Title:
The design and simulation of a bio-inspired multi-agent parking system

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Tee Qiao Ying, Amelia
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Bras, Berdinus A.
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Abstract
Finding 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.
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2018-04-16
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