Evidence map›Paper›PMID 40658745›Full record

ArticlePloS one2025

A comprehensive accident investigation system for assisted driving vehicles: Addressing complexities in fault determination and responsibility allocation.

Yanbin Hu, Wenhui Zhou

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

2 authors.

Yanbin HuResearch Institute for Road Safety of the Ministry of Public Security, Beijing, China.ORCID https://orcid.org/0009-0003-4648-5517
Wenhui ZhouResearch Institute for Road Safety of the Ministry of Public Security, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China's autonomous vehicle accidents, fault determination has grown increasingly complex due to the undefined legal status of autonomous driving systems. To assign responsibility accurately, it is crucial to consider the system's autonomy and decision-making capabilities. Furthermore, the lack of specialized technical equipment and software for data collection, analysis, and processing hinders rapid and precise problem identification, impacting accident handling efficiency and accuracy. To address this, a tailored comprehensive accident investigation system for assisted driving vehicles has been developed. This system comprises subsystems for traffic accident boundary analysis, control action safety analysis, causal scene restoration, and investigation report output. It systematically extracts accident evidence, analyzes causes, traces hidden hazards, and determines responsibility. By integrating these subsystems, the system offers a structured and comprehensive framework for intelligent vehicle accident investigations, enhancing overall efficiency and clarity.

Indexed as

Accidents, TrafficAutomobile DrivingAutomobilesChinaHumans

Identifiers

PMID40658745
PMCPMC12258604

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.