Electric Aircraft Platoons Could Slash Costs Without Overloading Air Traffic Controllers

A formation of battery-powered aircraft gliding in single file through a dedicated low-altitude corridor sounds like science fiction, but a new mathematical study argues it could be the key to making urban air mobility economically viable. Researchers at Concordia University in Montreal have developed an optimal control framework that allows strings of all-electric aircraft to fly as coordinated platoons while simultaneously minimizing operating costs and keeping the burden on air traffic management under control. The work, published in the journal Aerospace Systems, bridges two concerns that have usually been treated separately: the economics of electric flight and the cognitive load that dense traffic imposes on controllers and automated systems.

The study, authored by Lucas Souza e Silva and Luis Rodrigues of the Department of Electrical and Computer Engineering, addresses a gap that has widened as electric propulsion matures. Aircraft such as the Pipistrel Velis Electro and the GreenWing E430 have demonstrated that battery-driven flight is technically feasible, yet the promise of advanced and urban air mobility depends on flying many vehicles through constrained airspace safely and cheaply. Platooning, a concept borrowed from highway research where vehicles travel in closely spaced strings, offers one path: by coordinating airspeeds and separations, followers can respond smoothly to their predecessors, reducing both energy waste and the coordination effort needed to keep everyone apart.

The core challenge the researchers tackle is a fundamental trade-off. Flying faster burns more energy in a quadratic drag relationship but shortens flight time, and operators weight these effects differently depending on scheduling pressure and electricity pricing, a tension captured in airline practice by the cost index. Meanwhile, the tighter a platoon packs its aircraft, the less airspace it occupies, but the more attention each individual vehicle requires to maintain safe separation. To quantify this second, harder-to-measure quantity, the team introduced a novel construct they call the pairwise dynamic workload function, which assigns a continuous numerical value to the coordination effort between each follower aircraft and the one immediately ahead of it.

Technically, the pairwise dynamic workload grows as the separation between two aircraft shrinks and as their closing speed increases, reflecting the intuition that a rapidly approaching aircraft demands more of a controller’s or autopilot’s attention than one drifting lazily along. By embedding this workload term directly into the cost function of an optimal control problem, the researchers made airspace complexity a first-class objective, one that can be traded off against operational cost rather than treated as an afterthought. The formulation tracks each follower’s position, airspeed and remaining battery charge, and it enforces a hard constraint that inter-aircraft separation never falls below a minimum safe distance.

Solving this problem rigorously required the machinery of Pontryagin’s minimum principle, the classical tool of optimal control theory. The authors derived the complete optimal cruise airspeed profile for follower aircraft in a predecessor-follower platoon of all-electric vehicles flying under longitudinal wind disturbances, carefully handling the moments when the separation constraint becomes active. The analysis distinguishes three regimes: when aircraft are comfortably separated, when a follower first reaches the minimum safe distance, and when it must lock its speed to that of its predecessor for an extended interval. At the transition points, the mathematics produces characteristic jumps in the costate variables, which the paper resolves using established results on state-constrained optimal control.

Because the fully optimal solution involves coupled equations that can be computationally demanding, the team also derived an analytical suboptimal solution for heterogeneous platoons, that is, strings composed of different aircraft types with nonlinear dynamics. This closed-form approximation is the workhorse result of the paper, because it can be evaluated quickly enough for onboard implementation while remaining provably close in performance to the true optimum. Crucially, the authors did not stop at approximation: they formally established a general sufficient condition guaranteeing string stability, the property that disturbances, such as a gust or a leader’s speed change, do not amplify as they propagate backward along the chain of aircraft.

String stability is the concept that separates a useful platoon from a dangerous one. In an unstable string, a small speed correction by the lead aircraft grows into an ever-larger correction by each follower behind it, eventually producing wild oscillations in spacing that no air traffic system could tolerate. The phenomenon has been studied extensively in road vehicle platooning, where spacing policies and communication delays determine whether disturbances attenuate or magnify, and it has been examined for aircraft formations and for interval management procedures in conventional airspace. By proving a sufficient condition under which their suboptimal control law remains string stable even for heterogeneous, nonlinear, wind-perturbed electric aircraft, the Concordia team gives airspace designers a certificate of safety rather than a hope of one.

The framework was validated through case studies of all-electric aircraft operating in air corridors designed for low-altitude advanced and urban air mobility. The results show that the suboptimal analytical solution closely tracks the fully optimal one, while maintaining separations above the safety boundary, preserving string stability, and delivering meaningful reductions in both operating cost and airspace complexity compared with uncoordinated flight. Because the model accounts for battery state of charge and the nonlinear drag characteristics of electric propulsion, the computed cruise speeds represent genuinely achievable energy plans rather than idealized ones, an important distinction given that battery depletion directly constrains the range and reserve margins of electric vehicles.

