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dc.contributor.advisorBras, Bert
dc.contributor.authorTee Qiao Ying, Amelia
dc.date.accessioned2019-05-29T13:59:55Z
dc.date.available2019-05-29T13:59:55Z
dc.date.created2018-05
dc.date.issued2018-04-16
dc.date.submittedMay 2018
dc.identifier.urihttp://hdl.handle.net/1853/61165
dc.description.abstractFinding parking is one of the common hassles of modern life. Drivers can considerable amounts of time and fuel looking for parking in congested urban centers. Therefore, it is would be very valuable to find a method that can alleviate this parking problem. However, not all solutions are cost-feasible or in some cases, even feasible. The expansion of parking infrastructure is costly and it may be more feasible to implement efficient parking practices instead. This thesis proposes a bio-inspired smart parking solution which aims to reduce the amount of time drivers take to find parking using vehicle-to-vehicle communication and the principles of swarm intelligence. It is based on how individual honeybees communicate with each other while foraging for food. In doing so, they are able to optimize the amount of nectar collected for the colony. In the same way, vehicles can communicate with each other to identify the locations in which they are more likely to find an empty parking space. Results shows that the proposed algorithm is usually more efficient than existing parking algorithms with the exception of a small group of particular circumstances.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectSwarm intelligence
dc.subjectSmart parking
dc.subjectHoneybees
dc.subjectBio-inspired
dc.subjectSystem engineering
dc.titleThe design and simulation of a bio-inspired multi-agent parking system
dc.typeThesis
dc.description.degreeM.S.
dc.contributor.departmentMechanical Engineering
thesis.degree.levelMasters
dc.contributor.committeeMemberTelenko, Cassandra
dc.contributor.committeeMemberWeissburg, Marc
dc.date.updated2019-05-29T13:59:55Z


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