DashCop: Automated E-ticket Generation for Two-Wheeler Traffic Violations Using Dashcam Videos

• URL: http://arxiv.org/abs/2503.00428v1
• Date: Sat, 01 Mar 2025 10:10:06 GMT
• Title: DashCop: Automated E-ticket Generation for Two-Wheeler Traffic Violations Using Dashcam Videos
• Authors: Deepti Rawat, Keshav Gupta, Aryamaan Basu Roy, Ravi Kiran Sarvadevabhatla,
• Abstract summary: We propose DashCop, an end-to-end system for automated E-ticket generation.<n>The system processes vehicle-mounted dashcam videos to detect two-wheeler traffic violations.<n>Our system demonstrates significant improvements in violation detection, validated through extensive evaluations.
• Score: 8.265943897085835
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Motorized two-wheelers are a prevalent and economical means of transportation, particularly in the Asia-Pacific region. However, hazardous driving practices such as triple riding and non-compliance with helmet regulations contribute significantly to accident rates. Addressing these violations through automated enforcement mechanisms can enhance traffic safety. In this paper, we propose DashCop, an end-to-end system for automated E-ticket generation. The system processes vehicle-mounted dashcam videos to detect two-wheeler traffic violations. Our contributions include: (1) a novel Segmentation and Cross-Association (SAC) module to accurately associate riders with their motorcycles, (2) a robust cross-association-based tracking algorithm optimized for the simultaneous presence of riders and motorcycles, and (3) the RideSafe-400 dataset, a comprehensive annotated dashcam video dataset for triple riding and helmet rule violations. Our system demonstrates significant improvements in violation detection, validated through extensive evaluations on the RideSafe-400 dataset.

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