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EN
The continuous development and importance of the field of road transport these days make it necessary to design, develop and implement technological solutions that reduce (eliminate as much as possible) the risk of road accidents. Such a technological solution is also represented by advanced driver assistance systems (ADAS), systems that assist drivers in various ways, such as collision avoidance, automatic parking, adaptive cruise control, attention and lane departure warnings. Over the next ten years, there will likely be a rise in the need for ADAS system deployment in automobile construction, driven by consumer and regulatory interest in safety applications that protect drivers and lower accident rates. At the moment, autonomous emergency braking and forward collision warning systems are mandated for all cars in the US and the EU. Additionally, advanced driver assistance systems (ADAS) may soon distinguish automobile brands and have a significant impact on consumer preference. The present work aims to provide a general picture related to the current research and development of ADAS systems that refer to the detection of the traffic lane and lane markings. The approaches are presented regarding: the current development directions of ADAS systems, current traffic lane detection techniques, traffic lane detection methods and the use of artificial intelligence techniques in this field. The general conclusion is that further research is needed in the field, research to increase the performance of traffic lane detective systems by using advanced algorithms and easy-to-implement methods that do not require large hardware resources.
EN
Year to year, vehicles are becoming more advanced, and manufacturers offer newer support systems. Progressive technology development must be followed by relevant sociological changes, including establishing a proper user awareness level. Even though compulsory driver training, required before obtaining a license, consists of selected support features, e.g. ABS (Anti-lock Braking System), it does not provide novice drivers with the necessary practical skills and knowledge of all automation features available on the market. To reduce the human error factor, the European Parliament adopted new regulations, including minimum safety requirements for new vehicles. This paper identifies the gap between the current approach toward teaching automation and necessary changes that should be made to ensure road safety. It provides an overview of ADAS functions allowed to be used during driving license exam of category B in different European countries. Moreover, the publication contains results of work carried out under the Trustonomy project. Outcomes obtained from the questionnaires were used to develop new driver training curricula. The publication discusses the developments of a survey conducted among 83 Polish drivers and 91 car fleet managers. The paper reveals their attitude and expectations towards driver training. The results indicate that despite the awareness of ADAS's positive impact on safety (80% of drivers vote, 96% of car fleet managers votes), man people still didn't take part in any training and still do not know how to use systems properly. Even more worrying is the fact that more than 50% of drivers admitted they acquired knowledge about system operation based on their own mistakes. Many responders expressed their interest in acquiring new knowledge. This situation indicates an urgent need to introduce changes to the driver training system. Therefore, the publication highlights different regulatory boundaries across Europe and stresses the need to update existing curricula to introduce proper automation-related training.
EN
The paper presents an experimental stand for testing the front car camera S-CAM with embedded image recognition systems. The camera sends CAN messages these are converted to USART messages by microprocessor based system. The messages are interpreted by MATLAB script on the basis of database of traffic signs in accordance with Polish Road Code. The testing stand is mainly aimed for educating students interested in the fields of electronics and technologies related to automotive branch, as well. The second objective is a research on efficiency of traffic sign recognition system being one of functionalities of S-CAM camera. The technical specification of testing stand, its functionality and limitations were also discussed. The bench operation was illustrated with examples of stiff images, animation and real movies.
EN
ADAS (Advanced Driver Assistance Systems) plays an important role in building a safe and modern traffic system. For these systems, precise detection performance and response speed are critical. However, the detection of mobile vehicles is facing many difficulties due to the density of vehicles, the complex background scene in the city, etc. In addition, the detection and identification requirements respond in real time is also a challenge for current systems. This paper proposes a model using deep learning algorithms and artificial intelligence to increase accuracy and improve response speed for intelligent driving assistance systems. Accordingly, this paper proposes the YOLO (You Only Look One) model together with a sample data set collected and classified separately suitable for Vietnam traffic and our training algorithm. The experimental results were then performed on an NVIDIA Jetson TX2 embedded computer. The experimental results show that, the proposed method has increased the speed by at least 1.5 times with the detection rate reaching 79\% for the static camera system; and speed up at least 1.5x with a detection rate of 89\% for the dynamic camera system at 1280x720px high resolution images.
