Real Time Re-routing of Public Transportation System

Nowadays, many cities are on the verge of becoming smart cities. A smart transportation system is at the heart of smart city but cities lag with an efficient transport system. The current public transport systems follows static routing based approach i.e. they have fixed routes and frequency irrespective of the demand. In this paper, we propose an innovative method to solve this problem by rerouting the bus on-the-go based on public demand. Public can interact, manipulate and have an effect on the routing of the buses. The interaction of the public demand with routing is enabled by a central server which will analyses all the demand data collected from booking application. To facilitate the on-demand nature, a dynamic routing algorithm has been proposed that prepares new route for buses in real time. This algorithm works in the cloud server and suggests new and more efficient routes based on the aggregated data collected. This is enabled by the city wide link of equi-important bus depots which serve as loci of control for routing and rerouting. After evaluating, the system shows tremendous performance gain in regions with highly skewed bus-demand. Further, we propose this model to be implemented in public transport systems as a 30 - 70 percent combination of static and dynamic routing respectively for easier adaptation by the commuters.