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Journal articles on the topic 'Autonomous Train'

Author: Grafiati

Published: 4 May 2024

Last updated: 14 September 2024

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1

Guo, Yichen. "Design and research of train-centric autonomous control CBTC system." Applied and Computational Engineering 12, no. 1 (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

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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 th

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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 (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 (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

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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 p

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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 (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 (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 (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 (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 op

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Jing, Chunhui, Haohong Dai, Xing Yao, et al. "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 (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 vari

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Chai, Ming, Haoxiang Su, and Hongjie Liu. "Long Short-Term Memory-Based Model Predictive Control for Virtual Coupling in Railways." Wireless Communications and Mobile Computing 2022 (February 3, 2022): 1–17. http://dx.doi.org/10.1155/2022/1859709.

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The increasing need for capacity has led the railway industry to explore new train control systems based on a concept called virtual coupling. Inspired by the platooning of autonomous vehicles, the safe operation of virtual coupling is guaranteed by a relative brake distance-based train separation method. This paper proposes a novel long short-term memory (LSTM)-based model predictive control (MPC) method for train operations. An MPC-based control design for virtual coupled train operations is presented. The LSTM is introduced to model the dynamics of the preceding train to approximate the act

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Zhou, Yonghua, Zhenlin Zhang, and Deng Liu. "Analysis of train movement dynamics under various temporal–spatial constraints in fixed-block railway network using extended cellular automaton model." Modern Physics Letters B 28, no. 08 (2014): 1450060. http://dx.doi.org/10.1142/s0217984914500602.

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In the fixed-block railway traffic, the trains adjust their speeds in view of their preceding allowable spaces caused by their respective front adjacent trains or specified by scheduling commands. The railway lines have the line-type speed limits within some block sections and the point-type ones at the terminals of block sections. Those speed limits originate from line conditions, scheduling commands and indications of signal equipment. This paper attempts to in detail reveal the train movement mechanism synthetically considering those temporal–spatial constraints. The proposed train movement

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Hao, Yang, Tao Tang, and Chunhai Gao. "Train Distance Estimation in Turnout Area Based on Monocular Vision." Sensors 23, no. 21 (2023): 8778. http://dx.doi.org/10.3390/s23218778.

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Train distance estimation in a turnout area is an important task for the autonomous driving of urban railway transit, since this function can assist trains in sensing the positions of other trains within the turnout area and prevent potential collision accidents. However, because of large incident angles on object surfaces and far distances, Lidar or stereo vision cannot provide satisfactory precision for such scenarios. In this paper, we propose a method for train distance estimation in a turnout area based on monocular vision: firstly, the side windows of trains in turnout areas are detected

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Al-Khafaji, Israa M. Abdalameer, and A. V. Panov. "FEDERATED LEARNING FOR VISION-BASED OBSTACLE AVOIDANCE IN MOBILE ROBOTS." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 23, no. 3 (2023): 35–47. http://dx.doi.org/10.14529/ctcr230304.

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Federated learning (FL) is a machine learning approach that allows multiple devices or systems to train a model collaboratively, without exchanging their data. This is particularly useful for autonomous mobile robots, as it allows them to train models customized to their specific environment and tasks, while keeping the data they collect private. Research Objective to train a model to recognize and classify different types of objects, or to navigate around obstacles in its environment. Materials and me¬thods we used FL to train models for a variety of tasks, such as object recognition, obstacl

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Bouibed, Kamel, Abdel Aitouche, and Mireille Bayart. "Control and Reconguration of Train of Autonomous Electric Vehicles." Journal of Asian Electric Vehicles 10, no. 1 (2012): 1543–51. http://dx.doi.org/10.4130/jaev.10.1543.

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Mahtani, Ankur, Eddy Doba, and Nadia Ammad. "The Autonomous Train vision: Embedded AI for pedestrians monitoring." Transportation Research Procedia 72 (2023): 949–56. http://dx.doi.org/10.1016/j.trpro.2023.11.522.

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Gao, Yupeng. "Research on the autonomous train control system based on vehicle-to-vehicle communication." Applied and Computational Engineering 6, no. 1 (2023): 1495–502. http://dx.doi.org/10.54254/2755-2721/6/20230971.

