  Public transport is one of the major forms of transportation in the world.
This makes it vital to ensure that public transport is efficient. This research
presents a novel real-time GPS bus transit data for over 500 routes of buses
operating in New Delhi. The data can be used for modeling various timetable
optimization tasks as well as in other domains such as traffic management,
travel time estimation, etc. The paper also presents an approach to reduce the
waiting time of Delhi buses by analyzing the traffic behavior and proposing a
timetable. This algorithm serves as a benchmark for the dataset. The algorithm
uses a constrained clustering algorithm for classification of trips. It further
analyses the data statistically to provide a timetable which is efficient in
learning the inter- and intra-month variations.