EN
Lane detection is one of the key steps for developing driver assistance and vehicle automation features. A number of techniques are available for lane detection as part of computer vision tools to perform lane detection with different levels of accuracies. In this paper a unique method has been proposed for lane detection based on dynamic origin (DOT). This method provides better flexibility to adjust the outcome as per the specific needs of the intended application compared to other techniques. As the method offers better degree of control during the lane detection process, it can be adapted to detect lanes in varied situations like poor lighting or low quality road markings. Moreover, the Piecewise Linear Stretching Function (PLSF) has also been incorporated into the proposed method to improve the contrast of the input image source. Adding the PLSF method to the proposed lane detection technique, has significantly improved the accuracy of lane detection when compared to Hough transform method from 87.88% to 98.25% in day light situations and from 94.15% to 97% in low light situations.
EN
Strengthening road safety in the face of the enormous development of the automotive in recent decades is crucial. The safety benefits of automated vehicles are paramount. Automated vehicles have the potential to remove human error in road traffic, which will help protect drivers and passengers, as well as pedestrians and bicyclists. The carried-out forecasts are pioneering for Polish road traffic conditions. In England, studies have been carried out to determine the estimated impact of autonomous vehicles on road safety in simulated traffic conditions on the motorway. In Poland, preliminary forecasts of the reduction in the number of road accidents were made; however, they were based on other assumptions. Therefore, estimating the impact of using autonomous vehicles in order to increase the level of road safety is an innovative activity for Polish road conditions. For the purposes of this article, available statistical data on vehicles registered in Poland, their equipment with advanced driver-assistance systems as well as accident data and their causes were analyzed. A diagnosis of Road Safety in Poland in 2018 (base year for further estimations) was made, taking into account the trend of recent years together with an indication of the most common causes of road accidents. These data were compiled with statistical data from other countries about the influence of driversupport systems on traffic safety. Possible potential for increasing Road Safety in Poland by the year 2030 was estimated. The analyses were prepared assuming different types of processes related to traffic, road safety, and the recent development of the passenger car fleet in Poland. Presented results show four scenarios of road safety change, where the number of accidents is reduced with statistical average of 5000 reduction in the year 2030. These expectations are based on various predictable factors connected with upgrade of car fleet quality and take into account changes in road safety observed in recent years. Based on the current trend of driving automation and rapid development of driver-support systems, the provided estimations were found reliable and likely. The conducted research shows the benefits and the need for the use of driver-assistance systems in vehicles as they can measurably affect the level of road safety.
PL
W ostatnich latach znacznie wzrosła liczba zaawansowanych systemów wspomagających kierowcę. Spowodowało to potrzebę opracowania metod testowania ich jakości i niezawodności. Artykuł przedstawia przegląd metod badawczych stosowanych w przemyśle motoryzacyjnym wykorzystywanych w weryfikacji i walidacji zaawansowanych systemów wspomagania kierowcy (ADAS), aktywnego bezpieczeństwa i systemów jazdy autonomicznej. W pierwszej części przedstawiono podejście do testów nazywanych testowaniem w pętli, takich jak model w pętli, oprogramowanie w pętli itd., prezentując najciekawsze implementacje. Następnie omówiono testy wykonywane na różnych terenach testowych, które mają udowodnić niezawodność i jakość systemu. Testowymi terenami mogą być tory testowe, sztuczne miasta czy drogi publiczne. W ostatniej części przedstawiono walidację wykonaną w laboratorium z wykorzystaniem metod zarówno inwazyjnych, jak i nieinwazyjnych, opartych na wirtualnych jazdach testowych, stymulatorach czujników i hamowniach podwoziowych. Ponadto zidentyfikowaliśmy najbardziej obiecujące podejścia do skutecznej weryfikacji i walidacji systemów ADAS, aktywnego bezpieczeństwa oraz jazdy autonomicznej. Na koniec wskazujemy potencjalne luki w tym temacie, które wymagają dalszych badań.
EN
The number of advanced driver assistance systems has increased dramatically in recent years. This led to a need for the development of testing methods to prove the quality and reliability of such systems. This publication presents an overview of the testing methods used in the automotive industry for the verification and validation of advanced driver assistance systems (ADAS), active safety, and autonomous driving systems. The first part presents the approach to X-in-the-loop testing such as model, software, hardware, etc., presenting the most interesting implementations. Then it discusses testing in proven areas like road traffic, artificial cities, and test tracks. The last part presents validation in the laboratory using both invasive and non-invasive methods based on virtual test drives, sensor stimulators and chassis dynamometers. Moreover, we identified the most promising approaches for the efficient verification and validation of ADAS, active safety and autonomous driving systems. Finally, we address some gaps in the research which require further investigation.
