Research on the impact of driving environment complexity on driving safety based on Driver Sky View Index (DSVI)

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.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-05-08
DOI
https://doi.org/10.1371/journal.pone.0347999
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the impact of driving environment complexity on driving safety based on Driver Sky View Index (DSVI)

Ayin Yan, Ying He, Duoting Su, Li Quan et al.
PLoS ONE
Traffic and Road Safety
article

Research on the impact of driving environment complexity on driving safety based on Driver Sky View Index (DSVI)

Ayin Yan, Ying He, Duoting Su, Li Quan, Yuan Chen
article en

Abstract

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.

PLoS ONEVol. 21(5)
Chongqing University (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 6%
Traffic and Road Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.