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arXiv · 2502.12723

myEye2Wheeler: A Two-Wheeler Indian Driver Real-World Eye-Tracking Dataset

Bhaiya Vaibhaw Kumar·Deepti Rawat·Tanvi Kandalla·Aarnav Nagariya·Kavita Vemuri
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Abstract

This paper presents the myEye2Wheeler dataset, a unique resource of real-world gaze behaviour of two-wheeler drivers navigating complex Indian traffic. Most datasets are from four-wheeler drivers on well-planned roads and homogeneous traffic. Our dataset offers a critical lens into the unique visual attention patterns and insights into the decision-making of Indian two-wheeler drivers. The analysis demonstrates that existing saliency models, like TASED-Net, perform less effectively on the myEye-2Wheeler dataset compared to when applied on the European 4-wheeler eye tracking datasets (DR(Eye)VE), highlighting the need for models specifically tailored to the traffic conditions. By introducing the dataset, we not only fill a significant gap in two-wheeler driver behaviour research in India but also emphasise the critical need for developing context-specific saliency models. The larger aim is to improve road safety for two-wheeler users and lane-planning to support a cost-effective mode of transport.

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Bhaiya Vaibhaw Kumar, Deepti Rawat, Tanvi Kandalla, Aarnav Nagariya, Kavita Vemuri. 2025-02-18. myEye2Wheeler: A Two-Wheeler Indian Driver Real-World Eye-Tracking Dataset. https://arxiv.org/abs/2502.12723

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