Evidence map›Paper›PMID 40872039›Full record

ArticleSensors (Basel, Switzerland)2025

Driving Behavior of Older and Younger Drivers in Simplified Emergency Scenarios.

Yun Xiao, Mingming Dai, Shouqiang Xue

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

3 authors.

Yun XiaoSchool of Urban Construction and Transportation, Hefei University, Hefei 230606, China.ORCID 0000-0001-6142-7292
Mingming DaiSchool of Urban Construction and Transportation, Hefei University, Hefei 230606, China.ORCID 0009-0006-9050-4633
Shouqiang XueSchool of Urban Construction and Transportation, Hefei University, Hefei 230606, China.ORCID 0009-0001-6935-7097

Funding

Anhui Provincial Natural Science Foundation 2208085ME147
6 · The paper itself

Abstract

This study focuses on exploring the differences in driving abilities in emergency traffic situations between older drivers (aged 60-70) and young drivers (aged 20-35) in a simple traffic environment. Two typical emergency scenarios were designed in the experiment: Scenario A (intrusion of electric bicycles) and Scenario B (pedestrians crossing the road). The experiment employed a driving simulation system to synchronously collect data on eye movement characteristics, driving behavior, and physiological metrics from 30 drivers. Two-factor covariance analysis, correlation analysis, and regression analysis were conducted on the experimental data. The comprehensive study results indicated that the older group exhibited better driving performance in emergency scenarios compared to the younger group. Specifically, in Scenario A, the older group had a faster first fixation time on the AOI compared to the younger group, a faster braking reaction time, a higher maximum brake pedal depth, and a higher skin conductance level. In Scenario B, the older group's driving performance was similar to that in Scenario A, with better performance than the younger group. The study reveals that in some simple driving tasks, young-old drivers (60-70 years) can compensate for their physiological decline through self-regulation and self-restraint, thereby exhibiting safer driving behaviors.

Indexed as

Automobile DrivingAccidents, TrafficAdultAgedAge FactorsEmergenciesEye MovementsFemaleHumansMaleMiddle AgedReaction TimeYoung Adultdriving characteristicdriving performanceemergency traffic situationseye movementolder drivers

Identifiers

PMID40872039
PMCPMC12390459

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.