Maha’s research project deals with the real-time management fleet vehicle routing problem from the perspective of the exploitation of big data. Currently, extraction of useful information from big data represents a major information technology challenge. The method that we want to develop aim to exploit historical and real-time data collected from multiple sources such as sensors on the roads, video cameras, GPS probe vehicle, space-based navigation system in the vehicles, etc. to build a model that can predict travel times in real-time. Historical big data will also be used to better predict the occurrence of new requests during the day of operations. These predictive models are then integrated in the optimization procedure to make real-time decisions.
Real-time management of a fleet of vehicles allows greater responsiveness to contingencies that occur over time as the occurrence of new requests, road accidents, traffic congestion, etc. A Better decision making becomes possible, as is the ability to take proactive actions.