Evidence map›Paper›PMID 42102057›Full record

ArticlePloS one2026

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

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

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Li QuanFaculty of Chongqing Jianzhu College, Chongqing, China.
Yuan ChenFaculty of Architecture and Urban Planning, Chongqing University, Chongqing, China.
Duoting SuFaculty of Architecture and Urban Planning, Chongqing University, Chongqing, China.
Ayin YanFaculty of Architecture and Urban Planning, Chongqing University, Chongqing, China.
Ying HeFaculty of Architecture and Urban Planning, Chongqing University, Chongqing, China.ORCID https://orcid.org/0000-0002-4214-4745

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Automobile DrivingSafetyVisual FieldsAlgorithmsComputer SimulationEnvironmentEye-Tracking TechnologyFemaleHumansMaleVirtual Reality

Identifiers

PMID42102057
PMCPMC13155552

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.