Accident-preventive Measure Selection Method based on the Speed Cognition of Lead-vehicle Driver in Curved Roadway

Yotsutsuji, Hirofumi; Kita, Hideyuki; Kitamura, Kazuki

doi:10.1016/j.sbspro.2014.07.243

Cited by 2 publications

(1 citation statement)

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“…In order to improve traffic safety on curved roads, Yotsutsuji et al (2014) focused on the model research of drivers' cognitions to lead-vehicle speeds on curves [9]. Compared to the text symbols, colored ones bring stronger and faster impact on human vision.…”

Section: Introductionmentioning

confidence: 99%

A Sensor-Based Visual Effect Evaluation of Chevron Alignment Signs’ Colors on Drivers through the Curves in Snow and Ice Environment

Zhao

et al. 2017

Journal of Sensors

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The ability to quantitatively evaluate the visual feedback of drivers has been considered as the primary research for reducing crashes in snow and ice environments. Different colored Chevron alignment signs cause diverse visual effect. However, the effect of Chevrons on visual feedback and on the driving reaction while navigating curves in SI environments has not been adequately evaluated. The objective of this study is twofold: (1) an effective and long-term experiment was designed and developed to test the effect of colored Chevrons on drivers' vision and vehicle speed; (2) a new quantitative effect evaluation model is employed to measure the effect of different colors of the Chevrons. Fixation duration and pupil size were used to describe the driver's visual response, and Cohen's d was used to evaluate the colors' psychological effect on drivers. The results showed the following: (1) after choosing the proper color for Chevrons, drivers reduced the speed of the vehicle while approaching the curves. (2) It was easier for drivers to identify the road alignment after setting the Chevrons. (3) Cohen's d related to different colors of Chevrons have different effect sizes. The conclusions provide evident references for freeway warning products and the design of intelligent vehicles.

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Section: Introductionmentioning

confidence: 99%