Outbound Flights Research Articles

Landmark knowledge overrides optic flow in honeybee waggle dance distance estimation.

Honeybees encode in their waggle dances the vector (distance and direction) of an outbound flight to a food source or a new nest site. Optic flow has been identified as the major source of information in the distance estimation. Additional components of distance estimation were also identified, e.g. the sequence of experienced landmarks. Here we address the question of whether bees also use the landscape memory developed during exploratory orientation flights to estimate distance. We took advantage of the fact that flights in a narrow tunnel lead to further distance measures due to higher optic flow. We find that this effect is lost when bees had explored the area in which the tunnel is located and when they have somewhat restricted visual access to the surrounding environment through the mesh on top of the tunnel. These data are interpreted in the context of other findings about the structure of navigational memory in bees that develops during exploratory orientation flights. In particular, the data suggest that bees embed distance measures into a representation of navigational space that stores previously experienced landscape features.

Managing the challenge of fatigue for pilots operating ultra-long range flights

IntroductionUltra-long range (ULR) flights are defined as exceeding regulatory limits: normally 16 h flight time. They pose challenges due to long duty periods that could result in extended wakefulness and sleep loss, increasing the risk of fatigue. This study describes the mitigations used to manage fatigue in these operations. Two data collection phases were conducted on the Auckland-Chicago ULR route: when the route commenced (Study 1) and when the flight crew complement was altered (Study 2). Seasonal differences were also investigated.MethodsStudy 1 involved 72 crew who completed diaries and wore an actigraph to record sleep pre-departure, throughout the trip, and on return. In-flight, fatigue, sleepiness and workload were reported, and reaction time performance was measured. Study 2 involved 75 crew and data collection in the northern summer and northern winter. Crew completed diaries throughout the trip.ResultsStudy 1 data found crew sleep longer than usual in the 24 h pre trip and post flights. On the shorter outbound flight in-flight sleep averaged 3.3 h and on the longer inbound flight, 3.3–3.8 h, with most crew taking 3 breaks. Ratings of sleepiness and fatigue increased, and reaction time performance declined across flights, with greater decrements on longer inbound flights. Pilots did not fully adjust their sleep patterns to local time during the layover and no seasonal differences were found. Comparisons between Study 1 and 2 showed no difference in ratings of fatigue and sleepiness or in-flight sleep duration with an altered crew complement. There was a trend for Captains to report greater workload and less in-flight sleep in Study 2.DiscussionMitigations that allow for preparation and recovery are well utilized by crew. In-flight sleep is relatively short and ways of increasing the amount of sleep obtained should be considered. The incomplete adaptation of sleep during the layover has implications for rest break strategies on the return flight. The altered crew complement did not result in higher levels of fatigue or sleepiness or less in-flight sleep on average, although findings suggest a need to understand the effects of changing the crew complement on workload and in-flight sleep for Captains.

Anaphylaxis onboard commercial aircraft: what can we learn from post event safety reports?

This letter details a review of safety reports submitted to the UK Civil Aviation Authority over a 5 year period relating to severe allergic reactions. No trend of seasonality and evidence of aerosolisation was found. Reports were 4.8 times more likely to be submitted on an inbound flight than an outbound flight.

The Impact of Flight Revenue and Control Loads on Flight Schedules

Flight time optimization is an important means to solve the balance of airport capacity and flow, and has always been the focus of research in the field of air traffic. In view of the fact that the existing research mainly focuses on the fairness of time allocation for inbound and outbound flights, but there are few studies that comprehensively consider the influence factors of flight revenue and controller load, a multi-objective flight time optimization model is proposed to maximize the revenue of airline operation, minimize the workload of controllers, and minimize the deviation of fairness, and the improved genetic algorithm is used to solve the model, which is validated by the actual flight data of Shenzhen Bao'an International Airport. The effectiveness of the model is verified with the actual flight data of Shenzhen Baoan International Airport. The results show that after optimization, the average controller workload fairness deviation coefficient is decreased by 7.97%, the average airport fairness deviation is decreased by 15.30%, and the overall average airline revenue is increased by 0.21%, which achieves the purpose of improving airline revenue and reducing controller load.

