File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

AuTsz-Chiu

Au, Tsz-Chiu
Agents & Robotic Transportation Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.conferencePlace US -
dc.citation.conferencePlace San Francisco, CA; USA -
dc.citation.endPage 1322 -
dc.citation.startPage 1317 -
dc.citation.title 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference -
dc.contributor.author Au, Tsz-Chiu -
dc.contributor.author Shahidi, N. -
dc.contributor.author Stone, P. -
dc.date.accessioned 2023-12-20T03:06:00Z -
dc.date.available 2023-12-20T03:06:00Z -
dc.date.created 2014-12-23 -
dc.date.issued 2011-08-07 -
dc.description.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. -
dc.identifier.bibliographicCitation 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, pp.1317 - 1322 -
dc.identifier.scopusid 2-s2.0-80055064200 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/34451 -
dc.identifier.url http://www.scopus.com/inward/record.url?eid=2-s2.0-80055064200&partnerID=40&md5=d5974f1c83f1b16c80b4a67642fd970a -
dc.language 영어 -
dc.publisher AAAI -
dc.title Enforcing Liveness in Autonomous Traffic Management -
dc.type Conference Paper -
dc.date.conferenceDate 2011-08-07 -

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.