tibet. St. Martin's Griffin, 2009.

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Wangui, Edna. Adaptation to Current and Future Climate in Pastoral Communities Across Africa. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.604.

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Pastoralists around the world are exposed to climate change and increasing climate variability. Various downscaled regional climate models in Africa support community reports of rising temperatures as well as changes in the seasonality of rainfall and drought. In addition to climate, pastoralists have faced a second exposure to unsupportive policy environments. Dating back to the colonial period, a lack of knowledge about pastoralism and a systemic marginalization of pastoral communities influenced the size and nature of government investments in pastoral lands. National governments prioritized farming communities and failed to pay adequate attention to drylands and pastoral communities. The limited government interventions that occurred were often inconsistent with contemporary realities of pastoralism and pastoral communities. These included attempts at sedentarization and modernization, and in other ways changing the priorities and practices of pastoral communities.The survival of pastoral communities in Africa in the context of this double exposure has been a focus for scholars, development practitioners, as well as national governments in recent years. Scholars initially drew attention to pastoralists’ drought-coping strategies, and later examined the multiple ways in which pastoralists manage risk and exploit unpredictability. It has been learned that pastoralists are rational land managers whose experience with variable climate has equipped them with the skills needed for adaptation. Pastoralists follow several identifiable adaptation paths, including diversification and modification of their herds and herding strategies; adoption of livelihood activities that did not previously play a permanent role; and a conscious decision to train the next generation for nonpastoral livelihoods. Ongoing government interventions around climate change still prioritize cropping over herding. Sometimes, such nationally supported adaptation plans can undermine community-based adaptation practices, autonomously evolving within pastoral communities. Successful adaptation hinges on recognition of the value of autonomous adaptation and careful integration of such adaptation with national plans.
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Sangeetha, V., and S. Kevin Andrews. Introduction to Artificial Intelligence and Neural Networks. Magestic Technology Solutions (P) Ltd, Chennai, Tamil Nadu, India, 2023. http://dx.doi.org/10.47716/mts/978-93-92090-24-0.

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Artificial Intelligence (AI) has emerged as a defining force in the current era, shaping the contours of technology and deeply permeating our everyday lives. From autonomous vehicles to predictive analytics and personalized recommendations, AI continues to revolutionize various facets of human existence, progressively becoming the invisible hand guiding our decisions. Simultaneously, its growing influence necessitates the need for a nuanced understanding of AI, thereby providing the impetus for this book, “Introduction to Artificial Intelligence and Neural Networks.” This book aims to equip its readers with a comprehensive understanding of AI and its subsets, machine learning and deep learning, with a particular emphasis on neural networks. It is designed for novices venturing into the field, as well as experienced learners who desire to solidify their knowledge base or delve deeper into advanced topics. In Chapter 1, we provide a thorough introduction to the world of AI, exploring its definition, historical trajectory, and categories. We delve into the applications of AI, and underscore the ethical implications associated with its proliferation. Chapter 2 introduces machine learning, elucidating its types and basic algorithms. We examine the practical applications of machine learning and delve into challenges such as overfitting, underfitting, and model validation. Deep learning and neural networks, an integral part of AI, form the crux of Chapter 3. We provide a lucid introduction to deep learning, describe the structure of neural networks, and explore forward and backward propagation. This chapter also delves into the specifics of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). In Chapter 4, we outline the steps to train neural networks, including data preprocessing, cost functions, gradient descent, and various optimizers. We also delve into regularization techniques and methods for evaluating a neural network model. Chapter 5 focuses on specialized topics in neural networks such as autoencoders, Generative Adversarial Networks (GANs), Long Short-Term Memory Networks (LSTMs), and Neural Architecture Search (NAS). In Chapter 6, we illustrate the practical applications of neural networks, examining their role in computer vision, natural language processing, predictive analytics, autonomous vehicles, and the healthcare industry. Chapter 7 gazes into the future of AI and neural networks. It discusses the current challenges in these fields, emerging trends, and future ethical considerations. It also examines the potential impacts of AI and neural networks on society. Finally, Chapter 8 concludes the book with a recap of key learnings, implications for readers, and resources for further study. This book aims not only to provide a robust theoretical foundation but also to kindle a sense of curiosity and excitement about the endless possibilities AI and neural networks offer. The journ
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Sullivan, Mark D. Seeking the Roots of Health and Action in Biological Autonomy. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780195386585.003.0010.

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The roots of biological autonomy and health are the same. Goals make biology distinct as a science, for without goals, we cannot understand why a biological trait exists. Organisms are autonomous biological entities because they define what is inside and what is outside themselves. This boundary between inner and outer gives the organism a self-referential purpose. Claude Bernard made experimental physiology possible with his concept of the internal environment, but he was unable to explain how the organism established the boundary between itself and its environment. Hence, homeostasis portrays the organism as reactive not active. Autopoiesis is an alternative defining characteristic of living beings. It generates biological autonomy through additional biological constraint on chemical processes, not through a special vital force. Healthy organisms can construct their own environmental niche. For humans, this niche is social and is constructed with a social physiology. Both exercise and education increase health by increasing capacity for niche construction.
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Scerri, Eric, and Grant Fisher, eds. Essays in the Philosophy of Chemistry. Oxford University Press, 2016. http://dx.doi.org/10.1093/oso/9780190494599.001.0001.