Managing cabin crew fatigue during ultra-long range operations

IntroductionUltra-long range (ULR) flights have the potential to increase fatigue-related risk for cabin crew, if the extended flight times are associated with extended wakefulness, sleep loss and higher levels of crew fatigue. ULR flights may also require longer opportunities for recovery sleep. This study evaluates the utilization of fatigue risk mitigations for cabin crew operating the Auckland – Chicago ULR route with a two-day layover.Methods65 cabin crew (45 women; aged 20–59 years) wore an actigraph and completed a sleep/duty diary for 3 local nights prior to, throughout, and for 3 local nights after a ULR trip. Crewmembers rated their fatigue (Samn-Perelli Crew Status Check), sleepiness (Karolinska Sleepiness Scale), and workload (OW; NASA-TLX) at key times during each flight. Jet lag was rated each day at home and during layover.ResultsFatigue and sleepiness were highest at top-of-descent and after landing and were higher on the inbound flight than on the outbound flight. For every hour of additional sleep in-flight, top-of-descent fatigue ratings decreased by 0.24 points and top-of-descent sleepiness ratings decreased by 0.38, whereas top-of-descent fatigue and sleepiness ratings increased by 0.24 points with every 10-point increase in OW ratings. Crew slept more in the 24-hours prior to the outbound (M = 8.5 h) and inbound flights (M = 9.1 h) compared to pre-trip baseline days (M = 8.2 h). Post-trip, crew slept more during the first day (M = 9.9 h) compared to baseline, with 95% taking a daytime nap. Jet lag ratings decreased daily on return home but were still higher on the fourth day than on the day of the outbound flight.DiscussionCabin crew prepare for ULR flights by obtaining more sleep prior to departure. However, large individual differences in sleep and declining jet lag ratings across pre-trip days suggest that some crewmembers may still be recovering from a previous trip. Further refinement of in-flight sleep strategies and workload mitigations could be considered for managing fatigue risk at top-of-descent. Findings also highlight the importance of a protected period of post-trip rest to facilitate cabin crews' recovery from the effects of sleep restriction and circadian disruption associated with this ULR trip.

Air cargo network planning and scheduling problem with minimum stay time: A matrix-based ALNS heuristic

In air cargo delivery, cargo usually needs to stay in hubs after unloading operations until the designated outbound flight is ready to leave. The stay time may account for a significant part of the overall delivery time and is closely related to the service level of the cargo delivery. However, the prior studies on the air cargo network planning and scheduling problem mainly focused on the cost and revenue but paid little attention to the stay time. To bridge this gap, we introduce a new facet to the air cargo network planning and scheduling literature. The air cargo network planning and scheduling problem with minimum stay time involves the optimization of the hub location, flight deployment, flight timetabling, and flight-sequence-based cargo distribution to minimize the total stay time of freighter cargoes while guaranteeing a rational cost level. We develop a hierarchical modeling framework to handle this problem, where a time–space network is built to model the cargo stay time and the flight departure time. Next, to efficiently address the framework, the concept of the capacity matrix is introduced for model reformulation, and a matrix-based ALNS heuristic is proposed for model solving. The heuristic designs eight destroy operators from the column, row, and element perspectives, and develops a repair model for the repair operation. Finally, the proposed framework and algorithm are tested with a real-life instance from a leading express company in China.

0177 Quantifying the duration and timing of pilot sleep during layovers

Abstract Introduction Pilots flying long range (8-16 h) and ultra long range (16+ h) flights crossing several time zones must decide when and how much to sleep during layover between the outbound and return flight. Some pilots choose to sleep on home base time (HBT), while others attempt to sleep on local layover time. We sought broad patterns in the timing and amount of pilot sleep during layovers. Methods Using actigraphy, verified by self-report diaries, we collected sleep/wake data on 229 pilots (flying 460 total trips) from nine routes ranging from 10 to 17 hours in scheduled duration. All trips originated in the United States and seven were westbound routes, and two were eastbound routes. Scheduled layover durations ranged from 24 to 56 hours. We collected continuous sleep data three days before the trip, during both flights, during layover, and at least three days after the trip. Results Across all routes, pilots slept an average of 7 hours 58 minutes per 24 hours of layover (± 1 hour 53 minutes SD). Neither the amount nor timing of layover sleep depended on any of the following variables: 1) time (relative to home base) that the layover began; 2) direction of travel (westbound vs eastbound); 3) crew role (flying vs relief); and 4) total amount of sleep during the outbound flight. On layovers lasting 48 hours or longer, the second 24 hours showed more pilots sleeping during local night compared to the first 24 hours. Interindividual differences in the timing and amount of layover sleep were very large (larger than group differences between routes, between crews, and between flight directions.) On average, on layover days pilots obtained 17 minutes less sleep compared to pre-trip days and 32 minutes less sleep compared to post-trip days. Conclusion There are many complex factors that contribute to the timing and amount of layover sleep. We found that interindividual differences are larger than the variables that are constrained by the operational environment, which suggests that the timing and duration of layover sleep may be impacted more by individual traits rather than environmental or operational factors. Support (if any) United Airlines

