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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">mirtr</journal-id><journal-title-group><journal-title xml:lang="ru">Мир транспорта</journal-title><trans-title-group xml:lang="en"><trans-title>World of Transport and Transportation</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1992-3252</issn><publisher><publisher-name>Russian University of Transport (RUT)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.30932/1992-3252-2021-19-6-1</article-id><article-id custom-type="elpub" pub-id-type="custom">mirtr-2209</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ВОПРОСЫ ТЕОРИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>THEORY</subject></subj-group></article-categories><title-group><article-title>Погрешности измерения расстояния до препятствия средствами технического зрения и прогноза пути торможения в беспилотных системах управления движением поездов</article-title><trans-title-group xml:lang="en"><trans-title>Errors in Measuring the Distance to an Obstacle by Technical Vision Means and in Forecasting Braking Distance in Driverless Train Control Systems. World of Transport and Transportation</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Баранов</surname><given-names>Л. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Baranov</surname><given-names>L. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Баранов Леонид Аврамович – доктор технических наук, профессор, заведующий кафедрой управления и защиты информации</p><p>Москва</p></bio><bio xml:lang="en"><p>Baranov, Leonid A., D.Sc. (Eng), Professor, Head of the Department of Control and Protection of Information</p><p>Moscow</p></bio><email xlink:type="simple">Baranov.miit@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бестемьянов</surname><given-names>П. Ф.</given-names></name><name name-style="western" xml:lang="en"><surname>Bestemyanov</surname><given-names>P. F.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Бестемьянов Пётр Филимонович – доктор технических наук, профессор, директор Института транспортной техники и систем управления</p><p>Москва</p></bio><bio xml:lang="en"><p>Bestemyanov, Petr F., D.Sc. (Eng), Professor, Director of the Institute of Transport Vehicles and Control Systems</p><p>Moscow</p></bio><email xlink:type="simple">ilemsmiit@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Балакина</surname><given-names>Е. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Balakina</surname><given-names>E. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Балакина Екатерина Петровна – кандидат технических наук, доцент</p><p>Москва</p></bio><bio xml:lang="en"><p>Balakina, Ekaterina P., Ph.D. (Eng), Associate Professor</p><p>Moscow</p></bio><email xlink:type="simple">balakina_e@list.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Охотников</surname><given-names>А. Л.</given-names></name><name name-style="western" xml:lang="en"><surname>Okhotnikov</surname><given-names>A. L.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Охотников Андрей Леонидович – заместитель начальника Департамента – начальник Отдела стратегического развития</p><p>Москва</p></bio><bio xml:lang="en"><p>Okhotnikov, Andrey L., Deputy Head of the Department – Head of the Department of Strategic Planning</p><p>Moscow</p></bio><email xlink:type="simple">a.ohotnikov@vnias.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Российский университет транспорта</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian University of Transport</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Научно-исследовательский и проектно-конструкторский институт информатизации, автоматизации и связи на железнодорожном транспорте (АО «НИИАС»)</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Research and Design Institute of Railway Informatisation, Automation and Communications (JSC NIIAS)</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>28</day><month>12</month><year>2021</year></pub-date><volume>19</volume><issue>6</issue><fpage>6</fpage><lpage>12</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Баранов Л.А., Бестемьянов П.Ф., Балакина Е.П., Охотников А.Л., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Баранов Л.А., Бестемьянов П.Ф., Балакина Е.П., Охотников А.Л.</copyright-holder><copyright-holder xml:lang="en">Baranov L.A., Bestemyanov P.F., Balakina E.P., Okhotnikov A.L.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://mirtr.elpub.ru/jour/article/view/2209">https://mirtr.elpub.ru/jour/article/view/2209</self-uri><abstract><p>Системы технического зрения являются источниками информации о препятствии, оказавшемся на пути, при беспилотном управлении движением поездов. По полученной информации системой управления движением принимается решение о включении режима торможения с целью предотвращения наезда на препятствие.