Margdarshak: A Mobile Data Analytics based Commute Time Estimator cum Route Recommender

Waiting at traffic signals and getting stuck in traffic congestion eats a lot of time for a commuter in most of the metro cities of the world. Although there exists a large pool of navigation applications, but all of them turn out to be ineffective for dynamically finding out the best route under uncertainty. In this work, we present Margdarshak, a navigation system which utilizes the impact of congestion and wait time at traffic signals for estimating the travel time over a route. We collected a month-long traffic data from different routes at five various cities in India for analyzing the problem in detail. The evaluations performed over the system show that Margdarshak gives a mean estimation error of ±1.5$ minutes, and performs significantly better under uncertainty, compared to other state of the art navigation systems like Google Maps, Here Maps and Waze.