Analyzing the Impacts of Inbound Flight Delay Trends on Departure Delays Due to Connection Passengers Using a Hybrid RNN Model

Some delay patterns are correlated to historical performance and can reflect the trend of delays in future flights. A typical example is the delay from an earlier inbound flight causing delayed departure of a connecting and downstream outbound flight. Specifically, if an arriving aircraft arrives late, the connecting airline may decide to wait for connecting passengers. Due to the consistent flow of passengers to various destinations during a travel season, similar delay patterns could occur in future days/weeks. Airlines may analyze such trends days or weeks before flights to anticipate future delays and redistribute resources with different priorities to serve those outbound flights that are likely to be affected by feeder delays. In this study, we use a hybrid recurrent neural network (RNN) model to estimate delays and project their impacts on downstream flights. The proposed model integrates a gated recurrent unit (GRU) model to capture the historical trend and a dense layer to capture the short-term dependency between arrival and departure delays, and, then, integrates information from both branches using a second GRU model. We trained and tuned the model with data from nine airports in North, Central, and South America. The proposed model outperformed alternate approaches with traditional structures in the testing phase. Most of the predicted delay of the proposed model were within the predefined 95% confidence interval. Finally, to provide operational benefits to airline managers, our analysis measured the future impact of a potentially delayed inbound feeder, (PDIF) in a case study, by means of identifying the outbound flights which might be affected based on their available connection times (ACTs). From an economic perspective, the proposed algorithm offers potential cost savings for airlines to prevent or minimize the impact of delays.

Comprehensive operating efficiency measurement of 28 Chinese airports using a two-stage DEA-Tobit method

<abstract> <p>This paper presents a two-stage method combining data envelopment analysis (DEA) and a Tobit model to analyze the comprehensive operating efficiency of 28 airports in China in 2016. At the first stage, the DEA-BCC (Banker-Charnes-Cooper) model was employed to obtain the comprehensive operating efficiency of the combination of flight departure punctuality, non-cancellations, landing bridge rates from the perspective of airport infrastructure, surrounding airspace, route layouts, flight volume and weather. At the second stage, a Tobit model was used to analyze the influence of nine input variables from four aspects on obtained comprehensive operating efficiency, ultimately providing a clear and straightforward basis for formulating and testing policies. The comprehensive operating efficiency with this combination was further compared with each of the three efficiencies respectively. The important findings included the following: (1) The comprehensive operation efficiencies of most airports were greater than the individual efficiency; (2) These four types of operation efficiencies for most airports did not achieved DEA validity (100% efficiency), except for six airports (i.e., Haikou, Dalian, Jinan, Fuzhou, Nanning and Lanzhou); (3) These factors affecting each of the four types of operation efficiencies were different in that the number of terminals, duration of impact and average daily inbound and outbound flights had a negative impact on airport operational efficiency, while the average number of overnight aircraft per day and peak hour sorties had positive effects.</p> </abstract>

Research Partnerships and Guidance in Academic Global Ophthalmology.

Research Partnerships and Guidance in Academic Global Ophthalmology.

Business Class Travel Preserves Sleep Quality and Quantity and Minimizes Jet Lag During the ICC Women's T20 World Cup.

To determine the impact of the quality and quantity of sleep during an international flight on subsequent objective sleep characteristics, training and match-day load, self-reported well-being, and perceptions of jet lag of elite female cricketers during an International Cricket Council Women's T20 World Cup. In-flight and tournament objective sleep characteristics of 11 elite female cricketers were assessed using activity monitors. Seated in business class, players traveled west from Melbourne, Australia, to Chennai, India. The outbound flight departed Melbourne at 3:30 AM with a stopover in Dubai for 2 hours. The arrival time in Chennai was 8:10 PM local time (1:40 AM in Melbourne). The total travel time was 19 hours 35 minutes. Perceptual ratings of jet lag, well-being, and training and competition load were collected. To determine the impact of in-flight sleep on tournament measures, a median split was used to create subsamples based on (1)in-flight sleep quantity and (2)in-flight sleep quality (2 groups: higher vs lower). Spearman correlation coefficients were calculated to assess the bivariate associations between sleep measures, self-reported well-being, perceptual measures of jet lag, and internal training and match-day load. Mean duration and efficiency of in-flight sleep bouts were 4.72 hours and 87.45%, respectively. Aggregated in-flight sleep duration was 14.64 + 3.56 hours. Players with higher in-flight sleep efficiency reported higher ratings for fatigue (ie,lower perceived fatigue) during the tournament period. Tournament sleep duration was longer, and bed and wake times were earlier compared with habitual. Compared with other nights during the tournament, sleep duration was shorter following matches. Maximizing in-flight sleep quality and quantity appears to have implications for recovery and sleep exhibited during competition. Sleep duration was longer than habitual except for the night of a match, which suggests that T20 matches may disrupt sleep duration.

