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ACT: Perceptive acting under uncertaintySafety solutions for autonomous systems

Email actinfo@cwi.nl



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AUTONOMOUS VEHICLES NEED RISK-AWARE SOLUTIONS

As human behavior depends on a tightly controlled perception-action cycle that
carefully considers uncertainty and risk, so should the behavior of an
autonomous agent. But this is not trivial to attain. How much risk should an
autonomous agent take? And how does it determine that risk?


WITH THE PEOPLE, FOR THE PEOPLE

Can I cross? Is the cyclist seeing me? Will that car actually stop? A familiar
train of thoughts for a pedestrian navigating an urban environment. How do we
ensure that autonomous vehicles make life easier, not more complex?


AUTONOMOUS VEHICLES NEED RISK-AWARE SOLUTIONS

As human behavior depends on a tightly controlled perception-action cycle that
carefully considers uncertainty and risk, so should the behavior of an
autonomous agent. But this is not trivial to attain. How much risk should an
autonomous agent take? And how does it determine that risk?


WITH THE PEOPLE, FOR THE PEOPLE

Can I cross? Is the cyclist seeing me? Will that car actually stop? A familiar
train of thoughts for a pedestrian navigating an urban environment. How do we
ensure that autonomous vehicles make life easier, not more complex?


AUTONOMOUS VEHICLES NEED RISK-AWARE SOLUTIONS

As human behavior depends on a tightly controlled perception-action cycle that
carefully considers uncertainty and risk, so should the behavior of an
autonomous agent. But this is not trivial to attain. How much risk should an
autonomous agent take? And how does it determine that risk?


WITH THE PEOPLE, FOR THE PEOPLE

Can I cross? Is the cyclist seeing me? Will that car actually stop? A familiar
train of thoughts for a pedestrian navigating an urban environment. How do we
ensure that autonomous vehicles make life easier, not more complex?





INTERDISCIPLINARY RESEARCH

The ACT project bridges Neuroscience, Behavioral Psychology, Engineering,
Robotics and AI to study interactions with humans and autonomous systems and
develop new applications for safe navigation


OUTREACH

The ACT project organizes various outreach activities, including co-creation
workshops for governmental and societal partners; technology demonstrations and
public school-based awareness programs. Events will be announced here.


SOCIETAL IMPACT

The ACT project helps safeguard society from entering a suboptimal, risky and
irreversible transition to living with autonomous vehicles. It does so by
developing AI knowledge whereby society is in the lead and putting the human
central in AI technology.


RESULTS

The ACT project aims to 1) attain Increase insight into the modes of human
behavior under uncertainty 2) develop algorithms that capture behavior under
uncertainty and 3) establish measures and guidelines that determine user
friendly behavior


THE PROJECT

Recent technologies like GPS, smartphones, smart wearables, drones, or
self-driving vehicles are changing the way we interact with others in our
environment. While smart phones have already become ubiquitous and
indispensable, others technologies, like drones and self-driving cars, are much
more difficult to integrate, also for society at large. Developing self-driving
cars behave annoyingly unpredictable for other drivers, and can fail
dramatically in complex city environments, and similar problems exist with
drones. How do we make the behavior of autonomous vehicles predictable for
humans, to avoid conflict and dangerous situations for other traffic
participants? Humans are very good at predicting and adequately responding to
behaviors of other humans, even in demanding environments; machines lack this
human-predictable behavior needed to make urban mobility safe. This project will
chart out these human behaviors and implement them as “neuroware” to artificial
intelligence systems that can guide autonomous vehicles, like drones and
self-driving cars, in a safe way. Scientific, industrial, and societal partners
capitalize on a combination of psychology, neuroscience, artificial
intelligence, engineering and robotics to develop integrated solutions for the
interactions between humans and autonomous systems, and design protocols, rules
and innovative systems for urban mobility and safety.




ACT OVERVIEW

The consortium encompasses a large range of expertise in experimental and
computational neuroscience (in particular, brain mechanisms behind multisensory
perception and sensorimotor control), Psychology, AI and robotics (including
Bayesian inference, machine learning, deep learning, bio-inspired computation,
motion planning and control), and human-machine interactions (behavioral
analytics, machine learning, engineering, control theory). Industrial partners
bring both hardware and software engineering expertise as well as platforms of
what? (2getthere, IMEC, NXP, AIIM). Societal partners align the outcomes with
future guidelines and socially desirable outcomes of what? through their
expertise in these fields (VVN, RDW, SWOV).



