An investigation of operational management solutions and challenges for electric taxiing of aircraft

Taxiing aircraft using electric towing vehicles (ETVs) is expected to significantly contribute to the objective of climate-neutral aviation by 2050. This study reviews existing work on operational aspects of electric towing of aircraft, and discusses management solutions. We first discuss the varying electric taxi systems currently under development, and their implementation progress at airports. We outline the current specifications of ETVs and the procedures needed to perform electric taxiing movements. We next discuss the management needs for implementing ETVs at an airport, by reviewing existing mathematical models for ETV fleet management: dedicated vehicle routing models, ETV to flight assignment models, fleet sizing models and battery charging optimisation models. Last, we identify remaining research challenges. For instance, a main challenge is to increase the robustness of ETV routing and towing scheduling against disruptions due to flight delay. This paper summarizes the main research directions needed to support large-scale ETV implementation in the next few decades

Dispatching a fleet of electric towing vehicles for aircraft taxiing with conflict avoidance and efficient battery charging

Following the Paris Accords, the aviation industry aims to become climate neutral by 2050. In this line, electric vehicles that tow aircraft during taxiing are a promising emerging technology to reduce emissions at airports. This paper proposes an end-to-end optimization framework for electric towing vehicles (ETVs) dispatchment at large airports. We integrate the routing of the ETVs in the taxiway system where minimum separation distances are ensured at all times, with the assignment of these ETVs to aircraft towing tasks and scheduling ETV battery recharging. For ETV recharging, we consider a preemptive charging policy where the charging times depend on the residual state-of-charge of the battery. We illustrate our model for one day of operations at a large European airport. The results show that the 913 arriving and departing flights can be towed with 38 ETVs, with battery charging distributed throughout the day. The fleet size is shown to increase approximately linear with the number of flights in the schedule. We also propose a greedy dispatchment of the ETVs, which is shown to achieve an optimality gap of 6% with respect to the number of required vehicles and with 22% with respect to the maximum delay during towing. We also show that both algorithms can be leveraged to account for flight delays using a rolling horizon approach, and that over 95% of the flights can be reallocated if delays occur. Overall, we propose a roadmap for ETV management at large airports, considering realistic ETV specifications (battery capabilities, kinematic properties) and requirements for aircraft collision avoidance during towing

The Influence of Traffic Structure on Airspace Capacity

Best paper award for the Network Management trackInternational audienceAirspace structure can be used as a procedural mechanism for a priori separation and organization of en-route air traffic. Although many studies have explored novel structuring methods to increase en-route airspace capacity, the relationship between the level of structuring of traffic and airspace capacity is not well established. To better understand the influence of traffic structure on airspace capacity, in this research, four airspace concepts, representing discrete points along the dimension of structure, were compared using large-scale simulation experiments. By subjecting the concepts to multiple traffic demand scenarios, the structure-capacity relationship was inferred from the effect of traffic demand variations on safety, efficiency and stability metrics. These simulations were performed within the context of a future personal aerial transportation system, and considered both nominal and non-nominal conditions. Simulation results suggest that the structuring of traffic must take into account the expected traffic demand pattern to be beneficial in terms of capacity. Furthermore, for the heterogeneous, or uniformly distributed, traffic demand patterns considered in this work, a decentralized layered airspace concept, in which each altitude band limited horizontal travel to within a predefined heading range, led to the best balance of all the metrics considered

The Efficacy of Operational Bird Strike Prevention

Involving air traffic controllers and pilots into the bird strike prevention process is considered an essential step to increase aviation and avian safety. Prior to implementing operational measures such as real-time warning systems, it is vital to evaluate their feasibility. This paper studies the efficacy of a bird strike advisory system for air traffic control. In addition to the potential safety benefit, the possible impact on airport operations is analyzed. To this end, a previously developed collision avoidance algorithm underlying the system was tested in fast-time Monte Carlo simulations involving various air traffic and bird densities to obtain representative conclusions for different operational conditions. The results demonstrate the strong safety potential of operational bird strike prevention in case of precise bird movement prediction. Unless airports operate close to their capacity limits while bird abundance is high, the induced delays remain tolerable. Prioritization of hazardous strikes involving large individuals as well as flocks of birds are expected to support operational feasibility in all conditions

