Hi there, I'm Barry Brown and I'd like to talk to you today a little bit about our
CHI paper, The Halting Problem When Self-Triving Cars Stop In Traffic. The
paper is based around a collection of YouTube data that we've put together of
different self-driving car systems, focusing on this issue where these cars
can often stop on the road in sometimes problematic ways. Our goal is not to
review or evaluate those systems as other people who are doing that work. But really try and understand
a little bit better what's going on in these interactions these self-driving cars are having
on the road. And in particular the role that halting plays and why by sometimes halting incorrectly
these cars are getting into some international problems. More broadly we're interested in
introducing a sort of new genre of interaction for HCI, this new design space which is that of
the interaction between self-driving cars and their movements and other humans on the road.
Let me start though by playing you a clip of a Waymo driving in a suburban street and it's going
to have an interaction with this group of pedestrians who are waiting to cross. The
the video is recorded from the back seat of the car.
You can see a little bit of an insert there
which also shows you the state
of the Waymo's model of the world in the bottom right there.
So you can see that the car comes up to the intersection
and the family gesture for the car to continue
and keep coming around the corner.
Sorry, self-driving car.
It's easy.
It's no worries about that.
So while the car does finally make it around the Marathon Junction
and it's not perhaps unsafe,
certainly a little slightly frustrating interaction.
And indeed the passenger in the back has to apologize
for the self-driving cars behavior.
The problem that we get here is you get this little standoff
where the family moved across the road
and then the car moves, they then get back on the pavement,
the car then stops and you get this little standoff
that you actually often see quite commonly
with these self-driving vehicles.
The problem as we identify it is their inability
to understand a basic unit of road interaction,
which is yielding.
In traffic, it's very frequent that one road user
will indicate to another through slowing down
or stopping or moving in a certain way
that they are yielding for the other road user.
And this is, as I say, a kind of real basic building block of traffic civility that these systems often struggle with.
Let's take a look at our different system, the Tesla FSD system, seeing how it also copes with the situation where there's yielding going on.
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Again, you can see while the Tesla does manage to safely get through the intersection, it actually
allows five cars to go in front of it, even though it actually had the right way there.
Again, this fundamental problem, it can't see when cars are yielding for it. But in this case,
the yielding is slightly more complicated than just a go yield pair, because in an intersection
like this you actually find that the movement of the cars is a little bit more interconnected.
If you look for example, the Tesla gets blocked by this black car, the blue car slows down slowly,
but the Tesla doesn't react in time to actually kind of get through the intersection,
and it then has to in the end break. If you look at work on human interaction,
and you see that this is actually kind of recent
and quite important finding,
that we don't just sequentially take turns
that often actually are actions are responsive
and an ongoing way to the actions of another.
And this can be seen in road interactions,
that you get this tight mutual adjustment,
this reflexive adjustment of each person to each other.
And this is essential for things like yielding,
because you need to be able to constantly monitor
one other road users movements and deal with that
and how you move yourself.
We look at other data in the paper,
but I don't have so much time today,
but just to kind of wrap it all up,
I wanna talk a little bit about it in discussion.
I think this is kind of interesting case
of looking at advanced AI's in the world
and how they're behaving when they're having to interact
with other road users.
The key problem, one of the key problems perhaps we identify
is this problem of joint action,
that self-driving cars and other road users
need to produce action together.
And this is something that they still clearly struggle with.
They can deal with the kinematics of the road,
but this production of joint action
is much more difficult.
Getting to more depth, we talk a lot about
the importance of sequence and timing,
but also not just simply that things happen
in a sequence on the road, but that also there's this continual mutual adjustment going on.
And understanding that is really quite important, I think, for producing more socially responsive
agents, be they robots or self-driving cars. And lastly, we make a kind of final point
in the paper about the importance of repair and intersubjectivity in the production of
joint safe roads. And we clearly, we can see in the behaviour of the systems that we're
looking at, they're not quite there yet, although they've made such great, great
advances. But this actually provides, I think, a more kind of a more broader
issue, which is whether really it is actually possible that we can have
intersubjective agents and how essential is that going to be to have safe and
equitable boat environments. Thank you very much.
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