SwePub
Sök i LIBRIS databas

  Utökad sökning

WFRF:(Johnander Joakim)
 

Sökning: WFRF:(Johnander Joakim) > (2024) > Towards trustworthy...

  • Carrasco Limeros, SandraUniversidad de Alcala,University of Alcalá,Univ Alcala, Spain; AI Sweden, Sweden; Zenseact AB, Sweden (författare)

Towards trustworthy multi-modal motion prediction: Holistic evaluation and interpretability of outputs

  • Artikel/kapitelEngelska2024

Förlag, utgivningsår, omfång ...

  • WILEY,2024
  • electronicrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:research.chalmers.se:204d8ecc-1701-4178-b642-0052e01912f8
  • https://research.chalmers.se/publication/536212URI
  • https://doi.org/10.1049/cit2.12244DOI
  • https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-195291URI

Kompletterande språkuppgifter

  • Språk:engelska
  • Sammanfattning på:engelska

Ingår i deldatabas

Klassifikation

  • Ämneskategori:art swepub-publicationtype
  • Ämneskategori:ref swepub-contenttype

Anmärkningar

  • Funding Agencies|European Commission, Joint Research Center; Ministerio de Cienciae Innovacion [PID2020-114924RB-I00]; Comunidadde Madrid [S2018/EMT-4362]
  • Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning. This task is very complex, as the behaviour of road agents depends on many factors and the number of possible future trajectories can be considerable (multi-modal). Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited interpretability. Moreover, the metrics used in current benchmarks do not evaluate all aspects of the problem, such as the diversity and admissibility of the output. The authors aim to advance towards the design of trustworthy motion prediction systems, based on some of the requirements for the design of Trustworthy Artificial Intelligence. The focus is on evaluation criteria, robustness, and interpretability of outputs. First, the evaluation metrics are comprehensively analysed, the main gaps of current benchmarks are identified, and a new holistic evaluation framework is proposed. Then, a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception system. To enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework, an intent prediction layer that can be attached to multi-modal motion prediction models is proposed. The effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and intentions. The proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autonomous vehicles, advancing the field towards greater safety and reliability.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Majchrowska, SylwiaAI Sweden, Sweden; Zenseact AB, Sweden (författare)
  • Johnander Faxén, JoakimLinköpings universitet,Datorseende,Tekniska fakulteten,Zenseact AB, Sweden,Linköping University(Swepub:liu)joajo88 (författare)
  • Petersson, Christoffer,1979Chalmers tekniska högskola,Chalmers University of Technology,Zenseact AB, Sweden; Chalmers Univ Technol, Sweden(Swepub:cth)chrpet (författare)
  • Sotelo, Miguel ÁngelUniversidad de Alcala,University of Alcalá,Univ Alcala, Spain (författare)
  • Fernández Llorca, DavidEuropeiska kommissionens gemensamma forskningscentrum (JRC),Joint Research Centre (JRC), European Commission,Universidad de Alcala,University of Alcalá,Univ Alcala, Spain; European Commiss, Spain (författare)
  • Universidad de AlcalaUniv Alcala, Spain; AI Sweden, Sweden; Zenseact AB, Sweden (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:CAAI Transactions on Intelligence Technology: WILEY9:3, s. 557-5722468-65572468-2322

Internetlänk

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy