Motorcycle Conspicuity: Effects of Age and Daytime Running Lights

Author:

Al-Awar Smither Janan1,Torrez Lorenzo I.2

Affiliation:

1. University of Central Florida, Orlando,

2. Microsoft Corporation, Redmond, Washington

Abstract

Objective:This study investigated variables that may contribute to motorcycle conspicuity within a high-fidelity simulated environment. The variables included motorcycle lighting, vehicular daytime running lights (DRLs), and age of the driver of the other vehicle. Background: Research suggests that decreased levels of conspicuity associated with riding a small two-wheeled vehicle reduce the ability of other drivers to detect and respond to that vehicle effectively. This lack of conspicuity is often responsible for the frequent injuries and fatalities incurred by motorcycle riders. Method: The 75 participants who took part in this study watched a series of video clips of roadway traffic and were asked to indicate when they saw a hazardous situation, such as the presence of pedestrians, motorcycles, or traffic cones. Both motorcycle and following-vehicle lights were manipulated, and participant reaction times were collected and analyzed. Results: Analyses indicated main effects for all three variables as well as interaction effects between motorcycle lighting and vehicle-following conditions. Overall, findings showed a link between DRLs and the effective detection of motorcycles and suggested that age-related changes affect the ability to detect and respond to a motorcycle effectively. Conclusion: Although our laboratory findings corroborated previous correlational studies, further research in real-world settings, such as those with high-density traffic or under adverse environmental conditions, needs to be conducted. Application: Potential applications of this research include the assessment of appropriate lighting technology to enhance conspicuity of motorcycles and reduce the high rate of fatalities and injuries related to motorcycle crashes.

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

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