Literature DB >> 20828672

Sensitivity of the lane change test as a measure of in-vehicle system demand.

Kristie L Young1, Michael G Lenné, Amy R Williamson.   

Abstract

The Lane Change Test (LCT) is one of the growing number of methods developed to quantify driving performance degradation brought about by the use of in-vehicle devices. Beyond its validity and reliability, for such a test to be of practical use, it must also be sensitive to the varied demands of individual tasks. The current study evaluated the ability of several recent LCT lateral control and event detection parameters to discriminate between visual-manual and cognitive surrogate In-Vehicle Information System tasks with different levels of demand. Twenty-seven participants (mean age 24.4 years) completed a PC version of the LCT while performing visual search and math problem solving tasks. A number of the lateral control metrics were found to be sensitive to task differences, but the event detection metrics were less able to discriminate between tasks. The mean deviation and lane excursion measures were able to distinguish between the visual and cognitive tasks, but were less sensitive to the different levels of task demand. The other LCT metrics examined were less sensitive to task differences. A major factor influencing the sensitivity of at least some of the LCT metrics could be the type of lane change instructions given to participants. The provision of clear and explicit lane change instructions and further refinement of its metrics will be essential for increasing the utility of the LCT as an evaluation tool.
Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

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Mesh:

Year:  2010        PMID: 20828672     DOI: 10.1016/j.apergo.2010.06.020

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  7 in total

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Review 4.  Detection-Response Task-Uses and Limitations.

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Journal:  Sensors (Basel)       Date:  2018-02-14       Impact factor: 3.576

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Authors:  Joanna Lowrie; Helen Brownlow
Journal:  BMC Public Health       Date:  2020-06-22       Impact factor: 3.295

6.  Effect of Static Magnetic Field of Electric Vehicles on Driving Performance and on Neuro-Psychological Cognitive Functions.

Authors:  Yaqing He; Weinong Sun; Peter Sai-Wing Leung; Yuk-Tak Chow
Journal:  Int J Environ Res Public Health       Date:  2019-09-12       Impact factor: 3.390

7.  Feature Selection Model based on EEG Signals for Assessing the Cognitive Workload in Drivers.

Authors:  Patricia Becerra-Sánchez; Angelica Reyes-Munoz; Antonio Guerrero-Ibañez
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  7 in total

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