Minimizing deviation from scheduled times in a single mixed-operation runway

Urban air mobility with electric Vertical TakeOff and Landing (eVTOL) vehicles is envisioned to become a fast and flexible urban transportation mode. Apart from technical challenges for eVTOLs regarding vehicle design and manufacturing, airspace design and traffic control mechanisms are most desired on the operation side. In particular, from an operational point of view, the arrival phase is expected to be the main bottleneck, with restricted vertiport resources, high air traffic density, frequent flight manoeuvres, and limited eVTOL remaining battery energy, all leading to complex operational constraints. This work provides a framework to enable optimal and efficient on-demand eVTOLS arrivals in the context of on-demand urban air mobility. We investigate the throughput of a double landing pad vertiport by proposing a new vertiport terminal area airspace design and a novel rolling-horizon scheduling algorithm with route selection capability to compute the optimal required time of arrival for eVTOLs in a tactical manner. Finally, a case study on arrivals in a hexagonal vertiport network is performed to show the algorithm performance with different configurations. Our simulation results show that up to 50 seconds delay per eVTOL is expected during the commuter peak hours and less than 10 seconds delay is expected during off-peak hours.

show abstract

“…the maximum number of position shifts from the FCFS (First-Come-First-Served) arrival sequence [27].…”

Section: Decision Variablesmentioning

confidence: 99%

Rolling-Horizon Electric Vertical Takeoff and Landing Arrival Scheduling for On-Demand Urban Air Mobility

Kleinbekman

Mitici

Wei

2020

Journal of Aerospace Information Systems

View full text Add to dashboard Cite

show abstract

“…Recently, a hybrid metaheuristic algorithm based on tabu search and variable neighbourhood search is developed by [31], which is utilized to solve a integrated aircraft scheduling and routing problem. Simulated annealing (SA) method is utilized by [2] to delivers quick schedules for a mixed-mode RSP considering the CPS constraints and the dynamic nature of airport.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In China, for example, the passenger traffic increases from 138.3 millions of 2005 to 488.0 millions of 2016 with 12.22% average annual growth rate [1]. Globally, the annual travelers total of 2018 was up by about 6.5% compared to 2017, and the traffic volume is expected to reach over 6.4 billion by 2030 [2]. The ever growing demand of air transport is growingly increasing the pressure on airport operations due to restricted airdrome capacity and air traffic controller's ability.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Runway Scheduling Problem With Partial Distribution Information of Random Parameters

et al. 2020

View full text Add to dashboard Cite

Air traffic flow management is one of the most important operations in terminal airports heavily relying on advanced intelligence transportation techniques. This work considers a two-stage runway scheduling problem given a set of flights with uncertain arrival times. The first-stage problem is to identify a sequence of aircraft weight classes (e.g., Heavy, Large and Small) that minimizes runway occupying time (i.e., makespan). Then the second-stage decision is dedicated to scheduling the flights as punctually as possible after their arrival times realized, which translates into determining a sequence of flights for each aircraft category such that the total deviation time imposed on the flights is minimized. Instead of an exactly known probability distribution, information on uncertain parameters is limited (i.e., ambiguous), such as means, mean absolute deviations and support set of random parameters derived from historical data. Under this information on the random parameters, an ambiguous mixed-integer stochastic optimization model is proposed. For such a problem, we approximately construct a worst-case discrete probability distribution with three possible realizations per random parameter, and adopt a hybrid sample average approximation algorithm in which genetic algorithms are used to replace commercial solvers. To illustrate the effectiveness and efficiency of the proposed model and algorithm, extensive numerical experiments are carried out.

show abstract

“…The objective function is the total weighted tardiness of a schedule TWT = N j=1 w j (OT j − DOT j ). This objective allows reduction of delays, maximisation of the runway capacity, and reduction of congestion at the airport [14].…”

Section: 3mentioning

confidence: 99%

Constraint-Guided Local Search for Single Mixed-Operation Runway

Riahi

Newton

Sattar

2018

AI 2018: Advances in Artificial Intelligence

View full text Add to dashboard Cite

Aircraft sequencing problem (ASP) is to schedule the operation times of departing and arriving aircraft such that their deviation from the desired operation times are minimised. There are two types of hard constraint which make this problem very challenging: time window constraint for the operation time of each aircraft, and minimum separation time between each pair of aircraft. ASP is known to be NP-Hard. Although some progress has been made in recent years in solving ASP, existing techniques still rely on generic algorithms that usually lack problem specific knowledge. This leads to either finding low quality solutions or scrambling with large-sized problems. In this work, we propose a constraint-guided local search algorithm that advances ASP search by injecting the specific knowledge of the problem into its different phases. In the intensification phase, we propose a greedy approach that gives more priorities to aircraft that are more problematic and create more delays. In the diversification phase, we employ a bounded-diversification technique that controls the new position of each selected aircraft and does not allow them to move very far away from their current positions. Computational results show that the proposed algorithm outperforms the existing state-of-the-art methods with considerable margin.

show abstract

Minimizing deviation from scheduled times in a single mixed-operation runway

Cited by 30 publications

References 39 publications

Rolling-Horizon Electric Vertical Takeoff and Landing Arrival Scheduling for On-Demand Urban Air Mobility

Rolling-Horizon Electric Vertical Takeoff and Landing Arrival Scheduling for On-Demand Urban Air Mobility

Stochastic Runway Scheduling Problem With Partial Distribution Information of Random Parameters

Constraint-Guided Local Search for Single Mixed-Operation Runway

Contact Info

Product

Resources

About