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Dreams4Cars SIGNED

Dream-like simulation abilities for automated cars

Total Cost €

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EC-Contrib. €

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Partnership

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Project "Dreams4Cars" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA DEGLI STUDI DI TRENTO 

Organization address
address: VIA CALEPINA 14
city: TRENTO
postcode: 38122
website: www.unitn.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Project website http://www.dreams4cars.eu
 Total cost 4˙302˙865 €
 EC max contribution 4˙302˙865 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2016-1
 Funding Scheme RIA
 Starting year 2017
 Duration (year-month-day) from 2017-01-01   to  2019-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI TRENTO IT (TRENTO) coordinator 963˙382.00
2    DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH DE (KAISERSLAUTERN) participant 938˙667.00
3    THE UNIVERSITY OF SHEFFIELD UK (SHEFFIELD) participant 517˙725.00
4    HOGSKOLAN I SKOVDE SE (SKOVDE) participant 505˙625.00
5    CENTRO RICERCHE FIAT SCPA IT (ORBASSANO) participant 495˙000.00
6    MIDDLESEX UNIVERSITY HIGHER EDUCATION CORPORATION UK (LONDON) participant 479˙215.00
7    HEICH CONSULT GMBH DE (HURTH) participant 403˙250.00

Map

 Project objective

Dreams4Cars takes inspiration from the Simulation Hypothesis of Cognition – notably in the sense of Hesslow – and in particular from the idea that thoughts are chains of simulated actions and simulated perceptions. The main objective of Dreams4Cars is to set up an offline simulation mechanism in which robots, by recombining aspects of real-world experience, can produce an emulated world, with which they can collectively interact to safely develop and improve their Perception-Action systems, in particular focusing on the analysis of rare events. The Perception Action systems trained by simulations in this way will then be used for sensorimotor control in real interactions. The application domain of Dream4Cars is automated driving, which – besides being a major economic sector for the EU – also poses the issue of developing systems capable of dealing with arbitrary and open-ended circumstances. Accidents are rare events and, to demonstrate that autonomous systems are safe enough (i.e. significantly safer than humans – which is not achieved today at high and full automation levels), extensive field operation tests would normally be required. The solution offered by Dreams4Cars, by focusing on variations of much more frequent near-miss accidents, can develop safe behaviours for hypothetical/unexperienced situations. Hence Dream4Cars will contribute by solving both the problem of discovering critical situations and the problem of updating safely the software. Dreams4Cars will compare the driving agents evolved by the simulation technology to a baseline agent which will have the same State of the Art skills developed by the latest EU project in driving automation (AdaptIVe), hence concretely verifying the added value of the robotic technology (with target TRL 6).

