Exploring the injury severity of unlicensed powered two- and three-wheeler drivers in two-vehicle crashes in China.

Peixiang Xu, Fulu Wei, Dong Guo, Yongqing Guo, Lizu Sun, Chuan Liu, Bin Zhou

Abstract read

In one paragraph

Article in Scientific reports, 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

7 authors.

Peixiang Xu *School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China.

Fulu Wei *School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China. weifulu@sdut.edu.cn.

Dong GuoSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China.

Yongqing GuoSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China.

Lizu SunSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China.

Chuan LiuSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, 255000, China.

Bin ZhouState Key Lab of Intelligent Transportation System, Beijing, 100000, China.

Funding

Natural Science Foundation of Shandong Province,China ZR2024MG014SDUT & Zibo City Integration Development Project 2022JS005Shandong Provincial Programme of Introducing and Cultivating Talents of Discipline to Universities: Research and Innovation Team of Intelligent Connected Vehicle Technology 2021SLG08the Project of the Open Fund of State Key Lab of Intelligent Transportation System 2024-B009

6 · The paper itself

Abstract

Large presence of unlicensed powered two- and three-wheeler (PTW) drivers in China pose a significant threat to road safety. In this study, a customized Deep Forest Model (DF-ptw) is constructed to investigate the effect of unlicensed PTW drivers on crash severity in two-vehicle crashes, using a recent 3-year historical crash data. SHapley Additive explanation (SHAP) and Partial Dependence Plot (PDP) analysis reveal that unlicensed motorcyclists are significantly more likely to suffer serious injuries in two-vehicle crashes compared to unlicensed auto-rickshaw drivers. Additionally, factors such as drunk driving, fatigued driving, and being an unlicensed driver over the age of 53 notably elevate the risk of serious injury or death, with unlicensed motorcyclists being disproportionately affected. Moreover, self-employed unlicensed PTW drivers face a higher probability of serious injury or fatality in crashes compared to farmers, blue-collar, and white-collar workers. Unlicensed PTW drivers are also more susceptible to severe or fatal injuries on national and provincial roads, in low visibility conditions, during late-night hours, on non-separated roads, and at dusk or dawn. Based on these findings, this study proposes to reduce the frequency and severity of crashes involving unlicensed PTW drivers by focusing on more stringent eligibility checks, increasing safety awareness, and implementing advanced safety measures.

Indexed as

Accidents, TrafficAutomobile DrivingMotorcyclesWounds and InjuriesAdultAgedChinaFemaleHumansMaleMiddle AgedRisk FactorsYoung AdultMachine learningPowered two- and three-wheelerTwo-vehicle crashUnlicensed driver

Identifiers

PMID40189638

DOI10.1038/s41598-025-88896-3

PMCPMC11973215

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.