Analysis of Risk-Based Operational Bird Strike Prevention

Bird strike prevention in civil aviation has traditionally focused on the airport perimeter. Since the risk of especially damaging bird strikes outside the airport boundaries is rising, this paper investigates the safety potential of operational bird strike prevention involving pilots and controllers. In such a concept, controllers would be equipped with a bird strike advisory system, allowing them to delay departures which are most vulnerable to the consequences of bird strikes in case of high bird strike risk. An initial study has shown the strong potential of the concept to prevent bird strikes in case of perfect bird movement prediction. This paper takes the research to the next level by taking into account the limited predictability of bird tracks. As such, the collision avoidance algorithm is extended to a bird strike risk algorithm. The risk of bird strikes is calculated for birds expected to cross the extended runway center line and to cause aircraft damage upon impact. By specifically targeting these birds and excluding birds lingering on the runway which are taken care of by the local wildlife control, capacity reductions should be limited, and the implementation remain feasible. The extrapolation of bird tracks is performed by simple linear regression based on the bird positions known at the intended take-off times. To calculate the probability of collision, uncertainties resulting from variability in bird velocity and track are included. The study demonstrates the necessity to limit alerts to potentially damaging strikes with birds crossing the extended runway center line to keep the imposed delays tolerable for airports operating at their capacity limits. It is shown that predicting bird movements based on simple linear regression without considering individual bird behavior is insufficient to achieve a safety-effect. Hence, in-depth studies of multi-year bird data to develop bird behavior models and reliable predictions are recommended for future research. This is expected to facilitate the implementation of a bird strike advisory system satisfying both safety and capacity aspects

Designing for safety: The free flight air traffic management concept

This paper describes the conceptual design and validation of an air traffic management (ATM) concept and the role the safety and human factors played in this design and validation process. The free flight (FF) concept is characterised by being a direct route concept where the pilots, instead of the air traffic controller, are responsible for the separation assurance. Moving this task to the cockpit has consequences for the man machine interface in the cockpit, which needs to be modified to accommodate this new task (micro level design). On top of that, a set of rules and procedures are required to ensure an efficient and safe traffic flow (macro level design). Both the micro and macro aspect of this design are intertwined and require an accurate tuning to arrive at an overall acceptable solution. Both micro-level (flight simulator) experiments and macro-level (traffic simulations) experiments have been conducted to investigate the feasibility of this concept after optimising the initial conceptual design

Electric Taxiing with Disruption Management: Assignment of Electric Towing Vehicles to Aircraft

Reducing aircraft taxiing emissions will deliver a significant contribution to the worldwide goal of net-zero greenhouse gas emissions in the aviation industry. Replacing jet-engine taxiing by towing aircraft with electric towing vehicles is expected to reduce taxiing emissions by roughly80%. Introducing a fleet of towing vehicles introduces operational challenges to an airport. Although there has been research focused on optimizing the assignment of vehicles to aircraft, such an assignment will require changes during a day of operations, when disruptions such as flight delays occur. This paper proposes two models, a strategic and a disrupted model, with which an adaptive vehicle-to-aircraft assignment is created. The models are formulated as Mixed Integer Linear Problems, and both maximize the number of towed aircraft and minimize the schedule changes for vehicle operators. The approach illustrated includes vehicle and aircraft routing, conflict avoidance, and a model for energy usage. We apply the models to Amsterdam Airport Schiphol, where the disrupted model is able to create assignments that remain the same in subsequent time steps for an average of 55% of the vehicles, on a busy day, when towing all aircraft. Furthermore, the results show that minimizing schedule changes does not come at the expense of fewer towed aircraft, i.e. of smaller emission savings. Lastly, we investigate the impact of fleet size and general on-time performance on the assignments created by the model

Improving Algorithm Conflict Resolution Manoeuvres with Reinforcement Learning

Future high traffic densities with drone operations are expected to exceed the number of aircraft that current air traffic control procedures can control simultaneously. Despite extensive research on geometric CR methods, at higher densities, their performance is hindered by the unpredictable emergent behaviour from surrounding aircraft. In response, research has shifted its attention to creating automated tools capable of generating conflict resolution (CR) actions adapted to the environment and not limited by man-made rules. Several works employing reinforcement learning (RL) methods for conflict resolution have been published recently. Although proving that they have potential, at their current development, the results of the practical implementation of these methods do not reach their expected theoretical performance. Consequently, RL applications cannot yet match the efficacy of geometric CR methods. Nevertheless, these applications can improve the set of rules that geometrical CR methods use to generate a CR manoeuvre. This work employs an RL method responsible for deciding the parameters that a geometric CR method uses to generate the CR manoeuvre for each conflict situation. The results show that this hybrid approach, combining the strengths of geometric CR and RL methods, reduces the total number of losses of minimum separation. Additionally, the large range of different optimal solutions found by the RL method shows that the rules of geometric CR method must be expanded, catering for different conflict geometries

The Transition Towards Free Flight: A Human Factors Evaluation of Mixed Equipage, Integrated Air-Ground, Free Flight ATM Scenarios

This paper describes the initial results of a simulation experiment in which the human factors implications of three Mixed Equipage, Integrated Air-Ground, Free Flight Air Traffic Management (ATM) scenarios were investigated. The experiment primarily addressed how to accommodate a fleet of mixed equipped aircraft, with and without Airborne Separation Assurance System (ASAS), in a transitional free flight era in which both air and ground players have defined responsibilities. All three transitional ATM operational concepts evaluated, were designed with the idea that equipping aircraft should be immediately beneficial to the airlines

NASA Langley and NLR research of Distributed Air/Ground Traffic Management

Distributed Air/Ground Traffic Management (DAG-TM) is a concept of future air traffic operations that proposes to distribute information, decision-making authority, and responsibility among flight crews, the air traffic service provider, and aeronautical operational control organizations. This paper provides an overvie