Gautam Gupta

A Mixed Integer Linear Program for Airport Departure Scheduling

A mixed integer linear program is presented for deterministically scheduling departure aircraft at runways. The method addresses different schemes of managing the departure queuing area by treating it as first -in-first-out queues or as a simple parking area, wher e any available aircraft can take-off irrespective of its relative sequence with others. The method explicitly considers separation criteria between successive departures and also incorporates an optional prioritization scheme using time windows. Multiple objectives pertaining to throughput, system delay and maximum individual delay are used. Results indicate minimizing system delay alone improves throughput over a basic first -come-first-serve rule. Modifications for computational efficiency are also presented in the form of re-formulating certain constraints and defining additional inequalities for better bounds.

Managing departure aircraft release for efficient airport surface operations

This paper presents a model for managing departure aircraft at the spot or gate on the airport surface. The model is applied over two time frames: long term (one hour in future) for collaborative decision making, and short term (immediate) for decisions regarding the release of aircraft. The purpose of the model is to provide the controller a schedule of spot or gate release times optimized for runway utilization. This model was tested in nominal and heavy surface traffic scenarios in a simulated environment, and results indicate average throughput improvement of 10% in high traffic scenarios even with up to two minutes of uncertainty in spot arrival times.

A Concept and Implementation of Optimized Operations of Airport Surface Traffic

This paper presents a new concept of optimized surface operations at busy airports to improve the efficiency of taxi operations, as well as reduce environmental impacts. The suggested system architecture consists of the integration of two decoupled optimization algorithms. The Spot Release Planner provides sequence and timing advisories to tower controllers for releasing departure aircraft into the movement area to reduce taxi delay while achieving maximum throughput. The Runway Scheduler provides take-off sequence and arrival runway crossing sequence to the controllers to maximize the runway usage. The description of a prototype implementation of this integrated decision support tool for the airport control tower controllers is also provided. The prototype decision support tool was evaluated through a human-in-the-loop experiment, where both the Spot Release Planner and Runway Scheduler provided advisories to the Ground and Local Controllers. Initial results indicate the average number of stops made by each departure aircraft in the departure runway queue was reduced by more than half when the controllers were using the advisories, which resulted in reduced taxi times in the departure queue.

Incorporating Active Runway Crossings in Airport Departure Scheduling

A mixed integer linear program is presented for deterministically scheduling departure and arrival aircraft at airport runways. This method addresses different schemes of managing the departure queuing area by treating it as first-in-first-out queues or as a simple par king area where any available aircraft can take-off ir respective of its relative sequence with others. In addition, this method explicitly considers separation criteria between successive aircraft and also incorporates an optional prioritization scheme using time windows. Multiple objectives pertaining to throughput and system delay are used independently. Results indicate improvement over a basic first-come-first-serve rule in both system delay and throughput. Minimizing system delay results in small deviations from optimal throughput, whereas minimizing throughput results in large deviations in system delay. Enhancements for computational efficiency are also presented in the form of reformulating certain constraints and defining additional inequalities for better bounds.

An Integrated Collaborative Decision Making and Tactical Advisory Concept for Airport Surface Operations Management

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. There have been attempts to address the resulting inefficiencies with both strategic and tactical tools for metering departure aircraft. This paper presents Spot And Runway Departure Advisor with Collaborative Decision Making (SARDA-CDM): an integrated strategic and tactical system for improving surface operations by metering departure aircraft. SARDA-CDM is the augmentation of ground and local controller advisories through sharing of flight movement and related operations information between airport operators, flight operators and air traffic control at the airport. The goal is to enhance the efficiency of airport surface operations by exchanging information between air traffic control and airline operators, while minimizing adverse effects on stakeholders and passengers. The paper presents the concept of operations for SARDA-CDM, describing both the strategic and tactical components. Then the preliminary results from testing the concept in a real-time automated simulation environment are described. Results indicate benefits such as reduction in taxiing delay and fuel consumption. Further, the preliminary implementation of SARDA-CDM seems robust for two minutes delay in gate push-back times.

Effect of Uncertainty on Deterministic Runway Scheduling

Active runway scheduling involves scheduling departures for takeoffs and arrivals for runway crossing subject to numerous constraints. This paper evaluates the effect of uncertainty on a deterministic runway scheduler. The evaluation is done against a firstcome-first-serve scheme. In particular, the sequence from a deterministic scheduler is frozen and the times adjusted to satisfy all separation criteria; this approach is tested against FCFS. The comparison is done for both system performance (throughput and system delay) and predictability, and varying levels of congestion are considered. The modeling of uncertainty is done in two ways: as equal uncertainty in availability at the runway as for all aircraft, and as increasing uncertainty for later aircraft. Results indicate that the deterministic approach consistently performs better than first-come-first-serve in both system performance and predictability.