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The philosophy of chemistry has emerged in recent years as a new and autonomous field within the Anglo-American philosophical tradition. With the development of this new discipline, Eric Scerri and Grant Fisher's "Essays in the Philosophy of Chemistry" is a timely and definitive guide to all current thought in this field. This edited volume will serve to map out the distinctive features of the field and its connections to the philosophies of the natural sciences and general philosophy of science more broadly. It will be a reference for students and professional alike. Both the philosophy of chemistry and philosophies of scientific practice alike reflect the splitting of analytical and continental scholastic traditions, and some philosophers are turning for inspiration from the familiar resources of analytical philosophy to influences from the continental tradition and pragmatism. While philosophy of chemistry is practiced very much within the familiar analytical tradition, it is also capable of trail-blazing new philosophical approaches. In such a way, the seemingly disparate disciplines such as the "hard sciences" and philosophy become much more linked.
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Gephart, Werner; Witte, ed. The Sacred and the Law: The Durkheimian Legacy. Klostermann, 2017. http://dx.doi.org/10.5771/9783465142942.

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There is little doubt about the importance of Emile Durkheim’s work and the influence it had on the social sciences. His insights into the realms of normativity in particular remain an inspiring mine of information for theoretical reflection and empirical analyses. While his strengths, as we know nowadays, might not have always laid in systematic arguments, his main concerns have shaped the development of social thought in fundamental ways: the question of changing social bonds and the problem of integration; belief and unbelief in societal values; acceptance and rejection of the law, obligation and rights; inner tensions of normative orders; the problem of aligning the polymorphism of normativities with the polymorphic structures of society – and, hence, the project of normative and social pluralism. The Sacred occupies an important dual position in this context: marking an autonomous sphere of the Holy, endangered and upstaged by processes of modernization, and at the same time a fundamental trait of sociality, culture and normativity in general, thus providing the basis even still for modern, ‘secularized’ forms of collective beliefs. The current volume is comprised of contributions from a variety of disciplinary perspectives dealing with a wide range of topics in the realm of normativity in order to recall these important issues and demonstrate the influence and moment of Durkheim’s thinking on matters of the Sacred and the law.
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Book chapters on the topic "Autonomous Train"

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Peleska, Jan, Anne E. Haxthausen, and Thierry Lecomte. "Standardisation Considerations for Autonomous Train Control." In Lecture Notes in Computer Science, 286–307. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19762-8_22.

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AbstractIn this paper, we review software-based technologies already known to be, or expected to become essential for autonomous train control systems with grade of automation GoA 4 (unattended train operation) in existing open railway environments. It is discussed which types of technology can be developed and certified already today on the basis of existing railway standards. Other essential technologies, however, require modifications or extensions of existing standards, in order to provide a certification basis for introducing these technologies into non-experimental “real-world” rail operation. Regarding these, we check the novel pre-standard ANSI/UL 4600 with respect to suitability as a certification basis for safety-critical autonomous train control functions based on methods from artificial intelligence. As a thought experiment, we propose a novel autonomous train controller design and perform an evaluation according to ANSI/UL 4600. This results in the insight that autonomous freight trains and metro trains using this design could be evaluated and certified on the basis of ANSI/UL 4600 .
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Rey, Jeanne. "“Notice how you feel” and “train your brain”." In The Fabrication of the Autonomous Learner, 91–104. London: Routledge, 2023. http://dx.doi.org/10.4324/9781003379676-7.

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Hassoun, Melissa, Yassine Idel Mahjoub, and Damien Trentesaux. "Blockchain Adoption for Autonomous Train: Opportunities and Challenges." In Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future, 181–95. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-24291-5_15.

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Potena, Ciro, Daniele Nardi, and Alberto Pretto. "Fast and Accurate Crop and Weed Identification with Summarized Train Sets for Precision Agriculture." In Intelligent Autonomous Systems 14, 105–21. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48036-7_9.

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Gely, Corentin, Damien Trentesaux, and Antoine Le Mortellec. "Maintenance of the Autonomous Train: A Human-Machine Cooperation Framework." In Towards User-Centric Transport in Europe 2, 135–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38028-1_10.

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Bouibed, Kamel, Abdel Aitouche, and Mireille Bayart. "Modelling and Control of a Train of Autonomous Electric Vehicles." In Intelligent Robotics and Applications, 126–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10817-4_12.