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In recent years, there has been a significant increase in the importance of rail transit, which is largely due to the development of cities. It is anticipated that a new generation of train control systems will be required as the number of passengers increases and track resources become more limited. Seven driving modes of the autonomous train control system based on vehicle-to-vehicle communication are studied in four aspects: system architecture, control method, driving mode conversion, and system safety analysis. By analyzing the correlation between each operating mode in the normal and abn

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Wang, Shen, Thomas Weber, and Dieter Schramm. "Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario." Future Transportation 3, no. 1 (2022): 38–56. http://dx.doi.org/10.3390/futuretransp3010003.

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Trams are a meaningful means of public transport in urban traffic. However, trams have some well-known disadvantages. These include, for example, possibly long distances to the stop, long waiting times, and lack of privacy, among others. The innovative mobility concept “FLAIT-Train” offers solutions to the problems mentioned. The FLAIT-train operates on ordinary roads and is intended to offer DOOR-2-DOOR transport. In the first application phase, the FLAIT-train runs on exclusive lanes but in the future can mix with other traffic. They are designed as vehicles with 2 seats and 1 m width. The v

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García Cuenca, Laura, Enrique Puertas, Javier Fernandez Andrés, and Nourdine Aliane. "Autonomous Driving in Roundabout Maneuvers Using Reinforcement Learning with Q-Learning." Electronics 8, no. 12 (2019): 1536. http://dx.doi.org/10.3390/electronics8121536.

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Navigating roundabouts is a complex driving scenario for both manual and autonomous vehicles. This paper proposes an approach based on the use of the Q-learning algorithm to train an autonomous vehicle agent to learn how to appropriately navigate roundabouts. The proposed learning algorithm is implemented using the CARLA simulation environment. Several simulations are performed to train the algorithm in two scenarios: navigating a roundabout with and without surrounding traffic. The results illustrate that the Q-learning-algorithm-based vehicle agent is able to learn smooth and efficient drivi

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Gantumur, B., V. A. Prechissky, M. A. Sleptsov, and A. A. Barat. "ON THE EFFICIENCY OF USING AUTONOMOUS LOCOMOTIVES ON THE RAILWAYS OF MONGOLIA." World of Transport and Transportation 15, no. 1 (2017): 100–110. http://dx.doi.org/10.30932/1992-3252-2017-15-1-9.

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[For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version)].ABSTRACT The requirements of speed, reliability, safety and cost-effectiveness of cargo transportation pose a number of complex logistics tasks for Ulaanbaatar Railroad (UBZhD), including the choice of optimal train mass, series and number of locomotive sections for driving a freight train of a given weight. The mass of the train selected in the course of the study was checked by the condition of starting from the place on the calculated ascent. Based on the analys

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Neto, João Batista Pinto, Lucas de Carvalho Gomes, Miguel Elias Mitre Campista, and Luís Henrique Maciel Kosmalski Costa. "An Accurate GNSS-Based Redundant Safe Braking System for Urban Elevated Rail Maglev Trains." Information 11, no. 11 (2020): 531. http://dx.doi.org/10.3390/info11110531.

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The association of elevated rail structures and Maglev (magnetic levitation) trains is a promising alternative for urban transportation. Besides being cost-effective in comparison with underground solutions, the Maglev technology is a clean and low-noise mass transportation. In this paper, we propose a low-cost automatic braking system for Maglev trains. There is a myriad of sensors and positioning techniques used to improve the accuracy, precision and stability of train navigation systems, but most of them result in high implementation costs. In this paper, we develop an affordable solution,

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Kwak, Ho-Chan, Ji Young Song, Kyung-Min Kim, and Suk Mun Oh. "Dynamic Route Control Algorithm based on Autonomous Train Control System." Journal of the Korean Society for Railway 24, no. 9 (2021): 793–801. http://dx.doi.org/10.7782/jksr.2021.24.9.793.

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Weichselbaum, Johann, Christian Zinner, Oliver Gebauer, and Wolfgang Pree. "Accurate 3D-vision-based obstacle detection for an autonomous train." Computers in Industry 64, no. 9 (2013): 1209–20. http://dx.doi.org/10.1016/j.compind.2013.03.015.

