The problem every growing city and cosmopolitan faces is the unorganized approach to management of road traffic which mostly consists of daily commuters. We have focused on a part of the problem. One of the problematic agents is the clustering of cabs at certain locations which take certain routes making these geographic locations more crowded than they could bear. Also, this leads to dampening of traffic speed of major routes connecting these hotspots of pickup and drop points of passengers.
The initial apporach to the solution lies in the identification of these hotspots which cause the clustering of cabs. After we have analysed these hotspots in a demographic area, we will be having a fair idea of origin of significant traffic within a given time frame as well as the termination of the same. Now here lies the key point of our problem, at these hotspots there are more number of cabs present than any other location and at the same time frame there is a drop point which will be hosting more cabs than any other location. The picture becomes clearer when we have a dataset that provides us with data of a pair-wise pickup points and drop points. So, basically the hotspots identified exist in pairs of pickup locations and their respective drop points. So, the routes connecting these pair of points shall be hosting maximum traffic at those hours. The amount of cabs on these routes make up the most of traffic congestion on these routes.
The obvious solution to this problem is the reduction of cabs to increase traffic speed and free these routes by replacing them with appropriate options. These options could have a very wide range depending upon the dataset provided and party of interest. Whoever the implementer be, one thing is for sure that identification of replacing these extra traffic generating elements would drastically have an effect on the environment, mainly in terms of reduced pollution level, cost-effeciency of daily and inevitable commute and the reduced time spent on the same, hence resulting in increased productivity of both the consumer, as they would be spending less time being stuck in traffic and more in activities requiring more attention as well as time, and the service providing agency as they will be spending less capital in terms of burning fuel, maintenance of less vehicles etc. These service providers could be anyone like the cab companies who want to come up with more eco-friendly and cost-efficient options to provide service to their customers, or the government who could channel their public transport on routes that require more attention than the ones where these transports are not used as much.