A Low Emissions Taxi Movement Planning Tool

The goal of this research project was to develop and test an online, automated taxi movement planning tool, that optimizes the timed taxiing routes of all aircraft on an airport, by minimizing the impact on the environment. Automatic taxi planning tools have been developed before, but the emissions have never been included before as a factor in the optimal taxi planning. Since the tool is to be used in real-time in an operational context, the daily operations of airports have been analyzed and the tool has been tailor-made to meet the operational requirements. In order to cope with perturbations on the taxiway grid, the tool is capable of optimizing a taxi planning within 15 seconds. This way, a new planning can be calculated quickly if there are perturbations on the taxiway grid. The objective function comprises the following criteria: • Minimization of the emissions (normalized and weighted in the objective function) • For departures: minimization of the absolute deviation from the departure slot time • For arrivals: minimization of the taxiing time (normalized in the objective function) The mixed integer linear programming (MILP) methodology has been used to formulate and solve the problem. The formulation in this research project uses binary routing variables and continuous timing variables. This way, the routing and scheduling problem can be solved without the disadvantages of discrete time. The emissions of nitrogen oxides (NOx), carbon monoxide (CO), unburned hydrocarbons (UHC), carbon dioxide (CO2) and particulate matter (PM) are included in the optimization. The developed optimizer minimizes those five emissions, along with fuel burn, delays for departures and taxiing times for arrivals. The environmental variables are modeled using an action-based model, in which the emissions caused by accelerating, idling during a hold, taxiing at constant speed and turning have been modeled. The developed tool has been subjected to a comprehensive test case. The test case simulated a full day of flights on a major European hub: Amsterdam Airport Schiphol. The output of each emission type increased with only 1 to 2 percent, in comparison to the theoretical optimum (which is a scenario where each flight would be able to travel its optimal, unimpeded route, unhindered by separation constraints). When the emission optimization criteria were switched off (while keeping the objective criteria of arrivals taxiing time and departure slot time deviation), the output of each emission type increased with around 20 to 25 percent, in comparison to emission-enabled optimization. The computational times remained within limits, so the requirement was met of having the ability to do a replanning every 15 seconds. The environmental benefit of using this type of optimizer is estimated to be around 10 to 20 percent per emission type. The reduction can be attributed to the elimination of the buffering and waiting queues in front of runways, the elimination of holds at nodes and the intelligent overall routing, timing, sequencing and scheduling on the taxiway grid. Therefore, this research project proves that a surface movement planning tool, which minimizes the emissions or the total taxiing time, can be valuable for airports that have dense taxiing traffic and stringent environmental requirements.

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