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Wang, Shen, Thomas Weber, Dieter Schramm, and Thorben Berns. "Simulation-Based Investigation of On-Demand Vehicle Deployment for Night Bus Routes Using the Monte Carlo Method." Future Transportation 4, no. 2 (2024): 380–408. http://dx.doi.org/10.3390/futuretransp4020019.

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Public transportation systems, including trams and buses, play a crucial role in urban traffic. However, these traditional modes of transport have some well-known drawbacks, such as long distances between stops, lengthy waiting times, and a lack of privacy. In response to these challenges, an innovative mobility concept called “FLAIT-train” offers potential solutions. The FLAIT-train operates on regular roads and aims to provide DOOR-2-DOOR transport, addressing the issues associated with fixed stops and offering increased accessibility and convenience. In its initial phase, the FLAIT-train op

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Arshintsev, Dmitriy, Sergey Tolmachev, and Alexander Brzhezovskiy. "The development of service conditions for special-purpose cars based on the results of full-scale tests." Proceedings of Petersburg Transport University, no. 3 (September 20, 2018): 455–62. http://dx.doi.org/10.20295/1815-588x-2018-3-455-462.

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Objective: To develop the conditions of special cargo railway cars, multi-axis container cars and railway non-autonomous multiple unit trains circulation for transportation of special-purpose goods on public railways of OAO “RZhD”. The speeds of such trains can be higher in comparison with the speeds established by the existing normative documents of JSC “Russian Railways” for cargo trains. Special-purpose cars in nominal loading mode circulate in a train set with a unit locomotive. Methods: The assessment of conditions of the special-purpose rolling stock circulation was carried out by the re

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Hou, Kaiwen, and George Giannopoulos. "Modeling the Deployment and Management of Large-Scale Autonomous Vehicle Circulation in Mixed Road Traffic Conditions Considering Virtual Track Theory." Future Transportation 4, no. 1 (2024): 215–35. http://dx.doi.org/10.3390/futuretransp4010011.

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This paper offers a novel view for managing and controlling the movement of driverless, i.e., autonomous, vehicles by converting this movement to a simulated train movement moving on a rail track. It expands on the “virtual track” theory and creates a model for virtual track autonomous vehicle management and control based on the ideas and methods of railway train operation. The developed model and adopted algorithm allow for large-scale autonomous driving vehicle control on the highway while considering the temporal-spatial distribution of vehicles, temporal-spatial trajectory diagram optimiza

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Oppelt, Maximilian P., Andreas Foltyn, Jessica Deuschel, et al. "ADABase: A Multimodal Dataset for Cognitive Load Estimation." Sensors 23, no. 1 (2022): 340. http://dx.doi.org/10.3390/s23010340.

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Driver monitoring systems play an important role in lower to mid-level autonomous vehicles. Our work focuses on the detection of cognitive load as a component of driver-state estimation to improve traffic safety. By inducing single and dual-task workloads of increasing intensity on 51 subjects, while continuously measuring signals from multiple modalities, based on physiological measurements such as ECG, EDA, EMG, PPG, respiration rate, skin temperature and eye tracker data, as well as behavioral measurements such as action units extracted from facial videos, performance metrics like reaction

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Heirich, Oliver, Benjamin Siebler, and Erik Hedberg. "Study of Train-Side Passive Magnetic Measurements with Applications to Train Localization." Journal of Sensors 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/8073982.

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Passive magnetic sensors measure the magnetic field density in three axes and are often integrated on a single chip. These low-cost sensors are widely used in car navigation as well as in battery powered navigation equipment such as smartphones as part of an electronic compass. We focus on a train localization application with multiple, exclusively onboard sensors and a track map. This approach is considered as a base technology for future railway applications such as collision avoidance systems or autonomous train driving. In this paper, we address the following question: how beneficial are p

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Singhal, Vivek, Divya Anand, Hani Moaiteq Aljahdali, Nitin Goyal, Aman Singh, and Seifedine Kadry. "An Intelligent and Autonomous Sight Distance Evaluation Framework for Sustainable Transportation." Sustainability 13, no. 16 (2021): 8885. http://dx.doi.org/10.3390/su13168885.