</p><p>В соответствии с международным и отечественным опытом и нормами необходимо обеспечить вероятность опасного отказа, в данном случае – вероятность наезда на препятствие, не более 10-8 при доверительной вероятности 0,95 по SIL-4 (ГОСТ-Р61508). Учитывая наличие погрешности измерения расстояния до препятствия системой технического зрения и погрешности расчёта тормозного пути, требуется определить координату точки начала торможения при обнаружении предмета на пути таким образом, чтобы обеспечить остановку поезда до препятствия с вероятностью, определяемой в соответствии с SIL-4.</p><p>Особенностью решаемой задачи оценки погрешностей измерения расстояния до препятствия и расчёта тормозного пути является необходимость определения оценок их максимальных величин и разработки алгоритма использования этих оценок таким образом, чтобы вероятность наезда не превышала нормированного значения.</p><p>Приведена методика определения максимальной величины погрешности измерения расстояния до места препятствия, вероятность превышения которой довольно мала (от 10-2 до 10-6). Предложен алгоритм многократных измерений расстояния до препятствия с выбором минимального результата измерений для принятия решения о начале торможения, обеспечивающий выполнение нормативного показателя вероятности столкновения поезда с препятствием согласно SIL-4. Разработана методика оценки погрешности расчёта тормозного пути, обеспечивающая совместно с алгоритмом многократных измерений системой технического зрения расстояния до препятствия, нормативный показатель согласно SIL-4. Показана необходимость функционирования второго канала технического зрения из-за наличия кривых в пути следования. Обоснована необходимость использования алгоритмов многократных измерений до препятствия по второму каналу, расположенному вне поезда. Отмечено, что описанные в данной статье способы выбора максимальных значений случайных погрешностей измерений и расчётов, превышение величин которых имеет весьма малую вероятность, могут быть использованы в различных прикладных задачах управления движением на транспорте.</p></abstract><trans-abstract xml:lang="en"><p>Technical vision systems are sources of information about an obstacle on the track in the case of driverless train control. Based on the information received, the traffic control system decides to turn on the braking mode to prevent a colliosni with an obstacle. In accordance with international and domestic expertise and standard ratings, it is necessary to ensure the probability of a dangerous failure, in this case, the probability of hitting an obstacle, not more than 10-8 with a confidence probability of 0,95 according to SIL-4 ([Russian state standard] GOST-R61508). Considering the presence of an error in measuring the distance to an obstacle by the technical vision system and an error in calculating the stopping distance, it is required to determine the coordinate of the braking start point when an object is detected on the track in such a way as to ensure that the train stops before the obstacle with a probability determined in accordance with SIL-4.</p><p>A feature of the problem being solved for estimating the errors in measuring the distance to an obstacle and calculating the stopping distance implies the need to determine the estimates of their maximum values and to develop an algorithm for using these estimates in such a way that the collision probability does not exceed the normalised value.</p><p>A technique is described for determining the maximum value of the error in measuring the distance to the obstacle, the probability of exceeding which is quite small (from 10-2 to 10-6). A proposed algorithm for multiple measurements of the distance to an obstacle allows choosing the minimum measurement result for deciding on the start of braking, which ensures meeting standard indicator of a probability of a train colliding with an obstacle according to SIL-4. A method for estimating the error in calculating the stopping distance has been developed, which, together with the algorithm of multiple measurements by the technical vision system of the distance to the obstacle, provides the standard indicator according to SIL-4. The need for the second channel of technical vision due to the presence of curves along the route is shown. The necessity of using algorithms for multiple measurements to an obstacle through the second channel located outside the train is also substantiated. It is noted that the methods described in this article for choosing the maximum values of random errors in measurements and calculations, the values of which can be exceeded with a very low probability, can be used to solve various applied problems of traffic control in transportation processes.