Evidence map›Paper›PMID 42892795›Full record

ArticleCognition, technology & work (Online)2026

Hazard perception in manual and hands-off Level 2 driving under daytime and after dark lighting conditions: A driving simulator study.

Yee Thung Lee, Rafael C Gonçalves, İbrahim Öztürk, Albert Solernou, Karl Proctor, Natasha Merat

Abstract read
In one paragraph

Article in Cognition, technology & work (Online), 2026. 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

6 authors.

Yee Thung LeeInstitute for Transport Studies, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT UK.
Rafael C GonçalvesInstitute for Transport Studies, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT UK.
İbrahim ÖztürkInstitute for Transport Studies, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT UK.
Albert SolernouInstitute for Transport Studies, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT UK.
Karl ProctorJaguar Land Rover, Coventry, UK.
Natasha MeratInstitute for Transport Studies, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to examine drivers' hazard perception in an urban scene, under two different lighting conditions (daytime and after dark) and for two different levels of driving automation (manual driving and hands-off SAE level 2 automation). Forty-eight participants took part in four experimental drives in a driving simulator, encountering six different hazardous/potentially hazardous events in each drive. Results showed that drivers detected hazards significantly earlier and were more likely to react to the hazards in daytime, compared to after dark environments, particularly when pedestrians were approaching the road from the left. However, there was no significant difference in their response time towards the hazards, between the daytime and after dark environments. In terms of driver response in the two automation levels, the majority of drivers were proactive and reacted before the potentially hazardous events turned into actual hazards during manual driving, but responses were more reactive during automated driving. These findings highlight the need to account for context of the driving environment such as lighting conditions and levels of driving automation when designing systems or protocols that aim to support hazard perception and timely driver response.

Indexed as

After dark drivingDaytime drivingHands-off L2 automationHazard perceptionManual driving

Identifiers

PMID42892795
PMCPMC13675288

What OpenQuestion holds

Textmetadata
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.