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Kurt Dresner and Peter Stone. Sharing the Road: Autonomous Vehicles Meet Human Drivers. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, pp. 1263–68, Hyderabad, India, January 2007.
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In modern urban settings, automobile traffic and collisions lead to endless frustration as well as significant loss of life, property, and productivity. Recent advances in artificial intelligence suggest that autonomous vehicle navigation may soon be a reality. It has been demonstrated that a reservation-based approach can efficiently and safely govern interactions of multiple autonomous vehicles at intersections. Such an approach alleviates many traditional problems associated with intersections, in terms of both safety and efficiency. However, the system relies on all vehicles being equipped with the requisite technology --- a restriction that would make implementing such a system in the real world extremely difficult. In this paper, we extend the previously proposed system to allow for incremental deployability. The modified system is able to accommodate traditional human-operated vehicles using existing infrastructure. Furthermore, we show that as the number of autonomous vehicles on the road increases, traffic delays decrease monotonically toward the levels exhibited in the previous work. Finally, we develop a method for switching between various human-usable configurations while the system is running, in order to facilitate an even smoother transition. The work is fully implemented and tested in our custom simulator, and we present detailed experimental results attesting to its effectiveness.
@InProceedings{2007ijcai-dresner,
author="Kurt Dresner and Peter Stone",
title="Sharing the Road: Autonomous Vehicles Meet Human Drivers",
booktitle= IJCAI07,
address="Hyderabad, India",
month="January",year="2007",
pages = "1263--68",
abstract={
In modern urban settings, automobile traffic and collisions lead to
endless frustration as well as significant loss of life, property,
and productivity. Recent advances in artificial intelligence suggest
that autonomous vehicle navigation may soon be a reality. It has
been demonstrated that a reservation-based approach can efficiently
and safely govern interactions of multiple autonomous vehicles at
intersections. Such an approach alleviates many traditional problems
associated with intersections, in terms of both safety and
efficiency. However, the system relies on all vehicles being
equipped with the requisite technology --- a restriction that would
make implementing such a system in the real world extremely
difficult. In this paper, we extend the previously proposed system
to allow for incremental deployability. The modified system is able
to accommodate traditional human-operated vehicles using existing
infrastructure. Furthermore, we show that as the number of
autonomous vehicles on the road increases, traffic delays decrease
monotonically toward the levels exhibited in the previous
work. Finally, we develop a method for switching between various
human-usable configurations while the system is running, in order to
facilitate an even smoother transition. The work is fully
implemented and tested in our custom simulator, and we present
detailed experimental results attesting to its effectiveness.
},
bib2html_rescat = {Autonomous Intersection Management},
bib2html_pubtype = {Refereed Conference},
}
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