Graph mining for the detection of overcrowding and waste of resources in public transport
The imbalance between the quantity of supply and demand in public transport systems causes a series of disruptions in large metropolises. While extremely crowded vehicles are uncomfortable for passengers, virtually empty vehicles generate economic losses for system managers, and this usually comes back to passengers in the form of fare increases. Here a new methodology will be presented for the evaluation of collective transportation systems. It proposes the construction and mining of graphs that represent complex networks of supply and demand of the system to find such global imbalances.
The class responsible for selecting the stretches of the network with bottlenecks is "IdentifyBottleneckNetwork". It receives as input two networks: one in which the weights of the edges represent the supply, and the other the weights represent the demand. The procedure to be performed is to identify the segments of supply bottlenecks (where it has more demand than supply, in which it impairs passenger comfort) and the demand bottleneck segments (where it has more supply than demand, in which there is a loss for bus companies). For the supply bottlenecks, the edges are selected in which the difference of the weights of the edges of the supply network with the demand network is smaller than an overload indicator (SI). For the demand bottlenecks, the similar process is performed, the edges are selected in which the difference of the weights of the edges of the supply network with the demand network is smaller than a waste indicator (ID).