Work

Analysis of Traffic Signs Information Volume Affecting Driver’s Visual Characteristics and Driving Safety

Year: 2022

Type: article

Abstract: To study the influence of traffic signs information volume (TSIV) on drivers' visual characteristics and driving safety, the simulation scenarios of different levels of TSIV were established, and 30 participants were recruited for simulated driving tests. The eye tracker was used to collect eye movement data under three-speed conditions (60 km/h, 80 km/h, and 100 km/h) and different levels of TSIV (0 bits/km, 10 bits/km, 20 bits/km, 30 bits/km, 40 bits/km, and 50 bits/km). Principal component analysis (PCA) was used to select indicators sensitive to the influence of TSIV on the drivers' visual behavior and to analyze the influence of TSIV on the drivers' visual characteristics and visual workload intensity under different speed conditions. The results show that the fixation duration, saccade duration, and saccade amplitude are the three eye movement indicators that are most responsive to changes in the TSIV. The driver's visual characteristics perform best at the S3 TSIV level (30 bits/km), with the lowest visual workload intensity, indicating that drivers have the lowest psychological stress and lower driving workload when driving under this TSIV condition. Therefore, a density of 30 bits/km is suggested for the TSIV, in order to ensure the security and comfort of the drivers. The theoretical underpinnings for placing and optimizing traffic signs will be provided by this work.

Source: International Journal of Environmental Research and Public Health

DOI: 10.3390/ijerph191610349

Authors: Lei Han, Zhigang Du, Shoushuo Wang, Ying Chen

Institution: Wuhan University of Technology

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Human Factors and Ergonomics

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,618