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Mahtani, Ankur, Nadia Chouchani, Maxime Herbreteau, and Denis Rafin. "Enhancing Autonomous Train Safety Through A Priori-Map Based Perception." In Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification, 115–29. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05814-1_8.

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Mezzina, G., M. Barbareschi, Salavatore De Simone, Alessandro Di Benedetto, G. Narracci, C. L. Saragaglia, D. Serra, and Daniela De Venuto. "Smart On-Board Surveillance Module for Safe Autonomous Train Operations." In Lecture Notes in Electrical Engineering, 317–25. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95498-7_44.

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Kokare, Bapu Dada, Anil Kumar Gupta, and Sanjay A. Deokar. "Electric Power-Train Pre-fault Detection Using AI with IoT." In Internet of Vehicles and its Applications in Autonomous Driving, 173–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46335-9_11.

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Sebron, Walter, Elaheh Gol-Hashem, Peter Krebs, and Hans Tschürtz. "The Impact of Train Station Topologies on Operation of Autonomous People Movers." In Communications in Computer and Information Science, 223–37. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85521-5_15.

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Conference papers on the topic "Autonomous Train"

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Naidu, Harikumar, Harshita Chourasia, Praveen Kumar Mannepalli, and Pankaj Ramtekkar. "Advancing Train Safety Through Autonomous IoT based Obstacle Detection and Response." In 2024 International Conference on Innovations and Challenges in Emerging Technologies (ICICET), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/icicet59348.2024.10616334.

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Trentesaux, Damien, Rudy Dahyot, Abel Ouedraogo, Diego Arenas, Sebastien Lefebvre, Walter Schon, Benjamin Lussier, and Hugues Cheritel. "The Autonomous Train." In 2018 13th Annual Conference on System of Systems Engineering (SoSE). IEEE, 2018. http://dx.doi.org/10.1109/sysose.2018.8428771.

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Matsumoto, Masayuki, and Naohisa Kitamura. "Autonomous decentralized train control technology." In 2009 International Symposium on Autonomous Decentralized Systems (ISADS). IEEE, 2009. http://dx.doi.org/10.1109/isads.2009.5207322.

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Chouchani, Nadia, and Sana Debbech. "ATMO: Autonomous Train Map Ontology." In 11th International Conference on Model-Based Software and Systems Engineering. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0011893200003402.

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Yuan, Lei, Weihui Zhao, Chenling Li, and Datian Zhou. "Error correction method for train speed measurement using Doppler radar in train control system." In 2013 IEEE Eleventh International Symposium on Autonomous Decentralized Systems (ISADS). IEEE, 2013. http://dx.doi.org/10.1109/isads.2013.6513429.

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Li, Lulu, Haifeng Song, Jianjun Ma, and Hairong Dong. "Description and Analysis of Train-centric Communication based Autonomous Train Control System." In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2022. http://dx.doi.org/10.1109/itsc55140.2022.9922576.

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Mahtani, Ankur, Wael Ben-Messaoud, Abdelmalik Taleb-Ahmed, Smail Niar, and Clement Strauss. "Pedestrian Detection and Classification for Autonomous Train." In 2020 IEEE 4th International Conference on Image Processing, Applications and Systems (IPAS). IEEE, 2020. http://dx.doi.org/10.1109/ipas50080.2020.9334938.

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Ishida, Y. "The future of high-speed train." In Proceedings. ISADS 2005. 2005 International Symposium on Autonomous Decentralized Systems. IEEE, 2005. http://dx.doi.org/10.1109/isads.2005.1452101.

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Deng, Zixing, Haifeng Song, Hua Huang, Yidong Li, and Hairong Dong. "Multi-sensor based Train Localization and Data Fusion in Autonomous Train Control System." In 2020 Chinese Automation Congress (CAC). IEEE, 2020. http://dx.doi.org/10.1109/cac51589.2020.9327825.

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Hu, Shunding, Hongquan Lin, Xiaohong Lu, and Shengmao Xie. "Interoperability Technology Research of Train Autonomous Circumambulate System." In 2022 IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE). IEEE, 2022. http://dx.doi.org/10.1109/icite56321.2022.10101387.

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Reports on the topic "Autonomous Train"

1

Wang, Shenlong, and David Forsyth. Safely Test Autonomous Vehicles with Augmented Reality. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-015.

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Abstract:
This work exploits augmented reality to safely train and validate autonomous vehicles’ performance in the real world under safety-critical scenarios. Toward this goal, we first develop algorithms that create virtual traffic participants with risky behaviors and seamlessly insert the virtual events into real images perceived from the physical world. The resulting composed images are photorealistic and physically grounded. The manipulated images are fed into the autonomous vehicle during testing, allowing the self-driving vehicle to react to such virtual events within either a photorealistic simulator or a real-world test track and real hardware systems. Our presented technique allows us to develop safe, hardware-in-the-loop, and cost-effective tests for self-driving cars to respond to immersive safety-critical traffic scenarios.
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