292 Rest Schemes and Inflight Sleep Duration on Long Range and Ultra-Long Range Commercial Airline Routes

Abstract Introduction Pilots flying long range (LR; 8-16 hour) and ultra-long range (ULR; 16+ hour on 10% of trips) commercial airline routes use a variety of work/rest schedules during flights, resulting in a wide distribution of total inflight sleep time (TIFS) amounts. Since sleep is a strong predictor of performance, it is important to quantify TIFS and determine rest scheme patterns that optimize sleep opportunity and subsequent alertness and performance. Here we report rest schemes for pilots on LR and ULR routes and longer TIFS values than previously reported. These rest schemes can serve as templates to increase TIFS and improve pilot performance, particularly on ULR routes. Methods 427 commercial airline pilots provided data for this sub-study that was part of a larger study on Fatigue Risk Management System (FRMS) routes. Inflight sleep timing and duration were measured on 3 LR and 5 ULR routes. Inflight sleep times were self-reported in a sleep/work logbook and verified using actigraphy. Results Most outbound and inbound landing crews took one break during the second half of the flight (average LR TIFS=4.0 hr; average ULR TIFS=4.9 hr), while most outbound and inbound relief crews consequently took one break during the first half of the flight (average LR TIFS=3.5 hr; average ULR TIFS=4.5 hr). However, three of the five ULR routes used more complex split rest schemes for landing and relief crews, primarily on outbound flights (average TIFS=5.0 hr). Across all routes and both crews, the maximum average TIFS reached ~6 hours. Conclusion Our results indicate that pilots on average are sleeping inflight more than previous studies demonstrated. Additionally, we found that crews on some ULR flights used more complicated rest schemes, but still generally preferred 2 or 3 breaks. These findings have implications for airline procedures and aviation policies by showing that pilots may be sleeping longer than originally expected on LR and ULR flights. Recommending rest schemes that allow for the greatest inflight sleep opportunity may provide the best chance for inflight recuperation, especially before the Top of Descent critical phase of flight. Support (if any) United Airlines

Compression stockings for preventing deep vein thrombosis in airline passengers.

Air travel might increase the risk of deep vein thrombosis (DVT). It has been suggested that wearing compression stockings might reduce this risk. This is an update of the review first published in 2006. To assess the effects of wearing compression stockings versus not wearing them for preventing DVT in people travelling on flights lasting at least four hours. The Cochrane Vascular Information Specialist searched the Cochrane Vascular Specialised Register, CENTRAL, MEDLINE, Embase, CINAHL and AMED databases and World Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov trials registers to 1 April 2020. We also checked the bibliographies of relevant studies and reviews identified by the search to check for any additional trials. Randomised trials of compression stockings versus no stockings in passengers on flights lasting at least four hours. Trials in which passengers wore a stocking on one leg but not the other, or those comparing stockings and another intervention were also eligible. Two review authors independently selected trials for inclusion and extracted data. We sought additional information from trialists where necessary. One new study that fulfilled the inclusion criteria was identified for this update. Twelve randomised trials (n = 2918) were included in this review: ten (n = 2833) compared wearing graduated compression stockings on both legs versus not wearing them; one trial (n = 50) compared wearing graduated compression tights versus not wearing them; and one trial (n = 35) compared wearing a graduated compression stocking on one leg for the outbound flight and on the other leg on the return flight. Eight trials included people judged to be at low or medium risk of developing DVT (n = 1598) and two included high-risk participants (n = 1273). All flights had a duration of more than five hours. Fifty of 2637 participants with follow-up data available in the trials of wearing compression stockings on both legs had a symptomless DVT; three wore stockings, 47 did not (odds ratio (OR) 0.10, 95% confidence interval (CI) 0.04 to 0.25, P < 0.001; high-certainty evidence). There were no symptomless DVTs in three trials. Sixteen of 1804 people developed superficial vein thrombosis, four wore stockings, 12 did not (OR 0.45, 95% CI 0.18 to 1.13, P = 0.09; moderate-certainty evidence). No deaths, pulmonary emboli or symptomatic DVTs were reported. Wearing stockings had a significant impact in reducing oedema (mean difference (MD) -4.72, 95% CI -4.91 to -4.52; based on six trials; low-certainty evidence). A further three trials showed reduced oedema in the stockings group but could not be included in the meta-analysis as they used different methods to measure oedema. No significant adverse effects were reported. There is high-certainty evidence that airline passengers similar to those in this review can expect a substantial reduction in the incidence of symptomless DVT and low-certainty evidence that leg oedema is reduced if they wear compression stockings. The certainty of the evidence was limited by the way that oedema was measured. There is moderate-certainty evidence that superficial vein thrombosis may be reduced if passengers wear compression stockings. We cannot assess the effect of wearing stockings on death, pulmonary embolism or symptomatic DVT because no such events occurred in these trials. Randomised trials to assess these outcomes would need to include a very large number of people.

