Optimal Parking Path Planning and Parking Space Selection Based on the Entropy Power Method and Bayesian Network: A Case Study in an Indoor Parking Lot

According to the vehicle dynamics model and requirements of reliable safety minimal time, path planning problem parking in different types spaces is solved by obstacle avoidance analysis motion case optimal solution, trajectory from initial position designated space obtained. In static situation, are occupied; analyze type, left right occupancy distance between vacant starting point location unoccupied cars; establish attribute information matrix R0 calculate KMO value R0. This completed determine weak correlation attributes use as original evaluation entropy weight method, using method three space. These results weighted selection process, difficulty score determined, determined through ranking scores. dynamic case, number usage will change over with help Bayesian network, existing lot at previous moment learned according computer clock, which can be used reason about availability next moment. The weights updated a space, then new select situation. optimized could contribute enhancing efficiency for sustainable management indoor lots.