Monitoring Driver's Authority: Simulator Study

Abstract

In this paper, a multimodal adaptive driver assistance system is studied on a simulator setup. The main goal is to determine human driver's attention and authority level in a cognitive model and to trigger timely warnings according to his/her driving intents and driving skills with respect to the possible driving situation and hazard scenarios. In the previous studies, a fairly restrictive vision-based driver assistance system has been deployed to detect lane departure, blind-spot and to monitor following distance, headway time. The presented system models driving task in a cognitive architecture and assesses the cognition of the human driver by modeling the situation awareness of the driver by using fuzzy sets. Each fuzzy set simply represents the expert driver's perception in both of the longitudinal and lateral traffic. The presented system evaluates the driver's driving skills and attention level by comparing the expert and human driver's reactions suited in a finite set of decision and maneuvering task. In case of hazard analysis, the system triggers timely warnings pointing the driver's attention at the lateral or longitudinal maneuvering tasks depending on the interpreted situation. Introductory experiments are performed with a limited number of participants, the test driving data including the driver's perception and reaction to the surrounding vehicles and traffic situations are collected by the use of vehicle simulator. And the presented multimodal adaptive driver assistance system is evaluated by the simulator. The preliminary results seem to be promising.