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>транспорт</kwd><kwd>железнодорожный транспорт</kwd><kwd>техническое зрение</kwd><kwd>погрешность измерения расстояния до препятствия</kwd><kwd>беспилотные системы управления движением</kwd><kwd>расчёт тормозного пути</kwd><kwd>оценка погрешности</kwd></kwd-group><kwd-group xml:lang="en"><kwd>transport</kwd><kwd>technical vision</kwd><kwd>error in measuring the distance to an obstacle</kwd><kwd>autonomous traffic control systems</kwd><kwd>calculation of the stopping distance</kwd><kwd>error estimation</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено при финансовой поддержке РФФИ, НТУ «Сириус», ОАО «РЖД» и Образовательного Фонда «Талант и успех» в рамках научного проекта № 20-37-51001</funding-statement><funding-statement xml:lang="en">The study was financially supported by the Russian Foundation for Basic Research, NTU Sirius, JSC Russian Railways, and the Talent and Success Educational Foundation within the framework of research project No. 20-37-51001</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">. Matthies, Larry Obstacle Detection, 2014 In: Ikeuchi K (ed) Computer Vision Springer, Boston, MA DOI: 10 1007/978-0-387-31439-6_52</mixed-citation><mixed-citation xml:lang="en">Matthies, Larry Obstacle Detection, 2014 In: Ikeuchi, K (eds) Compouter Vision Springer, Boston, Ma DOI: 10 1007/978-0-387-31439-6_52</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">. Jain, R , Tamgade, P, Swaroopa, R , Bhure, P, Shahu, S ., Pote, R Simulation of Obstacle Detection of an Autonomous Car International Journal of Advanced Research in Science, Communication and Technology, 2021, pp 430−435 DOI: 10 48175/IJARSCT-1420</mixed-citation><mixed-citation xml:lang="en">Jain, R , Tamgade, P , Swaroopa, R , Bhure, P , Shahu, S , Pote, R Simulation of Obstacle Detection of an Autonomous Car International Journal of Advanced Research in Science, Communication and Technology, 2021, pp 430−435 DOI: 10 48175/IJARSCT-1420</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">. Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo Automatic Train Operation Using Autonomic Prediction of Train Runs IEEJ Transactions on Industry Applications, 2008, Vol 128, pp 1365-1372 DOI: 10 1541/ieejias 128 1365</mixed-citation><mixed-citation xml:lang="en">Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo Automatic Train Operation Using Autonomic Prediction of Train Runs IEEJ Transactions on Industry Applications, 2008, Vol 128, pp 1365–1372 DOI: 10 1541/ieejias 128 1365</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">. Chen Zhang; Xuewu Xu; Chen Fan; Guoping Wang Literature Review of Machine Vision in Application Field E3S Web of Conferences, 2021, Vol . 236, pp 04027 DOI: 202123604027</mixed-citation><mixed-citation xml:lang="en">Chen Zhang; Xuewu Xu; Chen Fan; Guoping Wang Literature Review of Machine Vision in Application Field E3S Web of Conferences, 2021, Vol 236, pp 04027 DOI: 202123604027</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">. Zhongfei Zhang, Weiss, R , Hanson, A R Obstacle detection based on qualitative and quantitative 3D reconstruction IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, Vol 19, pp 15−26 DOI: 10 1109/34 566807</mixed-citation><mixed-citation xml:lang="en">Zhongfei Zhang, Weiss, R , Hanson, A R Obstacle detection based on qualitative and quantitative 3D reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, Vol 19, pp 15−26 DOI: 10 1109/34 566807</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">. Feiden, D , Tetzlaff, R Cellular neural networks for motion estimation and obstacle detection Adv Radio Sci ., 2003, Vol 1, pp 143–147 DOI: https://doi org/10 5194/ars-1-143-2003</mixed-citation><mixed-citation xml:lang="en">Feiden, D , Tetzlaff, R Cellular neural networks for motion estimation and obstacle detection Advances in Radio Science, 2003, Vol 1, pp 143–147 DOI: 10 5194/ars-1-143-2003</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">. Lourenço, A , Marques, F , Santana, P, Barata, J A volumetric representation for obstacle detection in vegetated terrain, 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014), 2014, pp 283–290, DOI: 10 1109/ROBIO 2014 7090344</mixed-citation><mixed-citation xml:lang="en">Lourenço, A , Marques, F , Santana, P , Barata, J A Volumetric Representation for Obstacle Detection in Vegetated Terrain, 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014 DOI: 10 1109/ROBIO 2014 7090344</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">. Bernini, N ., Bertozzi, M ., Castangia, L ., Patander, M ., Sabbatelli, M Real-time obstacle detection using stereo vision for autonomous ground vehicles: A survey 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2014, pp 873–878 DOI: 10 1109/ITSC 2014 6957799</mixed-citation><mixed-citation xml:lang="en">Bernini, N , Bertozzi, M , Castangia, L , Patander, M , Sabbatelli, M Real-Time Obstacle Detection Using Stereo Vision for Autonomous Ground Vehicles: A Survey, 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 DOI: 10 1109/ITSC 2014 6957799</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">. Takahashi, Katsuhiko Obstacle detection device and method and obstacle detection system, 2014 [Электронный ресурс]: https://www.researchgatenet/publication/302747500_Obstacle_detection_device_and_method_and_obstacle_detection_system Доступ 16 11 2021</mixed-citation><mixed-citation xml:lang="en">Takahashi, Katsuhiko Obstacle detection device and method and obstacle detection system, 2014 [Electronic resource]: https://www researchgate.net/publication/302747500_Obstacle_detection_device_and_method_and_obstacle_detection_system Lastaccessed 16 11 2021</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Khan, Umair; Fasih, Alireza; Kyamakya, Kyandoghere; Chedjou, J Genetic Algorithm Based Template Optimization for a Vision System: Obstacle Detection, 2009 [Электронный ресурс]: https://www.researchgatenet/publication/228347428_Genetic_Algorithm_Based_Template_Optimization_for_a_Vision_System_Obstacle_Detection/ Доступ 16 11 2021</mixed-citation><mixed-citation xml:lang="en">Khan, Umair; Fasih, Alireza; Kyamakya, Kyandoghere; Chedjou, J Genetic Algorithm Based Template Optimization for a Vision System: Obstacle Detection, 2009 [Electronic resource]: https://www.researchgate net/publication/228347428_Genetic_Algorithm_Based_Template_Optimization_for_a_Vision_System_Obstacle_Detection/ Last accessed 16 11 2021</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Охотников А Л , Чернин М А Разработка систем для автономного подвижного состава // Автоматика, связь, информатика – 2021 − № 11 − С 21−24 DOI: 10 34649/AT 2021 11 11 006</mixed-citation><mixed-citation xml:lang="en">Okhotnikov, A L , Chernin, M A Development of systems for autonomous rolling stock [Razrabotka sistem dlya avtonomnogo podvizhnogo sostava] Avtomatika, svyaz, informatika, 2001, Iss 11, pp 21−24 DOI: 10 34649/AT 2021 11 11 006</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Вентцель Е С Теория вероятностей: Учебник − 12-е изд , стер − М : Юстиция, 2018 − 658 с ISBN 978-5-4365-1927-2</mixed-citation><mixed-citation xml:lang="en">Ventzel, E S Probability Theory: Textbook [Teoriya veroyatnostei: Uchebnik] 12th ed , ster Moscow, Yustitsiya publ , 2018, 658 p ISBN 978-5-4365-1927-2</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Баранов Л А Оценка интервала попутного следования поездов для систем безопасности движения на базе радиоканала // Мир транспорта − 2015 − № 2 . − С . 6−24 [Электронный ресурс]: https://mirtr elpub ru/jour/article/view/260 Доступ 16 11 2021</mixed-citation><mixed-citation xml:lang="en">Baranov, L A Evaluation of Metro Train Succession Time for Safety Systems Based on Radio Channel World of Transport and Transportation, 2015, Vol 13, Iss 2, pp 6−24 [Electronic resource]: https://mirtrelpub ru/jour/article/view/260 Last accessed 16 11 2021</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Баранов Л А , Головичер Я М , Ерофеев Е В ., Максимов В М Микропроцессорные системы автоведения электроподвижного состава / Под ред Л А Баранова − М : Транспорт, 1990 − 272 с ISBN 5-277-00964-7</mixed-citation><mixed-citation xml:lang="en">Baranov, L A , Golovicher, Ya M , Erofeev, E V , Maksimov, V M Microprocessor-based automatic control systems for electric rolling stock [Mikroprotsessornie sistemy avtovedeniya elektropodvizhnogo sostava] Ed by Baranov, L A Moscow, Transport publ , 1990, 272 p ISBN 5-277-00964-7</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Бестемьянов П . Ф . Методы повышения безопасности микропроцессорных систем интервального регулирования движения поездов // Автореф дис… докт техн наук – М .: Моск гос ун-т путей сообщ (МИИТ), 2001 – 48 с</mixed-citation><mixed-citation xml:lang="en">Bestemyanov, P F Methods for improving safety of microprocessor systems for interval regulation of train traffic Abstract of D Sc (Eng) thesis [Metody povysheniya bezopasnosti mikroprotsessornykh sistem intervalnogo regulirovaniya dvizheniya poezdov. Avtoref. dis… dok. tekh. nauk] Moscow, MIIT publ , 2001, 48 p</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Никифоров Б . Д ., Головин В . И ., Кутыев Ю . Г . Автоматизация управления движением поездов – М .: Транспорт, 1985 – 263 с</mixed-citation><mixed-citation xml:lang="en">Nikiforov, B D , Golovin, V I , Kutiev, Yu G Automation of train traffic control [Avomatizatsiya upravleniya dvizheniem poezdov] Moscow, Transport publ , 1985, 263 p</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Pudovikov, O . E ., Kiselev, M . D . Optimization of Parameters of Automatic Speed Control System of a Freight Train with Distributed Traction Russian Electrical Engineering, 2020, Vol 91, No . 9, pp 568−576 [Электронный ресурс]: https://elibrary ru/item asp?id=45136886 Доступ 16 11 2021</mixed-citation><mixed-citation xml:lang="en">Pudovikov, O E , Kiselev, M D Optimization of Parameters of Automatic Speed Control System of a Freight Train with Distributed Traction Russian Electrical Engineering, 2020, Vol 91, No 9, pp 568−576 [Electronic resource]: https://elibrary ru/item asp?id=45136886 Last accessed 16 11 2021</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Батенко А . П . Управление конечным состоянием движущихся объектов – М : Сов Радио, 1977 – 256 с.</mixed-citation><mixed-citation xml:lang="en">Batenko, A P Control of the finite state of moving objects [Upravlenie konechnym sostoyaniem dvizhushchikhsya ob’ektov] Moscow, Sov Radio publ , 1977, 256 p.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
