Lighting a Path for Autonomous Vehicle Communication: The Effect of Light Projection on the Detection of Reversing Vehicles by Older Adult Pedestrians

Brian Mason (), Sridhar Lakshmanan (), Pam McAuslan, Marie Waung and Bochen Jia
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Brian Mason: College of Engineering and Computer Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Sridhar Lakshmanan: College of Engineering and Computer Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Pam McAuslan: College of Arts, Sciences, and Letters, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Marie Waung: College of Arts, Sciences, and Letters, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Bochen Jia: College of Engineering and Computer Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA

IJERPH, 2022, vol. 19, issue 22, 1-15

Abstract: Pedestrian understanding of driver intent is key to pedestrian safety on the road and in parking lots. With the development of autonomous vehicles (AVs), the human driver will be removed, and with it, the exchange that occurs between drivers and pedestrians (e.g., head nods, hand gestures). One possible solution for augmenting that communication is an array of high-intensity light-emitting diodes (LEDs) to project vehicle-to-pedestrian (V2P) messages on the ground plane behind a reversing vehicle. This would be particularly beneficial to elderly pedestrians, who are at particular risk of being struck by reversing cars in parking lots. Their downward gaze and slower reaction time make them particularly vulnerable. A survey was conducted to generate designs, and a simulator experiment was conducted to measure detection and reaction times. The study found that elderly pedestrians are significantly more likely to detect an additional projected message on the ground than detect the existing brake light alone when walking in a parking lot.

Keywords: elderly pedestrian; gerontology; parking lot; autonomous vehicle; V2X; automotive lighting; human-centered design; downward gaze; vehicle intent; pedestrian instruction (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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