Optimized Stockholm Traffic
An ongoing project aimed at optimizing traffic flow in Stockholm using AI and mathematical modeling to reduce congestion and improve urban mobility.
- Goals: Develop algorithms to predict and optimize traffic patterns, integrating real-time data for efficient routing and signal control.
- Tech: Python, TensorFlow/PyTorch for ML models, NetworkX for graph-based simulations, Pandas/NumPy for data analysis.
- Outcomes: Preliminary models show 15-20% reduction in simulated travel times; exploring integration with real Stockholm traffic APIs for deployment.