Real-Time Traffic Management
The growth in transport demand of the lasts years is a trend expected to continue in the future, requiring the concerned stakeholders to find adequate answers. In particular, both in railways and air traffic this demand growth and the difficulties in building new infrastructures due to economic and physical constraints translates into the need of utilizing the existing network at full capacity, even at peak hours. An efficient timetable has to be computed for each day, which is an increasingly difficult task on its own. These timetables though may not be feasible when implemented. In fact, during the daily operations, disturbances may happen, changing the expected occupation times of tracks. Even if buffer times are provided, time-overlapping requests for the same resources might be made by multiple vehicles. Traffic dispatchers and aircraft controllers are required to answer these requests. Currently, the decisions are manually made, not allowing to fully evaluate their effects. Some may lead to future delays, which in turn may create new conflicting requests, causing in a worst-case scenario cancellations. The Air Traffic Flow Management in a Terminal Control Area and the Real-Time Railway Traffic Management problems are the formalization of respectively the dispatchers and controllers’ decision problem. Whole streams of research focus on these problems, where increasingly realistic models are being utilized while keeping the computation time of the algorithms utilized to find good quality solution at an acceptable level.
We utilize to model these problems on a microscopic level of detail the alternative graph formulation. Also, a rolling horizon framework is introduced to simplify the management of large and highly disturbed traffic time horizons. Various optimization-based approaches have been developed to optimize the resolution of time-overlapping requests based on different meta-heuristics. Also, since there in no clear agreement in the literature on which objective functions to use due to the different operational aspects and points of view of the multiple stakeholders involved, we have performed an analysis on how they influence each others. Decisions support systems have been developed to help dispatchers and controllers in taking informed decisions.
Various hypothetical disturbance scenarios are simulated for real case study and the proposed timing and routing solutions are compared in terms of their performance in the different scenarios. In general, the optimization approaches are found to improve the solutions significantly compared to a First In First Out heuristic, which simulates dispatchers and controllers decision.
References
Samà M., D’Ariano A., Pacciarelli D. (2013) Rolling Horizon Approach For Aircraft Scheduling In The Terminal Control Area Of Busy Airports. Transportation Research, Part E, 60 (1) 140-155.
Samà M., D’Ariano A., D’Ariano P., Pacciarelli D. (2014) Optimal aircraft scheduling and routing at a terminal control area during disturbances. Transportation Research Part C, 47 (1) 61-85
D’Ariano A., Samà M., D’Ariano P., Pacciarelli D. (2014) Evaluating the applicability of advanced techniques for practical real-time train scheduling. Transportation Research Procedia 3 279–288
