@inproceedings{SuchanECAI20,
   author = {Suchan, Jakob and Bhatt, Mehul and Varadarajan, Srikrishna},
   booktitle = {ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020 - Including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020)},
   pages = {2939--2940},
   publisher = {IOS Press},
   title = {{Driven by Commonsense: On the Role of Human-Centred Visual Explainability for Autonomous Vehicles}},
   series = {Frontiers in Artificial Intelligence and Applications},
   volume = {325},
   DOI = {10.3233/FAIA200463},
   abstract = {Within the autonomous driving domain, there is now a clear need and tremendous potential for hybrid solutions (e.g., inte- grating semantics, learning, visual computing) towards fulfilling es- sential legal and ethical responsibilities involving explainability (e.g., for diagnosis), human-centred AI (e.g., interaction design), and in- dustrial standardisation (e.g, pertaining to representation, realisation of rules & norms). In these contexts, this highlight paper positions recent research from IJCAI 2019 [4] aimed at advancing human- centred AI principles in the backdrop of the autonomous driving application domain. From a technical viewpoint, the highlighted re- search provides a model for advancing the state of the art in reason- ing about space and motion, combining reasoning and learning, non- monotonic reasoning, and computational modelling of high-level vi- suospatial commonsense. In addition to demonstrating the signifi- cance of integrated vision and semantics solutions in autonomous driving, we also highlight open questions emphasising the need for interdisciplinary mixed-methods research ?involving AI, Psychol- ogy, HCI? to better appreciate the complexity and spectrum of varied human-centred challenges in diverse naturalistic driving situations. },
    url = {pdfs/cognitive_vision/ECAI2020-driving.pdf},
   year = {2020}
}