<ul><li>A data-driven system has been developed to understand and predict traffic patterns in Bangalore, providing alternative route recommendations for commuters.</li><li>Using a publicly available dataset from Kaggle with 17,000 rows called Bangalore’s Traffic Pulse, a reliability index was calculated to measure road stability and volatility.</li><li>The roads were categorized based on metrics related to speed deviation and congestion deviation, leading to the calculation of a Route Risk Score that balances traffic pain and unpredictability.</li><li>Personalized route recommendations are provided to users based on their preferences, such as prioritizing predictability over traffic pain, enhancing the commuting experience in Bangalore.</li></ul>

Case Study: Smart Route Recommender for Bangalore Traffic

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