Visual Complexity of Head-Up Display in Automobiles Modulates Attentional Tunneling

Author:

Lee Jieun1,Lee Nahyun1,Ju Jangkyu1,Chae Jihwan1,Park Jiyoon2,Ryu Hoe Sung2ORCID,Cho Yang Seok1ORCID

Affiliation:

1. School of Psychology, Korea University, Seoul, Korea

2. Department of Artificial Intelligence, Korea University, Seoul, Korea

Abstract

Objective To investigate how the visual complexity of head-up displays (HUDs) influence the allocation of driver’s attention in two separate visual domains (near and far domains). Background The types and amount of information displayed on automobile HUDs have increased. With limited human attention capacity, increased visual complexity in the near domain may lead to interference in the effective processing of information in the far domain. Method Near-domain and far-domain vision were separately tested using a dual-task paradigm. In a simulated road environment, 62 participants were to control the speed of the vehicle (SMT; near domain) and manually respond to probes (PDT; far domain) simultaneously. Five HUD complexity levels including a HUD-absent condition were presented block-wise. Results Near domain performance was not modulated by the HUD complexity levels. However, the far domain detection accuracies were impaired as the HUD complexity level increased, with greater accuracy differences observed between central and peripheral probes. Conclusion Increased HUD visual complexity leads to a biased deployment of driver attention toward the central visual field. Therefore, the formulation of HUD designs must be preceded by an in-depth investigation of the dynamics of human cognition. Application To ensure driving safety, HUD designs should be rendered with minimal visual complexity by incorporating only essential information relevant to driving and removing driving-irrelevant or additional visual details.

Funder

The Korean Research Foundation Grant funded by the Korean Government

National Research Foundation of Korea, BK21 FOUR

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

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