Evidence map›Paper›PMID 42346319›Full record

ArticleJournal of eye movement research2026

Active Vision in Driving: Joint Modeling of Scanpaths and Risk Perception.

Chao Gou, Yueyao Lin, Yuchen Zhou, Wenjie Shi, Jincheng Jiang

Abstract read
In one paragraph

Article in Journal of eye movement research, 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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.

Chao GouSchool of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0002-4128-886X
Yueyao LinSchool of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0009-0008-3505-5948
Yuchen ZhouSchool of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0002-2470-0293
Wenjie ShiSchool of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0009-0006-4297-9562
Jincheng JiangSchool of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0001-5522-6910

Funding

National Natural Science Foundation of China JCYJ20240813151301003
6 · The paper itself

Abstract

Under the Active Vision hypothesis, eye movements are not passive responses to visual stimuli but are actively guided by task demands and internal goals. In driving, scanpaths may therefore reflect an ongoing process of information sampling for risk assessment. However, current computational models often isolate scanpath prediction from risk assessment, overlooking their intrinsic cognitive coupling. In this study, we investigate whether driver scanpaths and traffic risk perception can be jointly modeled within a unified framework. We propose a computational approach based on the introduced

Indexed as

active visionadversarial inverse reinforcement learningdriver scanpath predictiontraffic risk perceptionvisual search

Identifiers

PMID42346319
PMCPMC13301845

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.