Abstract
The Problem. High-fidelity driving simulators can generate a great deal of data. Traditional analytical techniques are useful and can provide answers across different treatment conditions. However, more complex analytical tools are needed to provide insights into variations in driver performance that occur within a treatment level or as drivers transition from one treatment level to the next. Role of Driving Simulators. Studies conducted in driving simulators provide greater control than studies in an on-road or naturalistic driving setting. Even if the data is collected with the same level of detail as naturalistic studies, the information related to drivers’ performance is much greater given that the same safety situation under the same scenarios can be observed multiple times. Key Results of Driving Simulator Studies. Researchers who acquire knowledge related to various analytical tools will be able to compare and contrast differences such that the appropriate insights can be gained on crash causation or safety factors, rather than merely correlations and associations. Scenarios and Dependent Variables. This chapter provides information on how to analyze various dependent variables (including speed, time-to-collision, accelerator release time) across different scenarios and is therefore not specific to any dependent variable or scenario. Platform Specificity and Equipment Limitations. The tools described in this chapter can be used across all simulator platforms and are not restricted by limitations of the apparatus.
| Original language | English (US) |
|---|---|
| Title of host publication | Handbook of Driving Simulation for Engineering, Medicine, and Psychology |
| Publisher | CRC Press |
| Pages | 21-1-21-14 |
| ISBN (Electronic) | 9781420061017 |
| ISBN (Print) | 9781138074583 |
| State | Published - Jan 1 2011 |
Keywords
- Analysis of Variance
- Complex Designs
- Multivariate Techniques
- Regression Models
ASJC Scopus subject areas
- General Engineering