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A platform for research: civil engineering, architecture and urbanism
Driver cognitive workload estimation: a data-driven perspective
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.
Driver cognitive workload estimation: a data-driven perspective
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.
Driver cognitive workload estimation: a data-driven perspective
Yilu Zhang, (author) / Owechko, Y. (author) / Jing Zhang, (author)
2004-01-01
567966 byte
Conference paper
Electronic Resource
English
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