earticle

영어

A correct understanding of hospital parking characters and parking behavioral regularities is very important to hospital parking planning, making parking management measures and improving the utilization of parking lot. The existing researches in parking behavior concentrate on parking behavior in central area, and the researches on hospital parking behavior are still not deep. Besides, the research methods mainly adopt disaggregate model which only considers driver’s observable manifest variables, neglecting the influence of mental latent variables on the results of parking choice, so the model’s explanatory ability is weakened. Aiming at the hot issue - hospital parking problem, based on the analysis of hospital parking character, this paper puts forward the latent variables of hospital parking mode choice. By improving the utility function of traditional ML disaggregate model, establishing three kinds of SEM-ML integration model which could describe car drivers’ characteristic manifest variables and subjective mental latent variables, and then applying examples to make comparison and analyze. The results show that: Compared with traditional ML model, the SEM-ML model has a better accuracy and explanatory ability. Among the three models, the SEM-ML3 integration model could describe the relationship between latent variables and manifest variables, latent variables and observable variable by structural equation, so it has a better accuracy and explanatory capability. The results validate that manifest variables (parking purpose) and mental latent variables (convenient level and feelings of parking) have effects on hospital parking mode choice. According to the analysis results, this paper proposes corresponding suggestions on planning and managing hospital parking from three aspects: convenience, comfort and safety.