Evidence map›Paper›PMID 41174083›Full record

ArticleCommunications engineering2025

Evolution mechanism and progressive reshaping model of driving behaviors when humans take over intelligent vehicles.

Ziyu Zhang, Chunyan Wang, Zhongkai Luan, Wanzhong Zhao

Abstract read
In one paragraph

Article in Communications engineering, 2025. 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

4 authors.

Ziyu Zhang *College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Chunyan Wang *College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Zhongkai LuanCollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Wanzhong ZhaoCollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. zwz@nuaa.edu.cn.ORCID http://orcid.org/0009-0001-4595-2852

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52372390National Natural Science Foundation of China (National Science Foundation of China) U24A20199
6 · The paper itself

Abstract

Despite the rapid development of autonomous driving, drivers still need to take over when autonomous driving exceeds its design scope or malfunctions. The role of drivers is undergoing a significant transformation from operators to backup users. The existing human driving behaviour models focus more on the behaviour of humans as operators, with static and time-invariant characteristics. However, as backup users, human behaviour characteristics during the takeover process exhibit dynamic and time-varying characteristics, and traditional driver models can no longer describe these, making it difficult to support the safe development of autonomous driving. Unfortunately, the evolution mechanism of driver behaviour is unclear, which has led to the continuous occurrence of accidents in autonomous vehicles. To support the safe development of autonomous driving, we studied the changes in drivers' cognition, decision-making, and control behaviours during the takeover, revealing the evolution mechanism of driver behaviours during the takeover. On this basis, a progressive reshaping model of human driving behaviours is constructed. The comparison with actual driver control data shows that the accuracy of the proposed model is 88.57%, providing a new perspective for understanding driver behaviour during emergency takeover and having certain application value in the research of autonomous driving technology.

Identifiers

PMID41174083
PMCPMC12579248

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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.