With the increasing number of vehicles on the roads, finding a free
parking space has become a time-consuming problem. Traditional car parks are
not equipped with occupancy sensors, so planning a systematic traversal of a
car park can ease and shorten the search. Since car park exploration is
similar to coverage path planning (CPP) problems, the core concepts of CPP
algorithms can be used. This paper presents a method that divides maps into
smaller cells using trapezoidal cell decomposition and then plans the
traversal using wavefront algorithm core concepts. This method can be used
for multi-storey car parks by planning the traversal of each floor
separately and then the path from one floor to the next. Several alternative
explorational paths can be generated by taking different personal
preferences into account, such as the length of the driven route and the
proximity to preferred locations. The planned traversals are compared by
step number, the cell visitedness ratio, the number of visits to each cell
and the cost function. The comparison of the methods is based on simulation
results.
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