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Railways are facing a serious problem of road vehicle–train collisions at unmanned railway level crossings. The purpose of the study is the development of a safe stopping sight distance and sight distance from road to rail track model with appropriate computation and analysis. The scope of the study lies in avoiding road vehicle–train collisions at unmanned railway level crossings. An intelligent and autonomous framework is being developed using supervised machine learning regression algorithms. Further, a sight distance from road to rail track model is being developed for road vehicles of 0.5

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Zanelli, Federico, Marco Mauri, Francesco Castelli-Dezza, Edoardo Sabbioni, Davide Tarsitano, and Nicola Debattisti. "Energy Autonomous Wireless Sensor Nodes for Freight Train Braking Systems Monitoring." Sensors 22, no. 5 (2022): 1876. http://dx.doi.org/10.3390/s22051876.

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Nowadays, railway freight transportation is becoming more and more crucial since it represents the best alternative to road transport in terms of sustainability, pollution, and impact on the environment and on public health. Upgrading the potentiality of this kind of transportation, it would be possible to avoid delays in goods deliveries due to road accidents, traffic jams, and other situation occurring on roads. A key factor in this framework is therefore represented by monitoring and maintenance of the train components. Implementing a real time monitoring of the main components and a predic

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Oh, Sehchan, and Young-Jong Cho. "Track Switching Algorithm for the T2T-Based Autonomous Train Control System." Journal of Korean Institute of Communications and Information Sciences 42, no. 11 (2017): 2160–69. http://dx.doi.org/10.7840/kics.2017.42.11.2160.

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Piccioni, Cristiana, Stefano Ricci, Arbra Bardhi, and Polis Karatzas. "Rail Vehicle Accessibility: Towards an Autonomous Train Usage for All Passengers." Transportation Research Procedia 72 (2023): 3260–67. http://dx.doi.org/10.1016/j.trpro.2023.11.863.

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Xie, Chun Lin. "Research on Applied Technology in Training Autonomous Abilities of Learners." Applied Mechanics and Materials 540 (April 2014): 556–59. http://dx.doi.org/10.4028/www.scientific.net/amm.540.556.

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This research aims at studying the effectiveness of applied technology in training learners’ autonomous learning abilities. Under the circumstance of networking, it is undoubted a new way to train autonomous abilities of learners with applied technology benefits the development of learners in future. Therefore, both instructors and learners have necessity to master and share some skills and strategies of autonomous learning by means of applied technology. It is also essential that learners enhance their abilities to manage their time and develop a positive attitude and a sense of responsibilit

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Wang, Wencong, Gang Li, Shuwei Liu, and Qiang Yang. "Trajectory Planning of a Semi-Trailer Train Based on Constrained Iterative LQR." Applied Sciences 13, no. 19 (2023): 10614. http://dx.doi.org/10.3390/app131910614.

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With the development of science and technology, self-driving technology is gradually being applied to automobile semi-trailer trains. Aiming at the problem that it is challenging to plan the traveling trajectory of an autonomous semi-trailer train, a trajectory planning algorithm based on a constrained iterative linear quadratic regulator is proposed. The constrained iterative linear quadratic regulator solves the problem that the iterative constrained linear quadratic regulator cannot deal with inequality constraints by transforming inequality constraints into interior point penalty functions

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Zhou, Yefang, Yanyan Li, Mingyang Hao, and Toshiyuki Yamamoto. "A System of Shared Autonomous Vehicles Combined with Park-And-Ride in Residential Areas." Sustainability 11, no. 11 (2019): 3113. http://dx.doi.org/10.3390/su11113113.

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As suburbanization and unprecedented population aging are converging, enhanced personal mobility for suburban residents is required. In this study, a collaborative scheme involving park-and-ride services associated with public transport and a shared autonomous vehicle system are proposed. Two residential areas in the Nagoya metropolitan region, Japan, are considered: a residential area at the outer edge of a subway line and a commuter town with a nearby railway station. Three user groups are assumed: park-and-ride commuters who park shared autonomous vehicles at the station and take the train

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Hadas, Zdenek, Ondrej Rubes, Filip Ksica, and Jan Chalupa. "Kinetic Electromagnetic Energy Harvester for Railway Applications—Development and Test with Wireless Sensor." Sensors 22, no. 3 (2022): 905. http://dx.doi.org/10.3390/s22030905.

