Sample Size Study of Driving Simulator Experiment for Freeway Design Safety Evaluations

Abstract

Driving Simulator, a powerful simulation tool, has already been used in safety evaluation of roadway geometric design during the pre-construction design stage. Conventional ways of estimating proper sample size include the empirical method, the resource equation, power analysis, and the Bayesian method. However, significant boundaries and prior distributions of operational indices are hard to identify in simulator studies, which makes it difficult to use conventional ways in choosing the acceptable sample size. This study proposes an empirical method to infer proper sample size. The Tongji University eight-degree-of-freedom driving simulator was utilized to collect continuous driving behavior data from a simulated mountainous freeway. Vehicle speed and lane departure events were selected as the indices to measure the influence of geometric design features on operational efficiency and safety. A mixed linear model and a mixed logistic regression model were used to assess the relationships between geometric design features and vehicle speed and lane departure. Random sampling was used to choose 10 samples of 5 to 50 drivers from a total of 55 drivers. Acceptable sample size was determined based on the parameter coefficient convergence elbow points of the mean squared error (MSE) curves of significant variables. The clear elbow points of the MSE curves indicate that 30 is an acceptable sample size.