Evidence map›Paper›PMID 40982563›Full record

ArticlePloS one2025

A fusion safety and security analysis framework for intelligent and connected vehicles.

Bin Sun, Shichun Yang, Yu Wang, Jiayi Lu, Zhaowen Pang, Xinjie Feng, Haoran Guang, Yaoguang Cao

Abstract read
In one paragraph

Article in PloS one, 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

8 authors.

Bin SunSchool of Transportation Science and Engineering, Beihang University, Beijing, China.ORCID https://orcid.org/0009-0008-4998-0974
Shichun YangSchool of Transportation Science and Engineering, Beihang University, Beijing, China.
Yu WangSchool of Transportation Science and Engineering, Beihang University, Beijing, China.
Jiayi LuInnovation Center of New Energy Vehicle Digital Supervision Technology and Application for State Market Regulation, Beijing, China.
Zhaowen PangSchool of Information and Communication Engineering, Hainan University, Haikou, China.
Xinjie FengSchool of Transportation Science and Engineering, Beihang University, Beijing, China.
Haoran GuangSchool of Transportation Science and Engineering, Beihang University, Beijing, China.
Yaoguang CaoState Key Lab of Intelligent Transportation System, Beihang University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Driven by advancements in emerging technologies and data-driven innovations, the global automotive industry is focusing on intelligent and connected vehicles (ICVs), which involve complex electronic systems and vast data interactions. Safety concerns have expanded beyond traditional safety measures to include functional safety, safety of the intended functionality (SOTIF), and cybersecurity. Despite their interconnected nature, current methods often address these domains separately, risking incomplete safety assessments. This paper introduces a fusion safety analysis method that evaluates the three domains collectively. By identifying safety attributes and mapping unsafe behaviors to hazardous scenarios, it quantitatively assesses integrated safety risks. An illustrative case study on adaptive cruise control (ACC) highlights the method's effectiveness, stressing the importance of addressing multi-dimensional safety issues to enhance ICVs safety.

Indexed as

AutomobilesSafetyAccidents, TrafficComputer SecurityHumans

Identifiers

PMID40982563
PMCPMC12453215

What OpenQuestion holds

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LicenceCC BY
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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.