An AI-Driven Unified Model for Traffic Sign and Lane Detection in Dynamic Road Environments

Key Points

• The research aims to evaluate the effectiveness of an AI-driven unified model for detecting traffic signs and lanes in dynamic environments.
• AI-driven model applied in traffic sign and lane detection tasks.
• Evaluation conducted in dynamic road environments.
• Comparison of performance metrics against traditional methods.
• AI model achieved a detection accuracy of 92% for traffic signs.
• Lane detection improved by 15% compared to baseline models.
• Statistical analysis revealed p=0.003, indicating significance.