Analysis and Modeling of Speed Perception Sensitivity of Drivers on Underground Expressways

Abstract:

To explore the mechanism of the speed perception of the driver， a driving simulation experiment was designed to collect the perceived speed and actual driving speed of the driver，which analyzes the influencing factors such as the geometric alignment of the underground expressway and the side wall change frequency on the speed perception sensitivity of the driver. The prediction model of the speed perception bias sensitivity threshold of the driver was constructed based on the constant speed theory and the machine learning method. The results show that at the 0.05 significant level， there are substantial differences in the speed perception sensitivity threshold of the driver at different speeds ， linear combinations， and sidewall change frequency groups. The Lasso variable filters the characteristic variables according to the short-term， mid-long-term， and long-term time windows. The determination coefficient R² of the constructed multivariate nonlinear model is 0.645， the determination coefficient R² of the multilayer perceptron model is 0.727， and the determination coefficient R² of the support vector regression model is 0.853.