Driver cognitive workload estimation: a data-driven perspective

Yilu Zhang · Y. Owechko · Jing Zhang

69 citations0/0 files storedIEEE International Conference on Intelligent Transportation Systems (ITSC)

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Human-Automation Interaction and Safety Context-Aware Activity Recognition Systems Sleep and Work-Related Fatigue

Abstract

Driver workload estimation (DWE) refers to the activities of monitoring a driver and the driving environment in real-time and acquiring the knowledge of the driver's workload continuously. With this knowledge of the driver's workload, the in-vehicle information systems (IVIS) can provide information on when the driver has the spare capacity to receive and comprehend it, which is both effective and efficient. However, after years of study, it is still difficult to build a robust DWE system. In this paper, we analyze the difficulties facing the existing methodology of developing DWE systems and propose a machine-learning-based DWE development process. Some preliminary but promising results are reported using a popular machine-learning method, the decision tree.

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References

2015Engineering Psychology and Human Performance 2014The Atomic Components of Thought 1999The Atomic Components of Thought 1976Engineering Psychology and Human Performance 2003Mental workload while driving: Effects on visual search, discrimination, and decision making.2000Effects of verbal and spatial-imagery tasks on eye fixations while driving.2002Graphical models for driver behavior recognition in a SmartCar 1986The model human processor: An engineering model of human performance.

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