0 PIs
0 PhD-students & Postdocs
0 Academic Partners
9 Societal Partners


THE ACT PROJECT

The ACT project encompasses three main project drives, integrating into a set of
pre-defined use cases.

prof dr Pieter Medendorp 4 PhD's & Postdocs


HUMAN BRAIN AND BEHAVIOR

Goals: Build-up a fundamental understanding of how human brains deal with
uncertainty in the real world. Translate these insights into frameworks that can
be applied in autonomous systems. Demonstrate uncertainty-optimized autonomous
agents. This sub-project involves as PIs: prof dr Pieter Medendorp (RU), dr
Jorge Meijas (UvA), prof dr Cyriel Pennartz (UvA), and prof dr Sander Bohte
(CWI, UvA).

dr Javier Alonso Mora 4 PhD's & Postdocs


UNCERTAINTY AND RISK-AWARE AUTONOMOUS AGENTS

Goals: Create a fundamental understanding of how autonomous agents can cope with
uncertainty. Provide means for computing performance guarantees of autonomous AI
systems under uncertainty. Demonstrate risk-aware autonomous agents that are
demonstrably trustable and predictable. This sub-project involves as PIs: dr
Javier Alsono Mora (TUD), dr Jens Kober (TUD), prof dr Robert Babuska (TUD),
prof dr Guido de Croon (TUD), and prof dr Sander Bohte (CWI, UvA).

prof dr Marieke Martens 3 PhD's & Postdocs


HUMAN-AGENT INTERACTION

Goals: Understand how autonomous agents can cope with human uncertainty. Develop
human-predictable perception, planning, and decision-making in interactive
environments. Deliver guidelines and demonstration of human-aware behavior and
planning of autonomous agents. This sub-project involves as PIs: prof dr Marieke
Martens (TU/e and TNO) and dr Bastiaan Petermeijer (NLR).

prof dr Sander Bohte 2 PhD's & Postdocs


USE CASES

Use cases will (1) focus on efficient multi-sensory information processing with
noisy and constrained resources, while maintaining safety guarantees; (2) focus
on operator-drone coordination, where efficiency, robustness, and reliability
are coupled to vehicle and mission specific guidelines in a risk-sensitive way,
to achieve human-predictable and human-trustable behavior; and (3) focus on
autonomous driving in a typical busy and cluttered Dutch setting. All partners
in the project are involved with the use-cases.


STEERING BOARD

The ACT project is guided by the Steering Board.


SANDER BOHTE

Coordinator

Senior researcher at CWI and part-time professor of Computational Neuroscience
at UvA and part-time professor of bio-inspired artificial neural networks at
RUG.


PIETER MEDENDORP

Human brain and behavior

Professor of Sensorimotor Neuroscience, Donders Institute, Radboud University
Nijmegen.


JAVIER ALONSO MORA

Uncertainty and Risk-aware Autonomous Agents

Associate professor at TU Delft.


MARIEKE MARTENS

Human-agent Interaction

Director of Science at TNO Traffic & Transport; professor of Human-Machine
Integration at TUe.


RECENT BLOG

Noteworthy developments in the project and related news.

10 June 2022


IN-PERSON KICK-OFF 2022

With most people having joined the project, we had our first in-person kick-off
meeting at Hotel De Werelt in Lunteren.

Read More



15 March 2023


GENERAL MEETING 2023

Almost a year has passed since our project kick-off, and the next yearly general
meeting is coming into view: on March 15th we are expecting all of you in
Nijmegen to enlighten all of us on your progress and to discuss how we can make
the most out of the project together.

Read More




PHD-STUDENTS & POSTDOCS

The ACT project comprises of a talented and diverse team of researchers, with
the heart of the research being carried out by the PhD-students and Postdocs,
including:

Probabilistic intention prediction of traffic participants in urban environments
at TUD.

Anna Mészáros

PhD-student

Planning in uncertain environments, at TUD

Khaled Mustafa

PhD-student

Intuitive Human-Machine interfacing at NLR.

Nischal Lingam

PhD-student

Working at TUD on (self-supervised/online/meta) learning robust and efficient
neuromorphic perception and processing for vision-based autonomous drone
navigation.

Jesse Hasenaars

PhD-student

Neuromorphic Uncertainty Estimation at CWI.

Tao Sun

Postdoc

Probabilistic intention prediction of traffic participants in urban environments
at TUD.

Anna Mészáros

PhD-student

Planning in uncertain environments, at TUD

Khaled Mustafa

PhD-student

Intuitive Human-Machine interfacing at NLR.

Nischal Lingam

PhD-student

Working at TUD on (self-supervised/online/meta) learning robust and efficient
neuromorphic perception and processing for vision-based autonomous drone
navigation.

Jesse Hasenaars

PhD-student

Neuromorphic Uncertainty Estimation at CWI.

Tao Sun

Postdoc

Probabilistic intention prediction of traffic participants in urban environments
at TUD.

Anna Mészáros

PhD-student




HAVE A QUESTION?

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 * +31 20 592 9393
 * actinfo@cwi.nl

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