Opis projektu DEENESFRITPL Przewidywanie zamiarów pieszych w celu zwiększenia bezpieczeństwa pojazdów inteligentnych Poziomy bezpieczeństwa pojazdów inteligentnych (ang. smart vehicle, SV) są wysokie w warunkach usystematyzowanych, takich jak ruch na autostradzie, ale w mniej zorganizowanych środowiskach, takich jak przejścia dla pieszych i obszary o ruchu mieszanym, poziomy te są znacznie niższe. Finansowany ze środków UE projekt SSVPI ma się przyczynić do zbadania możliwości przewidywania zamiarów pieszych uczestników ruchu, co ma kluczowe znaczenie dla bezpiecznego działania pojazdów SV. W szczególności w ramach projektu zostaną opracowane wieloźródłowe i wielomodalne algorytmy, które będą umożliwiały przewidywanie zamiarów pieszych w trudnych warunkach oświetleniowych. Wyniki będą stanowić podstawę do wielu rządowych i komercyjnych inicjatyw związanych z wprowadzaniem ruchu autonomicznego. Pokaż cel projektu Ukryj cel projektu Cel There has been a lot of research on smart vehicles (SV, including autonomous vehicles and smart powered wheelchairs), mainly for motorways and other structured environments, with resulting safety levels in such highly structured conditions being excellent. However, the situation is different for less structured environments, particularly where interaction between SV and pedestrians is possible, such as pedestrian junctions and mixed traffic environments. In these cases, more fundamental research in safety aspects is needed, since even minor contact between humans and vehicle poses serious dangers to unprotected humans. Specifically, pedestrian intention prediction is crucial for safe and smooth SV operation. This project aims to develop multi-source and multi-modal algorithms which can predict intentions of pedestrians under challenging lighting conditions (using both visible (RGB) and thermal imaging), using cues from both pedestrian movements as well as their environmental and social context. The project aims at enhancing the safety level of pedestrians in the context of SV in unstructured environments. Apart from the development of novel algorithms in this challenging domain, we aim to maximise the impact of our research through the creation of one of the first pedestrian intention prediction datasets combining RGB and thermal images. Performance evaluation of intention pedestrian algorithms will involve both vehicles in intersections, as well as smart wheelchairs for people with disabilities. By enhancing the safety level of SV and pedestrians through predicting pedestrians' intention under various lighting conditions, the results of this project will be very helpful for the development of SV, and will also promote the public' s acceptance of SV. Consequently, the results of this project are very beneficial for the EU, where multiple governmental and commercial autonomous driving initiatives are active. Dziedzina nauki engineering and technologymechanical engineeringvehicle engineeringautomotive engineeringautonomous vehicles Słowa kluczowe pedestrian intention prediction human-vehicle interaction pedestrian trajectory prediction autonomous driving autonomous vehicle smart vehicle Program(-y) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Temat(-y) MSCA-IF-2020 - Individual Fellowships Zaproszenie do składania wniosków H2020-MSCA-IF-2020 Zobacz inne projekty w ramach tego zaproszenia System finansowania MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Koordynator IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE Wkład UE netto € 224 933,76 Adres SOUTH KENSINGTON CAMPUS EXHIBITION ROAD SW7 2AZ LONDON Zjednoczone Królestwo Zobacz na mapie Region London Inner London — West Westminster Rodzaj działalności Higher or Secondary Education Establishments Linki Kontakt z organizacją Opens in new window Strona internetowa Opens in new window Uczestnictwo w unijnych programach w zakresie badań i innowacji Opens in new window sieć współpracy HORIZON Opens in new window Koszt całkowity € 224 933,76
