Self-driving revolution hampered by a lack of accurate simulations of
human behavior

Date:
June 20, 2023
Source:
University of Leeds
Summary:
Algorithms that accurately reflect the behavior of road users --
vital for the safe roll out of driverless vehicles -- are still
not available, warn scientists. They say there is 'formidable
complexity' in developing software that can predict the way people
behave and interact on the roads, be they pedestrians, motorists
or bike riders. To improve the modelling, a research team has
developed a simulation of how people behave on the roads based on
key cognitive theories.


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==========================================================================
FULL STORY ========================================================================== Self-driving revolution hampered by a lack of accurate simulations of
human behaviour.

Algorithms that accurately reflect the behaviour of road users -- vital
for the safe roll out of driverless vehicles -- are still not available,
warn scientists.

They say there is "formidable complexity" in developing software that
can predict the way people behave and interact on the roads, be they pedestrians, motorists or bike riders.

To improve the modelling, a research team led by Professor Gustav Markkula
from the Institute of Transport Studies at the University of Leeds has developed the first-ever simulation of how people behave on the roads
based on key cognitive theories.

Those separate theories were integrated into a larger, single
psychological model that would "describe behaviour in more complex,
real-world tasks." During computer tests, the model accurately reproduced various well-known but not previously understood behaviours of pedestrians
and drivers in common road scenarios. The model also predicted how
real-life human subjects would behave when facing interactive situations
in a virtual reality simulator.

Professor Markkula said: "These findings suggest that everyday road user behaviour relies on a number of complex underlying cognitive mechanisms,
which may be part of the reason why it has been more difficult than
expected to create self-driving vehicles." "Our research shows that
it is possible to integrate separate theories from psychology into
combined theories for applications such as simulating the way people
behave in traffic, which is something which has been called for but
rarely achieved." The researchers' findings -- Explaining human
interactions on the road by large-scale integration of computational psychological theory -- are published today (Tuesday, June 20) in the scientific journal PNAS Nexus.

Algorithms needed to unlock self-driving revolution The development of automated vehicles could have a major impact on the UK economy.

In a vision statement, the UK Government has said driverless vehicles
will launch a -L-42 billion industry and create 38,000 new jobs. The aim
is to see the start of the safe roll out of driverless vehicles by 2025.

But writing in the scientific journal PNAS Nexus, the researchers argue
that work towards driverless vehicles has been "hampered by a lack of
models of how human road users interact." Accurate models are needed to
run simulations necessary in both development and testing of driverless vehicles and their control systems, for example to demonstrate that the vehicles remain safe when confronted with a range of human behaviour on
the road.

Up to now, most computer models of road user behaviour have been
statistically based, with predictions of how people might behave based
on analysis of large datasets, but typically without analysing those
models at a detailed behavioural level.

The research by Professor Markkula and his team has instead focused specifically on the details of human behaviour and key concepts in
human psychology.

Road user behaviours and theories The researchers looked at several
typical human behaviours that exist on the road, such as hesitation
in unclear situations, or implicit communication using vehicle or body
movement to assert priority or to encourage someone else to go first.

The model predicts how people will behave by reference to key cognitive theories. For example, one is "theory of mind," where people will form
beliefs about what someone else is doing and how their own behaviour
may affect decisions being made by the other. This relates also to
"behavioural game theory," explaining how people consider the combined
effects of their own behaviour and the behaviour of others when deciding
what to do.

Another theory incorporated in the model describes imperfect human
perception, requiring people to take time to assess and understand what
is going on in their environment.

Testing with human participants in the laboratory -- including the HIKER pedestrian simulator at the University of Leeds Virtuocity facilities
- - revealed that the new psychological-theory based model could also
make correct predictions about driver-pedestrian interaction scenarios
studied in the experiments.

Professor Markkula, who holds the chair in Applied Behaviour Modelling
at Leeds, added: "Our research has shown that, by taking a number of
existing but separate mathematical theories about human psychology and behaviour, and putting these together, we can model -- in much more
detail than previously possible -- how humans interact in road traffic,
for example as drivers or pedestrians, including phenomena such as
hesitation and interpretation of others' intentions." In the paper,
the researchers say that much work remains to be done in the development
of psychological based models of road user behaviour.

The overall aim, say the researchers, is to develop computer models that
better reflect the human dimension to behaviour on the roads.

The authors of the paper -- Explaining human interactions on the road
by large- scale integration of computational psychological theory --
are Gustav Markkula, Yi-Shin Lin, Aravinda Srinivasan, Jac Billington,
Matteo Leonetti, Amir Hossein Kalantari, Yue Yang, Yee Mun Lee, Ruth
Madigan, and Natasha Mera. Matteo Leonetti is from Kings College London --
the others are based at the University of Leeds.

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========================================================================== Story Source: Materials provided by University_of_Leeds. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. Gustav Markkula, Yi-Shin Lin, Aravinda Ramakrishnan Srinivasan, Jac
Billington, Matteo Leonetti, Amir Hossein Kalantari, Yue Yang,
Yee Mun Lee, Ruth Madigan, Natasha Merat. Explaining human
interactions on the road by large-scale integration of computational
psychological theory.

PNAS Nexus, 2023; 2 (6) DOI: 10.1093/pnasnexus/pgad163 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2023/06/230620113736.htm

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