Spot Release Planner: Efficient Solution for Detailed Airport Surface Traffic Optimization

The Spot Release Planner (SRP) is an algorithm previously developed by the authors to reduce delay and congestion on the airport surface. The algorithm was developed to provide real time advisories to tower controllers. A Human-in-the-loop (HITL) simulation in April 2010 showed that the SRP reduced the average movement area delay of departure aircraft by 64%. The SRP is a two-stage algorithm that considers runway scheduling in the rst stage, and the rest of the ground movement, such as gate pushback and spot release, in the second stage. This decomposition of airport surface scheduling into two stages provides fast computational times and makes the SRP applicable for real-time decision making. However, the two stages also result in the given scheme being a heuristic for solving the complicated airport surface scheduling problem; no guarantees on quality of the obtained solution have been provided. This paper explores the quality of solutions obtained by the SRP and compares them with the optimal solution for airport surface trac. Simulations conducted for the East side of Dallas/Fort Worth International Airport (DFW) show that the SRP solutions are within 14s of the optimal solution for a detailed airport surface planner.

Robot Experiment Analysis of Airport Ramp Area Time Constraints

Improvement in airport operations using optimization schemes has been an active research area in the recent years. Particular attention has been given to improve taxiway and runway queue operations. However, once these operations are improved by an efficient taxiway schedule, its execution relies on the planning of ramp-area aircraft movements. An important step in the integration of the taxiway schedule with the planning of ramp-area aircraft maneuvers is to understand the constraints imposed on the aircraft trajectories due to the geometry of ramp-area and aircraft kinematics. Data for ramp trajectories are usually unavailable. To address this, we use an inexpensive scaled-down robot experiment to collect some critical data about aircraft trajectories. Ramp movement trajectories are then modeled by stochastic processes since they are heavily dependent on the human operator. We use the stochastic model to analyze the relationship between aircraft pushback time intervals and ramp-area conflicts. We then discuss constraints that can be imposed on aircraft pushback intervals to avoid any conflicts among trajectories.

Predictability in Airport Surface Operation Management

The performance of airport surface operations has usually been assessed with respect to delay, capacity and efficiency. Although predictability as a performance measure is recognized by stakeholders as an important goal, predictability metrics have not been defined for airport surface operations. This paper aims to fill that gap by using data from NASA’s Spot and Runway Departure Advisor (SARDA) human-in-the-loop simulations in 2012 to study airport operations predictability. Using the simulation data, we measure and compare predictability on the airfield with and without SARDA from three perspectives: controllers’ perspective, flight operator’s perspective and traffic management perspective. The controller survey results indicate the perception that SARDA reduces controller’s workload surges and has the potential to better handle off-nominal situations. By studying taxi-out time in both baseline and advisory runs, it is found that SARDA reduces variability in total taxi-out time and eliminates uncertainty in taxi-out time sooner into the taxi-out process. Moreover, SARDA enables more accurate predictions of wheels-off time through use of a linear regression model. There is no evidence indicating that SARDA causes more deviation from First-Scheduled-First-Served as compared to the non-SARDA case. Instead, SARDA improves First-In-First-Out performance in the queue area.

Cost -effective Sampling to Evaluate Condition of Un -staffed Facilities in National Airspace System

This paper proposes a methodology to evaluate the condition of un -staffed facilities in the infrastructure assets of the National Airspace System (NAS). The NAS contains around 5,000 un -staffed facilities and 9,000 structural towers. NAS facilities are very diverse in terms of their type, construction, size, geographic location, environment and the traffic area they serve. Given the significant number and the diversity of these facilitie s, assessing their performance and condition at an aggregate level is a challenging proposition. Specifically, systematic assessment of each facility in order to establish a comprehensive database is extremely expensive. We review sampling techniques previ ously developed and identify the advantages and disadvantages of each. We then propose a two -stage sampling methodology, which provides an adequate representative of the whole population. The current state -of -the -art in assessing facility condition and per formance is not very advanced. For certain type of facilities, only preliminary estimates have been made. Given (i) a large number and variety of facilities, (ii) the high cost of maintaining and updating a facility wide database for inspection and mainten ance of facilities and (iii) the budget constraints for FAA, this research will provide FAA with a cost effective method to assess its various un -staffed facilities.