Driver-vehicle-environment system characterization using statistical analyses

The paper shows that multiple correspondence analysis (MCA) is well suited to characterize the driver-vehicle-environment system. First, the complexity of this system is explained. Then partial models of this system are exposed followed by characterizing the methods. Among these methods, MCA has the required features to reveal what are the most relevant variables that could better characterize the system and to associate variable value tendencies with functioning modalities of the system. An example of MCA applied to characterize four driving situations is given.