EN
The number of advanced driver assistance systems has increased dramatically in recent years. This led to a need for the development of testing methods to prove the quality and reliability of such systems. This publication presents an overview of the testing methods used in the automotive industry for the verification and validation of advanced driver assistance systems (ADAS), active safety, and autonomous driving systems. The first part presents the approach to X-in-the-loop testing such as model, software, hardware, etc., presenting the most interesting implementations. Then it discusses testing in proven areas like road traffic, artificial cities, and test tracks. The last part presents validation in the laboratory using both invasive and non-invasive methods based on virtual test drives, sensor stimulators and chassis dynamometers. Moreover, we identified the most promising approaches for the efficient verification and validation of ADAS, active safety and autonomous driving systems. Finally, we address some gaps in the research which require further investigation.
PL
W ostatnich latach znacznie wzrosła liczba zaawansowanych systemów wspomagających kierowcę. Spowodowało to potrzebę opracowania metod testowania ich jakości i niezawodności. Artykuł przedstawia przegląd metod badawczych stosowanych w przemyśle motoryzacyjnym wykorzystywanych w weryfikacji i walidacji zaawansowanych systemów wspomagania kierowcy (ADAS), aktywnego bezpieczeństwa i systemów jazdy autonomicznej. W pierwszej części przedstawiono podejście do testów nazywanych testowaniem w pętli, takich jak model w pętli, oprogramowanie w pętli itd., prezentując najciekawsze implementacje. Następnie omówiono testy wykonywane na różnych terenach testowych, które mają udowodnić niezawodność i jakość systemu. Testowymi terenami mogą być tory testowe, sztuczne miasta czy drogi publiczne. W ostatniej części przedstawiono walidację wykonaną w laboratorium z wykorzystaniem metod zarówno inwazyjnych, jak i nieinwazyjnych, opartych na wirtualnych jazdach testowych, stymulatorach czujników i hamowniach podwoziowych. Ponadto zidentyfikowaliśmy najbardziej obiecujące podejścia do skutecznej weryfikacji i walidacji systemów ADAS, aktywnego bezpieczeństwa oraz jazdy autonomicznej. Na koniec wskazujemy potencjalne luki w tym temacie, które wymagają dalszych badań.
EN
The global objective of this paper is to analyze engineering risk of series production in Automotive Industries based on problems caused by supplied chain of products when a strong process to avoid engineering risk problems is missing. Automotive Industries Companies in Romania use just some theoretical tools like as D-FMEA (Design – Failure Mode and Effect Analysis) for engineering risk in their design products in ADAS domein. The main causes appear after the production starts and sometimes it brings the production to a halt. The risks reveal details of different levels and high risk can be caused by unforeseen challenges during of series production. On this paper, the method for engineering risk of management used is based on project management guide by Paul Roberts adapted to causes identification and risk plan.
EN
Nowadays Advanced Driver Assistant Systems (ADAS) are becoming more popular in car equipment. During ADAS development process it is necessary to prepare numerical models and perform simulation tests, so the systems could be safely implemented. However, because these systems are directly connected to a human – machine interface, volunteer tests on a car simulator are conducted. They are indispensable for testing the correct operation of the system, but above all for showing differences in the operation of the system and a driver in terms of human reliability. Presented research shows results of simulator tests in two cases: extra - urban and mixed scenarios. The tests were classic, tracking tasks in which the driver was required to keep a safe, predefined distance from the leading car. Consequently, the results of experiments were compared to results of the reference car performance, i.e. the car equipped with Adaptative Cruise Control system. It made possible to assess the driver reliability. Moreover, questionnaire tests (NASA TLX) were also applied to assess subjects’ workload. Finally, results of volunteers’ rides were compared to results of a simulation with use a driver model based on fuzzy logic. This model, in the future, may be used in development of a car simulator equipped with ADAS.
