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Enforcing Liveness in Autonomous Traffic Management.
Tsz-Chiu Au, Neda Shahidi, and Peter
Stone.
In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
Looking ahead to the time when autonomous cars will be common, Dresnerand Stone proposed a multiagent systems-based intersection controlprotocol called Autonomous Intersection Management (AIM). Theyshowed that by leveraging the capacities of autonomous vehicles it ispossible to dramatically reduce the time wasted in traffic, andtherefore also fuel consumption and air pollution. The proposedprotocol, however, handles reservation requests one at a time and doesnot prioritize reservations according to their relative priorities andwaiting times, causing potentially large inequalities in grantingreservations. For example, at an intersection between a main streetand an alley, vehicles from the alley can take an excessively longtime to get reservations to enter the intersection, causing a wasteof time and fuel. The same is true in a network of intersections, inwhich gridlock may occur and cause traffic congestion. In this paper,we introduce the batch processing of reservations in AIM to enforceliveness properties in intersections and analyze the conditions underwhich no vehicle will get stuck in traffic. Our experimental resultsshow that our prioritizing schemes outperform previous intersectioncontrol protocols in unbalanced traffic.
@inproceedings{AAAI11-au,
Author = {Tsz-Chiu Au and Neda Shahidi and Peter Stone},
Booktitle= {Proceedings of the Twenty-Fifth Conference on Artificial Intelligence},
Title = {Enforcing Liveness in Autonomous Traffic Management},
Year = {2011},
Month= {August},
abstract = {
Looking ahead to the time when autonomous cars will be common, Dresner
and Stone proposed a multiagent systems-based intersection control
protocol called Autonomous Intersection Management (AIM). They
showed that by leveraging the capacities of autonomous vehicles it is
possible to dramatically reduce the time wasted in traffic, and
therefore also fuel consumption and air pollution. The proposed
protocol, however, handles reservation requests one at a time and does
not prioritize reservations according to their relative priorities and
waiting times, causing potentially large inequalities in granting
reservations. For example, at an intersection between a main street
and an alley, vehicles from the alley can take an excessively long
time to get reservations to enter the intersection, causing a waste
of time and fuel. The same is true in a network of intersections, in
which gridlock may occur and cause traffic congestion. In this paper,
we introduce the batch processing of reservations in AIM to enforce
liveness properties in intersections and analyze the conditions under
which no vehicle will get stuck in traffic. Our experimental results
show that our prioritizing schemes outperform previous intersection
control protocols in unbalanced traffic.
},
}
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