In recent years, with the rapid growth of the number of cars, the problem of "difficult parking" has become increasingly prominent, especially in the parking lot. It often takes a long time for drivers to find a free parking space. Low parking efficiency seriously affects the driver's parking feeling, which is an urgent problem to be solved. In view of this phenomenon, based on the analysis of the internal structure of the parking lot, this paper abstractly establishes the parking guidance data model, comprehensively considers the restrictive factors affecting the driver's parking psychology, then uses the improved Dijkstra algorithm to optimize the guidance data model, and finally finds out the optimal parking path, which greatly improves the parking efficiency and parking feeling.
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