Summary:
In this thesis, we present and implement principles and results from Auction
Theory in
approaches/systems that address congestion effects emerging in urban
environments.
We first provide extended literature review on critical aspects and modules of
dominant
auction mechanisms, highlighting the importance of the incentive compatibility
property
as well as the resulting efficiency issues on both the auctioneer's and
bidders' sides. We
then focus on competition/congestion effects that emerge in urban environments
due to
the lack of coordination in the allocation of distributed limited resources. In
particular, we
acknowledge the determining impact of the uncoordinated search for parking
resources
on the generation of “tragedy of commons” situations and propose auction-based
systems as instances of intelligent transportation systems for realizing
centralized
parking space allocation schemes. In this study, drivers are viewed as
strategic agents
who make rational decisions while attempting to minimize the cost of the
acquired
parking spots. These decisions amount to determining whether a driver will bid
or not for
the auctioned parking places as well as the amount of bid when opting for
participating
in the auction. In this respect, we present a comparative research for various
auction
mechanisms in terms of both the resulting social cost and the revenue collected
by the
auctioneer, under various assumptions on the competition levels as shaped by the
parking demand/supply ratio, the pricing policies, the valuations of bidders
for the
auctioned parking places and the associated bidding strategies. Ultimately,
this work
summarizes and locates particular analytical results from Auction Theory proving
theoretical support for the practical management of limited-capacity parking
resources
and presenting useful insights to the dynamics emerging from developing various
auction mechanisms.
Keywords:
competition, social cost, revenue, Intelligent Transportation Systems, parking search problem