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This paper deals with a development and lab testing of energy harvesting technology for autonomous sensing in railway applications. Moving trains are subjected to high levels of vibrations and rail deformations that could be converted via energy harvesting into useful electricity. Modern maintenance solutions of a rail trackside typically consist of a large number of integrated sensing systems, which greatly benefit from autonomous source of energy. Although the amount of energy provided by conventional energy harvesting devices is usually only around several milliwatts, it is sufficient as a

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Wang, Yang, Yihao Chen, Hao Yuan, and Cheng Wu. "An automated learning method of semantic segmentation for train autonomous driving environment understanding." International Journal of Advances in Intelligent Informatics 10, no. 1 (2024): 148. http://dx.doi.org/10.26555/ijain.v10i1.1521.

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One of the major reasons for the explosion of autonomous driving in recent years is the great development of computer vision. As one of the most fundamental and challenging problems in autonomous driving, environment understanding has been widely studied. It directly determines whether the entire in-vehicle system can effectively identify surrounding objects of vehicles and make correct path planning. Semantic segmentation is the most important means of environment understanding among the many image recognition algorithms used in autonomous driving. However, the success of semantic segmentatio

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Pfeiffer, Christian, Simon Wengeler, Antonio Loquercio, and Davide Scaramuzza. "Visual attention prediction improves performance of autonomous drone racing agents." PLOS ONE 17, no. 3 (2022): e0264471. http://dx.doi.org/10.1371/journal.pone.0264471.

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Humans race drones faster than neural networks trained for end-to-end autonomous flight. This may be related to the ability of human pilots to select task-relevant visual information effectively. This work investigates whether neural networks capable of imitating human eye gaze behavior and attention can improve neural networks’ performance for the challenging task of vision-based autonomous drone racing. We hypothesize that gaze-based attention prediction can be an efficient mechanism for visual information selection and decision making in a simulator-based drone racing task. We test this hyp

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Lu, Bo, Le Ru, Shiguang Hu, Wenfei Wang, Hailong Xi, and Xiaolin Zhao. "Research on Autonomous Manoeuvre Decision Making in Within-Visual-Range Aerial Two-Player Zero-Sum Games Based on Deep Reinforcement Learning." Mathematics 12, no. 14 (2024): 2160. http://dx.doi.org/10.3390/math12142160.

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In recent years, with the accelerated development of technology towards automation and intelligence, autonomous decision-making capabilities in unmanned systems are poised to play a crucial role in contemporary aerial two-player zero-sum games (TZSGs). Deep reinforcement learning (DRL) methods enable agents to make autonomous manoeuvring decisions. This paper focuses on current mainstream DRL algorithms based on fundamental tactical manoeuvres, selecting a typical aerial TZSG scenario—within visual range (WVR) combat. We model the key elements influencing the game using a Markov decision proce

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Kolmogorov, Aleksey, and Nadezhda Zaytseva. "AUTOMATIC COMPUTER LEARNING SYSTEM THE SIMULATOR." Modern Technologies and Scientific and Technological Progress 2024, no. 1 (2024): 140–41. http://dx.doi.org/10.36629/2686-9896-2024-1-140-141.

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One of the effective tools of a computer simulator is considered – an automatic training system (AOS) designed to train operators of technological installations on a simulator in an autonomous mode without the participation of an instructor

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Pan, Yunpeng, Ching-An Cheng, Kamil Saigol, et al. "Imitation learning for agile autonomous driving." International Journal of Robotics Research 39, no. 2-3 (2019): 286–302. http://dx.doi.org/10.1177/0278364919880273.

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We present an end-to-end imitation learning system for agile, off-road autonomous driving using only low-cost on-board sensors. By imitating a model predictive controller equipped with advanced sensors, we train a deep neural network control policy to map raw, high-dimensional observations to continuous steering and throttle commands. Compared with recent approaches to similar tasks, our method requires neither state estimation nor on-the-fly planning to navigate the vehicle. Our approach relies on, and experimentally validates, recent imitation learning theory. Empirically, we show that polic

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V S, Amar. "Autonomous Driving using CNN." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 3633–36. http://dx.doi.org/10.22214/ijraset.2021.35771.

