Evidence map›Paper›PMID 39409291›Full record

ArticleSensors (Basel, Switzerland)2024

Study on the Driver Visual Workload in High-Density Interchange-Merging Areas Based on a Field Driving Test.

Yue Zhang, Pei Jiang, Siqi Wang, Shuang Cheng, Jin Xu, Yawen Liu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

6 authors.

Yue ZhangCollege of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China.
Pei JiangShenzhen General Integrated Transportation and Municipal Engineering Design & Research Institute Co., Ltd., Shenzhen 518003, China.
Siqi WangChangsha BYD Automobile Co., Ltd., Changsha 410019, China.
Shuang ChengShenzhen General Integrated Transportation and Municipal Engineering Design & Research Institute Co., Ltd., Shenzhen 518003, China.
Jin XuCollege of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China.
Yawen LiuShenzhen General Integrated Transportation and Municipal Engineering Design & Research Institute Co., Ltd., Shenzhen 518003, China.

Funding

Chongqing University Innovation Research Group Project Grant No. CXQT21022the National Natural Science Foundation of China Grant No. 52172340
6 · The paper itself

Abstract

A visual workload model was constructed to determine and evaluate drivers' visual workload characteristics in high-density interchange-merging areas. Five interchanges were selected, and a real-vehicle driving test was conducted with 47 participants. To address the differences in drivers' visual characteristics in the interchange cluster merging areas, the Criteria Importance Through Intercriteria Correlation (CRITIC) objective weighting method was employed. Six visual parameters were selected to establish a comprehensive evaluation model for the visual workload in high-density interchange-merging areas. The results show that the average scanning frequency and average pupil area change rate are most strongly correlated with the visual workload, whereas the average duration of a single gaze has the lowest weight in the visual workload assessment system. Different driver visual workloads were observed depending on the environment of the interchange-merging areas, and based on these, recommendations are proposed to decrease drivers' workload, thereby increasing road safety.

Indexed as

Automobile DrivingWorkloadAdultEye MovementsFemaleHumansMaleYoung Adultdriving behavioreye movementhigh-density interchangeroad engineeringtraffic safetyvisual workload

Identifiers

PMID39409291
PMCPMC11479118

What OpenQuestion holds

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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.