PL
Obecnie zaawansowane systemy wspomagania kierowcy (ADAS) stają się coraz popularniejszym elementem wyposażenia samochodów. Z procesem ich rozwoju wiąże się konieczność przygotowania modeli numerycznych i przeprowadzenie testów symulacyjnych, aby zapewnić bezpieczne wdrożenie systemów. Z faktu ich bezpośredniego powiązania z interfejsem człowiek- maszyna wynika potrzeba prowadzenia testów na symulatorze z udziałem ochotników. Są one niezbędne do sprawdzenia poprawności działania danego systemu, ale przede wszystkim do wykazania różnic w działaniu systemu i kierowcy w kontekście niezawodności człowieka. Prezentowane badania pokazują wyniki testów symulatorowych w dwóch scenariuszach: pozamiejskim i mieszanym. Testy składały się z klasycznych zadań, w których kierowca musiał utrzymywać bezpieczną, z góry określoną odległość od wiodącego samochodu. W rezultacie wyniki eksperymentów porównano z osiągami samochodu referencyjnego, wyposażonego w tempomat adaptacyjny tzw. ACC (Adaptative Cruise Control). Umożliwiło to ocenę kierowcy pod kątem jego niezawodności. Ponadto do analizy obciążenia uczestników zastosowano również testy kwestionariuszowe NASA TLX. Ostatecznie wyniki przejazdów uczestników testów porównano także z wynikami symulacji przeprowadzonej z wykorzystaniem modelu wirtualnego kierowcy (zbudowanego z użyciem logiki rozmytej). Model ten w przyszłości będzie mógł być wykorzystany do opracowania i rozwoju symulatora samochodowego wyposażonego w ADAS.
EN
The article presents one application from the ADAS (Advanced Driver Assistance Systems) group of systems, which enables the reading of parameters from the module connected to the diagnostic port in the vehicle. The developed application enables better control of engine operation and supports the driver in the field of, among others indication of currently running gear and suggestion of switching on the higher or lower gear depending on the engine parameters read. The suggestion of changing gears is shown graphically and sonically. The application is designed for mobile devices working under the control of Android operating system.
EN
The paper presents benefits of Advanced Driver Assistance Systems (“ADAS”) application from the safety point of view. Statistical data on accidents on Polish roads in 2015 was used as the basis for preliminary risk assessment. Potential reduction of the number of accidents due to ADAS equipment per each of accidents’ type was estimated using an expert method. Knowing the participation of individual types and causes in the total number of accidents, assessment of the influence of systems to improve road safety was possible. Estimates carried out for the following systems: the Advanced Emergency Braking System ("AEBS"), the Adaptive Cruise Control ("ACC") and the Lane Departure Warning ("LDW"). The results show that the most effective is AEBS - reduction of the number of accidents by 33%. If ACC was considered – 27%, LDW – 4%. For all three driver assistance systems are active, the road safety can increase by almost 47%.
PL
Tematem niniejszej publikacji jest przedstawienie korzyści z zastosowania zaawansowanych systemów wspomagania kierowcy (Advanced Driver Assistance Systems – „ADAS”) z punktu widzenia bezpieczeństwa. Wstępna ocena ryzyka została wykonana z wykorzystaniem danych statystycznych dotyczących wypadków na polskich drogach w roku 2015 z podziałem na ich rodzaje i przyczyny. Dla poszczególnych rodzajów i przyczyn wypadków oszacowano, wykorzystując metody eksperckie, zmniejszenie liczby wypadków (zmniejszenie współczynnika wypadkowości) spowodowane wyposażeniem samochodu w systemy wspomagania kierowcy. Znając udział poszczególnych typów i rodzajów w ogóle wypadków możliwa była ocena wpływu omawianych systemów na poprawę bezpieczeństwa ruchu drogowego. Oszacowania przeprowadzono dla zawansowanego systemu hamowania awaryjnego („Advanced Emergency Braking Systems – „AEBS”), tempomatu adaptacyjnego (Adaptive Cruise Control - „ACC”) oraz systemu ostrzegania przed niezamierzoną zmianą pasa ruchu (Lane Departure Warining - „LDW”). Wyniki pokazują, że najbardziej efektywny jest AEBS - redukcja liczby wypadków o około 33%. Natomiast dla ACC wyniesie ona 27%, dla LDW 4%. Jeśli aktywne są trzy systemy wspomagania kierowcy, bezpieczeństwo na drodze może wzrosnąć nawet o 4
EN
The paper presents examples of the functionalities of the Lidar that is used in the automotive industry for advanced driving assistance systems. Firstly, a brief overview of Lidar technology and an introduction to communication that is built on a CAN bus is presented. Then, the Lidar that was selected for the tests is described along with the principles of how it works and its startup conditions. Finally, a description of the experiment is presented along with the results.
