Supporting Left-Turn Safety: Evaluating Ecological Augmented Reality Head-Up Display Interfaces in Dynamic Traffic Scenarios

With the increasing adoption of augmented reality head-up displays (AR-HUDs) in vehicles, there is a growing need for effective interface design to support driver performance in complex traffic scenarios. While AR-HUDs offer advantages over traditional heads-up displays by presenting dynamic, context-relevant information, they may also increase cognitive load and introduce safety concerns. This study investigates the effectiveness of an ecological interface design (EID) method applied to AR-HUDs for unprotected left turns. Two experiments were conducted, assessing subjective evaluations, behavioral performance, and eye movement metrics. Experiment 1 compared ecological, virtual traffic light, and no interface conditions, while Experiment 2 explored the consistency of ecological interface effects under varying speeds of oncoming traffic. The results indicate that the ecological interface significantly improved drivers’ subjective experience, decision-making speed, and safe turning rates. In addition, it enhanced search efficiency and reduced distraction. However, an interaction effect between vehicle speed and interface presence revealed that ecological interfaces may amplify the perceptual effect of environmental variables. These findings provide practical guidance for the development of AR-HUD systems, emphasizing the value of EID while highlighting the need for balanced integration with environmental cues.

Authors

Institutions

Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2026-05-10
DOI
https://doi.org/10.1177/03611981261443198
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Supporting Left-Turn Safety: Evaluating Ecological Augmented Reality Head-Up Display Interfaces in Dynamic Traffic Scenarios

Hui Li, Z Q 梓骞 Yang 杨, Chenglong Jiang, Weidan Xu et al.
Transportation Research Record Journal of the Transportation Research Board
Human-Automation Interaction and Safety
article

Supporting Left-Turn Safety: Evaluating Ecological Augmented Reality Head-Up Display Interfaces in Dynamic Traffic Scenarios

Hui Li, Z Q 梓骞 Yang 杨, Chenglong Jiang, Weidan Xu, Cailu Guo
article en

Abstract

With the increasing adoption of augmented reality head-up displays (AR-HUDs) in vehicles, there is a growing need for effective interface design to support driver performance in complex traffic scenarios. While AR-HUDs offer advantages over traditional heads-up displays by presenting dynamic, context-relevant information, they may also increase cognitive load and introduce safety concerns. This study investigates the effectiveness of an ecological interface design (EID) method applied to AR-HUDs for unprotected left turns. Two experiments were conducted, assessing subjective evaluations, behavioral performance, and eye movement metrics. Experiment 1 compared ecological, virtual traffic light, and no interface conditions, while Experiment 2 explored the consistency of ecological interface effects under varying speeds of oncoming traffic. The results indicate that the ecological interface significantly improved drivers’ subjective experience, decision-making speed, and safe turning rates. In addition, it enhanced search efficiency and reduced distraction. However, an interaction effect between vehicle speed and interface presence revealed that ecological interfaces may amplify the perceptual effect of environmental variables. These findings provide practical guidance for the development of AR-HUD systems, emphasizing the value of EID while highlighting the need for balanced integration with environmental cues.

Transportation Research Record Journal of the Transportation Research Board
Zhejiang Sci-Tech University (CN), Zhejiang University of Technology (CN), East China Normal University (CN), Zhejiang Gongshang University (CN)
Openalex Percentile: Top 3%
Human-Automation Interaction and Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.