 Publications

year authors and title journal last update
List of publications.
2019 Alice Plebe, Mauro Da Lio, Daniele Bortoluzzi
On Reliable Neural Network Sensorimotor Control in Autonomous Vehicles
published pages: 1-12, ISSN: 1524-9050, DOI: 10.1109/tits.2019.2896375
IEEE Transactions on Intelligent Transportation Systems 2020-01-30
2019 Donà, Riccardo; Rosati Papini, Gastone Pietro; Valenti, Giammarco
MSPRT action selection model for bio-inspired autonomous driving and intention prediction
published pages: , ISSN: , DOI:
IROS Workshop: Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio-inspiration helpful? 2020-01-30
2019 Riccardo Dona, Gastone Pietro Rosati Papini, Mauro Da Lio, Luca Zaccarian
On the Stability and Robustness of Hierarchical Vehicle Lateral Control With Inverse/Forward Dynamics Quasi-Cancellation
published pages: 10559-10570, ISSN: 0018-9545, DOI: 10.1109/tvt.2019.2941379
IEEE Transactions on Vehicular Technology 68/11 2020-01-30
2019 Zia, Tehseen Zahid, Usman Windridge, David
Modelling Relation Paths with Generative Adversarial for Representation Learning of knowledge Bases
published pages: , ISSN: , DOI:
2020-01-30
2019 Plebe, Alice; Da Lio, Mauro
A Cognitively Informed Perception Model for Driving
published pages: , ISSN: , DOI:
IROS workshop: Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio-inspiration helpful? 2020-01-30
2018 Da Lio, Mauro; Plebe, Alice; Bortoluzzi, Daniele; Rosati Papini, Gastone Pietro; Donà, Riccardo
A System for Human-like Driving Learning
published pages: , ISSN: , DOI:
Proceedings of the 25th ITS World Congress 2018 2020-01-30
2019 Mauro Da Lio, Daniele Bortoluzzi, Gastone Pietro Rosati Papini
Modelling longitudinal vehicle dynamics with neural networks
published pages: 1-19, ISSN: 0042-3114, DOI: 10.1080/00423114.2019.1638947
Vehicle System Dynamics 2020-01-30
2019 Iian Gunn, David Windridge
Revisiting direct neuralisation of first-order logic
published pages: , ISSN: , DOI:
2020-01-30
2018 Basabdatta Sen-Bhattacharya, Sebastian James, Oliver Rhodes, Indar Sugiarto, Andrew Rowley, Alan B. Stokes, Kevin Gurney, Steve B. Furber
Building a Spiking Neural Network Model of the Basal Ganglia on SpiNNaker
published pages: 1-1, ISSN: 2379-8920, DOI: 10.1109/TCDS.2018.2797426
IEEE Transactions on Cognitive and Developmental Systems 2020-01-22
2018 Kamanasish Bhattacharjee, Sushil Kumar, Hari Mohan Pandey, Millie Pant, David Windridge, Ankit Chaudhary
An improved block matching algorithm for motion estimation in video sequences and application in robotics
published pages: 92-106, ISSN: 0045-7906, DOI: 10.1016/j.compeleceng.2018.03.045
Computers & Electrical Engineering 68 2020-01-22
2018 David Windridge, Serge Thill
Representational fluidity in embodied (artificial) cognition
published pages: 9-17, ISSN: 0303-2647, DOI: 10.1016/j.biosystems.2018.07.007
Biosystems 172 2020-01-22
2017 Windridge, David; Gunn, Iain A. D.; Da Lio, Mauro; Mazzalai, Alessandro; Thill, Serge; Svensson, Henrik; Anderson, Sean; Blenkinsop, Alexander; Gurney, Kevin; James, Sebastian; Math, Rafael; Berghoefer, Elmar; Yueksel, Mehmed; Saroldi, Andrea; Andreone, Luisa; Heich, Hermann-Josef
A Hybrid Multi-Layer Architecture for Autonomous Vehicles Utilising a Hierarchical Perception-Action Dream Simulation Mechanism
published pages: , ISSN: , DOI:
EUCognition Meeting 2017 2020-01-22
2017 Santosh Tirunagari, Norman Poh, Kevin Wells, Miroslaw Bober, Isky Gorden, David Windridge
Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition
published pages: 393-407, ISSN: 0932-8092, DOI: 10.1007/s00138-017-0835-5
Machine Vision and Applications 28/3-4 2020-01-22
2018 Iain A.D. Gunn, Álvar Arnaiz-González, Ludmila I. Kuncheva
A taxonomic look at instance-based stream classifiers
published pages: 167-178, ISSN: 0925-2312, DOI: 10.1016/j.neucom.2018.01.062
Neurocomputing 286 2020-01-22
2018 Sebastian James, Sean A. Anderson
Linear System Identification of Longitudinal Vehicle Dynamics Versus Nonlinear Physical Modelling
published pages: , ISSN: , DOI:
Proceedings of Control 2018 Control 2018 - The 12th Interna 2020-01-22
2018 Mauro Da Lio, Alessandro Mazzalai, Kevin Gurney, Andrea Saroldi
Biologically Guided Driver Modeling: the Stop Behavior of Human Car Drivers
published pages: 2454-2469, ISSN: 1524-9050, DOI: 10.1109/TITS.2017.2751526
IEEE Transactions on Intelligent Transportation Systems 19/8 2020-01-22
2016 Serge, Thill; Da Lio, Mauro
Dream­like simulation abilities for automated cars: The Dreams4Cars project.
published pages: , ISSN: , DOI:
EUCognition Meeting 2016 2020-01-22
2017 David Windridge
Emergent Intentionality in Perception-Action Subsumption Hierarchies
published pages: , ISSN: 2296-9144, DOI: 10.3389/frobt.2017.00038
Frontiers in Robotics and AI 4 2020-01-22

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