With ongoing urbanization, driving environments have become increasingly complex, substantially increasing the volume of information drivers must process. To explore the impact of environmental complexity on driving safety, this study addresses the limitations of previous research in quantitatively analyzing multidimensional urban environmental factors. It introduces the Driver Sky View Index (DSVI), a visual field–based metric for quantifying environmental complexity. A method for extracting the sky view ratio was developed by integrating 3D street scene modeling with semantic segmentation, enabling a nonlinear mapping between DSVI and environmental complexity. A virtual reality simulation was employed to model nine scenarios across three road segments characterized by varying DSVI levels. Eye-tracking technology and a synchronized driving behavior recording system were used to capture visual and operational responses from 24 participants. The entropy weight–rank sum ratio (EW-RSR) composite algorithm was then applied to quantify the impact of DSVI thresholds on driving safety. The results indicate that DSVI significantly affects both driver behavior and visual characteristics, effectively reflecting how environmental complexity influences driving performance. Moreover, DSVI demonstrates a strong linear correlation with driving load (R² = 0.641, p < 0.05). Notably, when the DSVI value ranges from 0.241 to 0.397, a marked improvement in driving safety is observed. As an innovative quantitative indicator, DSVI not only facilitates the evaluation and optimization of urban traffic environments but also provides a valuable reference for enhancing driving comfort and safety.
Quan et al. (Fri,) studied this question.
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