Existing congestion metrics often fail to capture disparities across road types in rapidly urbanizing cities like Nagpur, necessitating an evaluation of time-based and speed-based measures for effective traffic management. This study investigates the relationship between time-based and speed-based congestion metrics on Nagpur’s road network, utilizing real-time traffic data collected via the TomTom Routing API (Application Programming Interface). The methodology involves data collection for various road segments, including flyovers, main roads, and service roads, during peak hours. Mathematical validation confirmed a strong correlation between the two metrics, with disparities observed across different road types. Results indicate that service roads exhibit higher disparities due to frequent interruptions, while flyovers demonstrate more consistent traffic flow. This research underscores the importance of selecting appropriate congestion metrics for targeted urban traffic management. These findings can inform the development of targeted interventions to alleviate congestion on service roads and optimize traffic management strategies.