Kumar, Bhaiya Vaibhaw (International Institute of Information Technology, Hyderabad), Rawat, Deepti (International Institute of Information Technology), Kandalla, Tanvi (Mahindra University), Nagariya, Aarnav (IIIT Hyderabad), Vemuri, Kavita (International Institute of Information Technology, Hyderabad)

MyEye2Wheeler: A Two-Wheeler Indian Driver Real-World Eye-Tracking Dataset

Scheduled for presentation during the Poster Session "Transportation Data Analysis and Calibration" (FrAT17), Friday, September 27, 2024, 10:30−12:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 8, 2024

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.