Search results

    Search results

    Show all results for ""
    Can not find any results or suggestions for "."

    Search tips

    • Make sure there are no spelling errors
    • Try different search terms or synonyms
    • Narrow your search for more hits

    How can we help?

    Contact Us

    Find Employees

    Skip to sub menu Skip to content
    University of Skövde, link to startpage
    University of Skövde, link to startpage

    Search results

      Search results

      Show all results for ""
      Can not find any results or suggestions for "."

      Search tips

      • Make sure there are no spelling errors
      • Try different search terms or synonyms
      • Narrow your search for more hits

      How can we help?

      Contact Us

      Find Employees

      Intention recognition for real-time automotive 3D situation awareness

      Skövde Artificial Intelligence Lab Informatics

      Intention recognition for real-time automotive 3D situation awareness

      Skövde Artificial Intelligence Lab
      Informatics

      Quick Facts

      Full project name

      IRRA - Intention recognition for real-time automotive 3D situation awareness

      Duration

      1/1/2019 - 12/31/2022

      Financing

      VINNOVA (Swedish Governmental Agency for Innovation Systems)

      Partners

      Volvo Car Corporation (coordinator), the Swedish Transport Administration (Trafikverket), RISE SICS, Smart Eye AB

      Intention recognition is the task of inferring an agent´s intention based on its previous actions. It is crucial for human social intelligence which in turn enables understanding of, and for the ability to predict, other humans´ behaviours, such as for example other drivers´ intent to overtake, stop, turn, or switch lanes. For making situation-based decisions, both autonomous and human drivers need to take the intentions of surrounding vehicles into account. This is especially true in a mix of autonomous and human drivers.

      Expected results and effects

      Existing algorithms and models for intention recognition need to be improved w ith respect to accuracy, robustness, transparency and scalability, in order to meet the requirements of the Swedish automotive industry and Trafikverket. It is an open research question how to achieve this level of maturity. This lack of knowledge is a bottleneck for the automotive industry prohibiting the creation of novel advanced and intelligent automotive services and products based on social intelligence and intention recognition.

      Planned approach and implementation

      Selection of user cases based on important industrial and societal application areas for IR: drivers, vehicles, and system Improvement of existing algorithms for IR using state-ofthe- art in machine learning, computer vision, multi-agent system, automatic derivation, location and new sensor technology Evaluation of results is done through proof-of-concept implementation, vehicle-based tests, and through publication Knowledge transfer is ensured through an industrial doctoral student, workshops, and publications

      Project leader

      Senior Lecturer in Computer Science

      Participating Researchers