On Improving Operational Planning and Control in Public Transportation Networks using Streaming Data: A Machine Learning Approach”
; João Mendes-Moreira, JMM
; Gama, J.G.
On Improving Operational Planning and Control in Public Transportation Networks using Streaming Data: A Machine Learning Approach”, Proc European Conf. on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML/PKDD, Nancy, France, Vol. 1, pp. 41 - 50, September, 2014.
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Nowadays, transportation vehicles are equipped with intelligent
sensors. Together, they form collaborative networks that broadcast
real-time data about mobility patterns in urban areas. Online intelligent
transportation systems for taxi dispatching, time-saving route finding
or automatic vehicle location are already exploring such information in
the taxi/buses transport industries. In this PhD spotlight paper, the authors
present two ML applications focused on improving the operation
of Public Transportation (PT) systems: 1) Bus Bunching (BB) Online
Detection and 2) Taxi-Passenger Demand Prediction. By doing so, we intend to give a brief overview of the type of approaches applicable to these type of problems. Our frameworks are straightforward. By employing online learning frameworks we are able to use both historical and real-time data to update the inference models. The results are promising.