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- Title
自动代客泊车接受度及停车选择行为影响因素分析.
- Authors
赵传林; 靳思缘; 武海娟; 丁力
- Abstract
Automated valet parking ( AVP) is an important part of driverless systems and plays an important role in alleviating urban traffic congestion. To investigate the influencing factors of acceptance and parking choice behavior of automatic valet parking, the structural equation model based on the technology acceptance model was established, using six psychological latent variables, i. e., perceived ease of use, perceived usefulness, behavioral attitude, behavioral intention, perceived risk, and trust. The random forest algorithm was used to build acceptance models considering psychological latent variables and ignoring psychological latent variables based on online survey questionnaire data. It is found that the random forest model considering psychological latent variables has higher fitting accuracy, making it more suitable for analyzing the influencing factors of automatic valet parking choice behavior. The random forest model with psychological latent variables is used to screen the variables through the out-of-bag estimation error rate, and it is found that the model has the smallest out-of-bag estimation error rate when the number of variables is 9. The selected variables are parking cost, education level, perceived risk, total travel cost, behavioral intention, trust, monthly income level, perceived ease of use, and age. These 9 variables are then included in the logistic regression to further analyze the degree of influence of each variable on the choice behavior. The parameter calibration results show that parking cost, education level, perceived risk, total travel cost, behavioral intention, trust, monthly income level, and age have significant effects on the choice behavior.
- Publication
Science Technology & Engineering, 2023, Vol 23, Issue 35, p15259
- ISSN
1671-1815
- Publication type
Article