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Human beings are currently addicted to automation and robotics technologies. The state-of-the-art in deep learning technologies and AI is the subject of this autonomous driving. Driving with automated driving systems promises to be safe, enjoyable, and efficient.. It is preferable to train in a virtual environment first and then move to a real-world one. Its goal is to enable a vehicle to recognise its surroundings and navigate without the need for human intervention. The raw pixels from a single front-facing camera were directly transferred to driving commands using a convolution neural netwo

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BAHOV, T. B., and S. A. VOROTNIKOV. "UTILIZATION OF SYNTHETIC DATA FOR SNOW PARTICLES FILTRATION IN A LIDAR POINT CLOUD." IZVESTIA VOLGOGRAD STATE TECHNICAL UNIVERSITY, no. 4(287) (April 2024): 20–26. http://dx.doi.org/10.35211/1990-5297-2024-4-287-20-26.

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The article discusses the use of synthetic data from the CARLA simulator to train an algorithm for snow filtration in a LIDAR point cloud used as the main sensor of a self-driving car or autonomous mobile outdoor robot.

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Pose, Sebastian, Stefan Reitmann, Gero Jörn Licht, Thomas Grab, and Tobias Fieback. "AI-Prepared Autonomous Freshwater Monitoring and Sea Ground Detection by an Autonomous Surface Vehicle." Remote Sensing 15, no. 3 (2023): 860. http://dx.doi.org/10.3390/rs15030860.

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Climate change poses special and new challenges to inland waters, requiring intensive monitoring. An application based on an autonomous operation swimming vehicle (ASV) is being developed that will provide simulations, spatially and depth-resolved water parameter monitoring, bathymetry detection, and respiration measurement. A clustered load system is integrated with a high-resolution sonar system and compared with underwater photogrammetry objects. Additionally, a holistic 3D survey of the water body above and below the water surface is generated. The collected data are used for a simulation

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Liu, Mingshuo, Shiyi Luo, Kevin Han, Ronald F. DeMara, and Yu Bai. "Autonomous Binarized Focal Loss Enhanced Model Compression Design Using Tensor Train Decomposition." Micromachines 13, no. 10 (2022): 1738. http://dx.doi.org/10.3390/mi13101738.

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Deep learning methods have exhibited the great capacity to process object detection tasks, offering a practical and viable approach in many applications. When researchers have advanced deep learning models to improve their performance, the model derived from the algorithmic improvement may itself require complementary increases in computational and power demands. Recently, model compression and pruning techniques have received more attention to promote the wide employment of the DNN model. Although these techniques have achieved a remarkable performance, the class imbalance issue during the mo

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Lee, Dong-Jin, and In-June Hwang. "Self-powered Senor System using RF energy for Autonomous Train Control System." Journal of the Korean Society for Railway 25, no. 1 (2022): 43–51. http://dx.doi.org/10.7782/jksr.2022.25.1.43.

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Oh, Sehchan, and Hyeon-Yeong Choi. "Protection Algorithm for Virtual Coupler in T2T-Based Autonomous Train Control System." Journal of Korean Institute of Communications and Information Sciences 43, no. 11 (2018): 1894–902. http://dx.doi.org/10.7840/kics.2018.43.11.1894.

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Theriault, James A., Craig Sheppard, Joey Hood, Hilary B. Moors-Murphy, and Matthew Coffin. "Counting odontocetes from click train detections using multiple independent autonomous acoustic sensors." Journal of the Acoustical Society of America 135, no. 4 (2014): 2241. http://dx.doi.org/10.1121/1.4877333.

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Suzuki, Tsuyoshi, Takashi Kawano, Yutaka Umehara, Yoshihide Nagatsugu, and Masayuki Matsumoto. "Assurance technology for the mode change of autonomous decentralised train control system." International Journal of Critical Computer-Based Systems 2, no. 2 (2011): 111. http://dx.doi.org/10.1504/ijccbs.2011.041255.

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Hwang, Jong-Gyu, Sung-Yoon Chae, Hyeon-Yeong Choi, and Rag-Gyo Jeong. "Design of SITL-based Simulator for Performance Analysis of Autonomous Train Control." TRANSACTION OF THE KOREAN INSTITUTE OF ELECTRICAL ENGINEERS P 71, no. 4 (2022): 203–9. http://dx.doi.org/10.5370/kieep.2022.71.4.203.

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