SSVPI · Safety in Smart Vehicle - Pedestrian Interaction
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2022-04-01 → 2024-03-31
- Финансиране от ЕС
- 224 934 €
- Участници
- 1
- Схема
- MSCA-IF
Линиите свързват координатора с партньорите.
Накратко на български
Интелигентните автомобили се изследват в условия на смесен трафик, за да могат по-точно да предвиждат намеренията на пешеходците на кръстовищата. Това помага за намаляване на риска от катастрофи и повишава доверието на хората в автономното шофиране.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Safety in Smart Vehicle - Pedestrian Interaction
The SSVPI project addresses the challenge of enhancing the safety of smart vehicles (SV) in less structured environments, such as pedestrian junctions and mixed-traffic areas. While SVs are highly reliable on structured motorways, their performance in environments with pedestrian interactions needs improvement. Predicting pedestrian intentions is crucial for preventing accidents and ensuring smooth operation in these complex settings. Improving smart vehicle safety in pedestrian-rich environments is critical for: 1. Safety: Reducing the risk of accidents between pedestrians and vehicles. 2. Public Trust: Building public confidence and acceptance of smart vehicle technologies. 3. Regulatory Support: Supporting governmental and commercial initiatives with robust data and advanced algorithms to improve pedestrian safety and transportation efficiency. The SSVPI project aims to achieve the following objectives: 1. Develop algorithms that can predict the behavior and intentions of pedestrians in less structured environments to enhance the safety level of pedestrians 2. Capture multimodal driving data, offering valuable resources for pedestrian safety research 3. Promote the public's acceptance of SV as well as trust in SV The SSVPI project has made meaningful advancements in predicting pedestrian behavior/intention, protecting privacy, and improving pose estimation performance under various conditions. These contributions enhance the safety of pedestrians and the reliability of smart vehicles in less structured environments. The project's outcomes provide valuable resources and insights that support ongoing efforts in autonomous driving technology, contributing to safer and more efficient transportation systems.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
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.
Оригинален текст от CORDIS (на английски).
Участници
- IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE · LondonКоординаторОбединеното кралство
Връзки
Данни: CORDIS, © Европейски съюз