Beyond its immediate technical contributions, the research points toward a broader shift in how emerging aviation will be managed. The authors frame their findings as a step toward sustainable, more autonomous air traffic procedures, in which aircraft assume much of the separation responsibility themselves, freeing human controllers and automation to supervise flows at the corridor level. Such autonomy is widely seen as a prerequisite for scaling advanced air mobility, since projected traffic densities in urban skies would overwhelm conventional control paradigms. By building workload and complexity metrics directly into the flight control loop, the framework offers regulators a quantitative language for deciding how much autonomy is safe, and for operators a principled way to weigh the savings of tight platooning against the coordination costs it creates.

The work also connects to a growing literature on energy-efficient formation flight, optimal cruise scheduling for hybrid and electric aircraft, and multi-agent conflict resolution, synthesizing strands that have developed largely in parallel. Its combination of rigorous optimality analysis, certified stability, and practical applicability to realistic urban air mobility corridors distinguishes it from studies that address only one of these facets. As electric aircraft multiply and dedicated low-altitude corridors move from concept documents to regulated airspace, tools of this kind, which make the cost of coordination explicit and controllable, are likely to become part of the standard design toolkit. The Montreal study, funded by the Fonds de Recherche du Québec and the Natural Sciences and Engineering Research Council of Canada, demonstrates that the future of clean urban flight may depend less on any single breakthrough in batteries than on the quiet mathematics of keeping aircraft in safe, stable, and economical formation.

The intellectual lineage of the new framework stretches back further than electric aviation itself. Automated formation flight was being analyzed in the early 1990s, when researchers demonstrated control laws for aircraft flying in close formation, and the concept of string stability was subsequently formalized in the intelligent highways community, most visibly through the California PATH program, which spent two decades developing and testing coordinated vehicle strings. That literature established the now-standard insight that the choice of spacing policy, and the delays in the communication channel linking neighbors, jointly determine whether a platoon dampens or amplifies disturbances. The Concordia study imports this analytical heritage into a domain where the spacing policy must also respect battery limits and the specific drag characteristics of electric propulsion.

The workload side of the formulation likewise draws on a mature body of air traffic research. Metrics such as dynamic density, developed at NASA in the late 1990s, and earlier frameworks for evaluating controller complexity attempted to capture how difficult a traffic situation is for the human managing it, well before any aircraft could coordinate autonomously. Recent reporting on controller fatigue and staffing shortfalls has underlined why such measures matter: as traffic grows, the marginal cost of each additional aircraft is not fuel but attention. By expressing that attention as a pairwise, dynamically evolving quantity embedded in the aircraft’s own cost function, the new work effectively moves a concept once reserved for ground-side capacity planning into the onboard optimization loop.

The choice of a predecessor-follower architecture also echoes current FAA thinking. Interval management procedures built on ADS-B In already ask equipped aircraft to achieve and maintain a spacing interval relative to a designated aircraft, and the agency’s urban air mobility concepts of operations envision corridor-based operations in which responsibility for separation is distributed between ground automation and the vehicles themselves. A provably string-stable platoon law can be read as the aircraft-level complement to such trajectory-based procedures, offering the attenuation guarantees that interval management studies have long sought.

For electric aircraft specifically, the framework complements recent work on minimum-energy cruise for advanced air mobility vehicles, extending the energy question from a single aircraft to a coordinated string. Because electric propulsion couples tightly with battery state of charge, and because charging infrastructure will remain scarce in early deployments, coordinated airspeed scheduling that reduces energy demand per flight may prove as consequential for urban air mobility economics as any improvement in cell chemistry.

Subject of Research: Optimal control of string-stable platoons of all-electric aircraft balancing operating costs and airspace complexity

Article Title: String-stable platoons of all-electric aircraft with operating costs and airspace complexity trade-off

Article References: Souza e Silva, L., & Rodrigues, L. (2026). String-stable platoons of all-electric aircraft with operating costs and airspace complexity trade-off. Aerospace Systems. https://doi.org/10.1007/s42401-026-00542-6

Image Credits: AI Generated

DOI: 10.1007/s42401-026-00542-6

Keywords: all-electric aircraft, platooning, string stability, optimal control, urban air mobility, airspace complexity, operating cost, battery-electric aviation, air traffic management, predecessor-follower control, Pontryagin minimum principle, advanced air mobility