PL
Artykuł prezentuje przykładowe funkcjonalności urządzenia typu Lidar, które jest używane w samochodowych zaawansowanych systemach wspomagania kierowcy. Tekst zawiera przegląd technologii Lidar, wprowadzenie do komunikacji opartej na magistrali CAN oraz opis wybranego do testów Lidaru wraz z zasadami działania i warunkami jego uruchomienia. Dodatkowo opisane zostały przykładowe eksperymenty przeprowadzone z wykorzystaniem urządzenia oraz ich wyniki.
PL
Zespół Smart Power z Politechniki Śląskiej od 2012 r. uczestniczy w międzynarodowych wyścigach pojazdów energooszczędnych Shell Eco-marathon. Podczas konstruowania swojego drugiego pojazdu – elektrycznego pojazdu typu miejskiego – zespół położył nacisk na opracowanie zaawansowanych systemów wspomagania kierowcy (ADAS); w ich projektowaniu wykorzystano metody wirtualnego prototypowania.
EN
Smart Power team participates in the World competition of energy efficient vehicles – Shell Eco-marathon since 2012. During the design work on the second vehicle i.e. an electric vehicle Urban Concept category, attention of the team has been drawn to the development of Advanced Driver Assistance Systems (ADAS), with the respective methods of design applied in the virtual prototyping work.
EN
Advance driver assistance systems (ADAS) have been commonly introduced in modern car fleet on the roads nowadays. Current computer techniques allow to test and verify even quite complex algorithms used by sophisticated ADAS in real-time simulations. Systems can be tested according to already existing norms or standards e.g. ISO or any other test protocols – like proposed NCAP or NHTSA tests. Every such a test has limitations and conditions that would not be present in the real world, like only one target car. In 2007 the 3rd edition of DARPA Grand Challenge known as DARPA Urban Challenge (DUC) took place. During competition fully autonomous vehicles needed to complete safe driving along realistic urban area respecting all standard US traffic rules and taking into account existing in reality other road players. Based on requirements of DUC a series of test protocols of computer simulation have been proposed. Virtual fully autonomous vehicle has been controlled by the series of split out single action ADAS systems for easier analysis of the car behaviour, at the early test phase. Although It has successfully completed test run, developed own control algorithms needs further optimization.
PL
Zaawansowane systemy wspomagające kierowcę (Advance Driver Assistance Systems - ADAS) odnajdują powszechne zastosowanie we współczesnych samochodach. Aktualne techniki komputerowe pozwalają na wykonywanie testów i weryfikacji nawet skomplikowanych algorytmów, użytych w złożonych systemach ADAS, w symulacjach czasu rzeczywistego. Systemy takie mogą być testowane zgodnie z istniejącymi normami i standardami (na przykład: ISO) oraz protokołami (na przykład zaproponowane przez NCAP lub NHTSA). Każdy z tych testów ma jednak pewne ograniczenia, które nie są możliwe do spełnienia w przypadku fizycznych testów, jak chociażby tylko jeden dodatkowy samochód jako monitorowany obiekt. W 2007r. odbyła się trzecia edycja DARPA Grand Challenge, znana także jako DARPA Urban Challenge (DUC). Podczas zawodów, w pełni autonomiczne samochody miały za zadanie bezpiecznie ukończyć przejazd po realistycznym terenie miejskim z uwzględnieniem zarówno wszystkich przepisów ruchu drogowego (USA) jak i innych (fizycznie występujących w teście) uczestników ruchu. Opierając się o wymagania DUC wykonana została zaproponowana seria symulacji komputerowych. W pełni autonomiczny, wirtualny pojazd, kontrolowany był przez serię rozdzielonych, niezależnych i jednozadaniowych systemów ADAS dla łatwiejszej analizy zachowania samochodu we wczesnej fazie testów. Pomimo udanego ukończenia przejazdu testowego, algorytmy sterujące samochodem wymagają dalszej optymalizacji.
16
Content available remote Comparative Survey on Traffic Sign Detection and Recognition: a Review
EN
Developing real-time Advanced Driver Assistance Systems (ADAS) based on video aiming to extract reliable vehicle state information has attracted a lot of attention during the past decades. This ADAS system includes inter-vehicle communication, driver behavioral monitoring, and human-machine interactions. In these systems, robust and reliable traffic sign detection and recognition (TSDR) technique is a critical step for ensuring vehicle safety. This paper provides a comprehensive survey on traffic sign detection and recognition system based on image and video data. Our main focus is to present the current trends and challenges in the field of developing an efficient TSDR system followed by a detail comparative study between different renowned methods used by various researchers. Finally, conclusion followed by some future suggestion is provided to develop an efficient TSDR system is provided. This survey will hopefully lead to develop an effective traffic sign detection and recognition system which will ensure driver safety in future.
