A quantitative evaluation method of ambient environment complexity of parking space for automatic parking system
For boosting the success rate of automatic parking,a quantitative evaluation model of parking space environment complexity is established.An index system is established with seven indica-tors,such as parking space type and parking space line attributes,and the corresponding quantitative characterization method is proposed.In view of the problem that the subject-objective combination weight assignment method cannot correctly calculate the critical index weight of a single sample,a more reliable one based on square summation normalization is proposed on the basis of analytic hierar-chy process(AHP).The fuzzy comprehensive evaluation method is applied to solve the complexity of the car parking environment.The proposed model is validated through designed simulation tests.The results show that compared with the AHP combined with entropy weight method,the proposed method can correctly assign larger weights to critical determinants,while avoiding invalid weight assignments.Furthermore,the proposed model can correctly reflect the changes of parking space environment complexity,providing a feasible new path for automatic selection of parking spaces.
intelligent transportationautomatic parking systemactive selection of parking spacesfuzzy comprehensive evaluationanalytic hierarchy process
万方数据
维普
