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.

Effect of Motion Cues on Highway Driving Performance in Simulated Driving

“…Participants were required to drive at least 3000 km annually and to have driven at least 10,000 km in total. Wang et al conducted a study on acceptable sample size of participants, based on the same driving scenario and apparatus as this study ( 32 ). The clear convergence of the mean squared error curves of significant variables indicate that 30 is an acceptable sample size.…”

A user study of directional tactile and auditory user interfaces for take-over requests in conditionally automated vehicles

“…2) In factorial designs, the traditional methods for determining the appropriate sample size (power analysis) drastically underestimate the required sample needed to power an interaction (Bartlett, 2019). Wang et al had proposed a novel method to estimate sample size based on the mean squared error curve and determined that 30 drivers should be the acceptable sample size for driving safety evaluation studies in driving simulators (Wang et al, 2019). A limitation of our study design is that while repeated measures do increase the power for within-subject effects and interactions, the power for between-subject variables decreases compared to completely random designs with the same number of participants (Donmez et al, 2006).…”