PL
System ADAS (Advanced Driver Assistance System) obejmuje także metody rozpoznawania znaków drogowych. W artykule przedstawiono przegląd metod detekcji i rozpoznawania znaków drogowych bazujących na obrazie video. W artykule dokonano oceny istniejących metod oraz zaproponowano środki poprawy ich efektywności.
EN
Th e article presents the design methodology of Advanced Driver Assistance Systems (ADAS) for electric vehicles. As an example the Blind Spot Information System (BLIS) is described, which was created for an urban electric car - Bytel, the vehicle constructed within the Smart Power project. A specialized soft ware was used, TASS PreScan, the soft ware created for the purposes of advance driver’s assistance systems design. Th e article discusses the following stages of ADAS system creation - the needs analysis, the designing and the model testing. Within the needs analysis there are such subcategories as the needs defi nition, the project goals and the project planning . Th e designing part focuses on two aspects: choosing the proper tool for designing and testing ADAS model and creating the system model, including data processing system and control system. Th e model testing section includes test planning and testing procedure description. Th e article ends with conclusions and future directions of the proposed model development
PL
Bolid elektryczny MuSHELLka, startujący w światowych zawodach Shell Eco-marathon w 2013 roku, wyposażono w aktywne systemy bezpieczeństwa: BLIS (system informujący kierowcę o pojawieniu się obiektu w mar-twym polu), ACC (system skanujący przestrzeń przed bolidem), ACS (system działający w przypadku kolizji). Bazują one na istniejących systemach, które są wykorzystywane obecnie w samochodach. Dostosowanie tych systemów na potrzeby bolidu elektrycznego MuSHELLka było bardzo skomplikowane, jednak za pomocą specjalnego oprogramowania PreScan firmy TASS zaprojektowano jei przebadano tak, aby zapewniały kierowcy i jego konkurentom większe bezpieczeństwo. Słowa kluczowe: systemy bezpieczeństwa, zaawansowany system wspomagania kierowcy, systemy automatyki jazdy, PreScan, Bolid MuSHELLka, Shell Eco-marathon, system informacji „martwego pola”, system informacji o wyprzedzaniu, system bezpieczeństwa w przypadku kolizji.
EN
Electric vehicle MuSHELLka during development for 2013 Shell Eco-marathon, has been equipped with active safety systems. Blind Spot Information System, Adaptive Cruise Control and Automatic Crash System. All those systems will ensure driver and his opponents more safety. Projects of submitted systems based on real layouts which are nowadays in cars. Adaptation of those systems for our vehicle and race needs were complicated. With aid of special software PreScan from TASS, which is a computer simulator for advanced driver assistance systems, there were possibilities to design and test safety systems in the specified environment. It is an urban racetrack in Rotterdam, Holland. Also there were capabilities to specify sensors and their properties. Entirely with MATLAB/Simulink software have given opportunity to build and verify selected safety systems.
EN
With Galileo, the European GNSS (Global Navigation Satellite System) starting early services in 2015, open-area-testing of applications which use the new positioning system gets more and more important. This contribution gives an overview on existing test sites like railGATE, automotiveGATE and seaGATE, it highlights the latest addition for dynamic calibration with geodetic precision and finally describes the testing regime of the BONUS project ANCHOR, where multiple test sites are used for maximum benefit in a maritime application.
PL
Wraz z systemem Galileo, europejskim systemem nawigacji satelitarnej GNSS, którego pierwsze usługi przewiduje się udostępnić w 2015 roku, coraz bardzie istotne staje się stworzenie warunków dla testowania aplikacji systemu w otwartym terenie. Te możliwości dają poligony railGATE, automotiveGATE oraz seaGATE, które opisano w artykule, zwracając szczególną uwagę na dynamiczne kalibrowanie urządzeń z geodezyjną dokładnością. Zwrócono również uwagę na specyfikę testów przewidzianych w projekcie ANCHOR realizowanym w ramach europejskiego programu BONUS. Przewiduje się w nich różne warunki pod kątem maksymalizacji zastosowań morskich.
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