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Articles

Maximum acceptable speed based on physiological performance for different alignments of rural roads under the influence of visibility in fog—a driving simulator study

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Pages 145-150 | Received 05 Oct 2019, Accepted 29 Jan 2020, Published online: 03 Mar 2020
 

Abstract

Objectives: The goals of this research are to: (i) investigate whether the driver’s physiological performance has a significant impact on driving speed choice, considering the visibility level under fog conditions and the horizontal and vertical alignment of a rural road; (ii) quantify the relationships among these variables; (iii) calculate the maximum acceptable speed that meets the driver’s physiological tolerance threshold.

Methods: A driving simulator study was conducted. A total of 30 participants were recruited, and each completed 5 driving simulator trials under varying visibility levels, radii of curvature and vertical grades. A multiple linear regression model was established to measure the association between normalized heart rate, driving speed, visibility, radius of curvature and gradient.

Results: The results indicated that driving speed, visibility, radius of curvature and gradient all significantly affected the normalized heart rate. For instance, an increase in driving speed and vertical grade and a reduction in the radius of curvature are related to an increase in normalized heart rate. Moreover, an acceptable speed model that considered the driver’s normalized heart rate was constructed, given the visibility level and horizontal and vertical alignment.

Conclusions: The study shows a significant correlation between the drivers’ physiological performance and his or her driving speed choice under the influence of visibility in fog. Given visibility conditions and road alignment parameters, we can calculate the maximum acceptable speed that meets the driver’s physiological requirements. Such findings should be indicative of real-time traffic management that could reduce the crash risk under inadequate visibility conditions in fog.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant No. 51878236, 51578207, 51678211, 71971073] and the Research Grants Council of Hong Kong (Project No. 25203717).

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