The effect of motion and signalling on drivers’ ability to predict intentions of other road users

Lee, Yee Mun; Sheppard, Elizabeth · 2016 · OpenAlex-citations

DOI: 10.1016/j.aap.2016.07.011

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Summary

This study investigates how drivers predict the intentions of approaching vehicles at junctions, specifically examining the roles of motion cues and signaling validity. Accurate prediction is critical for avoiding collisions, yet previous research relied heavily on static photographs, which may not reflect the dynamic nature of real-world driving. The authors aimed to determine if dynamic video stimuli improve judgment accuracy compared to static images, how vehicle type (cars vs. motorcycles) affects these judgments, and how valid versus invalid signals influence driver perception. The experiment utilized a 2x2x2x2 within-subjects design with 40 licensed drivers. Participants viewed stimuli of cars and motorcycles approaching a junction, either turning or driving straight, with or without indicators. Stimuli were presented as either 2-second videos or static photographs of the final frame. Signal validity was manipulated: "valid" trials matched the signal to the maneuver (e.g., turning with a signal), while "invalid" trials mismatched them (e.g., turning without a signal). Participants judged whether the vehicle would turn or go straight. Data were analyzed using signal detection theory to calculate perceptual sensitivity ($d'$) and response bias ($c$). Results indicated that drivers were significantly more accurate in judging intentions using video stimuli ($d' = 2.30$) than photographs ($d' = 1.36$). Valid signals also significantly improved accuracy ($d' = 2.83$) compared to invalid signals ($d' = 0.82$). A significant interaction between stimulus type and vehicle type revealed that drivers judged cars more accurately than motorcycles in videos, but motorcycles more accurately than cars in photographs. This suggests that dynamic cues like deceleration and trajectory are more visible for larger vehicles, while static cues like rider head orientation and vehicle tilt are more discernible for motorcycles. Additionally, drivers exhibited a response bias toward judging "turn" when signals were invalid, likely due to the higher safety cost of incorrectly assuming a vehicle will go straight. The findings highlight that dynamic information is superior for intention prediction, supporting the need for caution when interpreting motorcyclists' intentions, as drivers performed worse with motorcycles in video conditions. The study underscores the importance of valid signaling but also demonstrates that drivers can utilize alternative cues when signals are absent or misleading. These insights suggest that training and road safety interventions should account for the differences in cue availability between vehicle types and the limitations of static assessment methods.

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Topics

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• signaling behavior
• anticipation
• ehmi external hmi
• driver vru interaction
• mental model of traffic
• vru facing ehmi

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• Theoretical Contribution: computational model, theory or model