Optimization of Transfer Baggage Handling in a Major Transit Airport

We consider the handling of baggage from passengers changing aircraft at an airport. The transfer baggage problem is to assign the bags from each arriving aircraft to an infeed area, from where a network of conveyor belts will bring them to the corresponding outbound flight. The main objective is to minimize the number of missed bags, but in order to reach this goal, we introduce some auxiliary objectives that minimize the transportation time of bags, while ensuring robustness and avoiding overload of the handling facilities. We first present a static mixed integer programming model for the transfer baggage problem. However, the transfer baggage process is subject to uncertainty related to aircraft arrival time, transportation time from aircraft to baggage handling facility, and capacity use in the baggage handling system. In order to handle this uncertainty, a stochastic model is developed, optimizing over a finite set of scenarios. Although the model in theory should lead to more balanced and stable decisions, it suffers of long solution times. Therefore, a semi-stochastic model is presented, where short-term decisions are stochastic, while long-term decisions are deterministic. Computational experiments on real-life data from a major European hub airport are reported, demonstrating that each of the three models has its advantages. In particular, the semi-stochastic model shows promising results both with respect to robustness and solution times.

Continuous Time Formulation and Lagrangian Relaxation Algorithm for the Gate Assignment Problem

Gates are important operating facilities and resources in civil airports. It is a core task in the airport operation management to select reasonable gates for inbound and outbound flights. We present a continuous time formulation with second-order cone programming (SOCP) for the gate assignment problem which allocates flights to available gates to optimize both the transfer time of passengers and the robustness of the airport operations schedules. The problem is formulated as a mixed integer nonlinear program, and then, the quadratic objective that minimizes the walking distance of transferring passengers is linearized, and the objective that minimizes the variance of idle time at the gates is transformed to a second-order cone constraint with a linear objective function. Then, a Lagrangian relaxation algorithm is developed by exploiting the problem structure. Computational tests are carried out to illustrate the efficiency of the model and the algorithms. It is shown that the continuous time formulation is more efficient than the existing model, and the Lagrangian relaxation algorithm can obtain better solutions faster than a commercial solver.

Clusters of 2019 coronavirus disease (COVID-19) cases in Chinese tour groups.

International travel may facilitate the spread of the novel coronavirus disease (COVID‐19). The study describes clusters of COVID‐19 cases within Chinese tour groups travelling in Europe January 16–28. We compared characteristics of cases and non‐cases to determine transmission dynamics. The index case travelled from Wuhan, China, to Europe on 16 January 2020, and to Shanghai, China, on 27 January 2020, within a tour group (group A). Tour groups with the same outbound flight (group B) or the same tourism venue (group D) and all Chinese passengers on the inbound flight (group C) were investigated. The outbreak involved 11 confirmed cases, 10 suspected cases and six tourists who remained healthy. Group A, involving seven confirmed cases and six suspected cases, consisted of familial transmission followed by propagative transmission. There was less pathogenicity with propagative transmission than with familial transmission. Disease was transmitted in shared outbound flights, shopping venues within Europe and inbound flight back to China. The novel coronavirus caused clustered cases of COVID‐19 in tour groups. When tourism and travel opens up, governments will need to improve screening at airports and consider increased surveillance of tour groups—particularly those with older tour members.

Airline choice model for an international round-trip flight considering outbound and return flight schedules

This paper quantified the impact of outbound and return flight schedule preferences on airline choice for international trips. Several studies have used airline choice data to identify preferences and trade-offs of different air carrier service attributes, such as travel time, fare and flight schedule. However, estimation of the effect return flight schedules have on airline choice for an international round-trip flight has not yet been studied in detail. Therefore, this study introduces attributes related to return flight characteristics and round-trip flight schedule interaction into the airline choice models, which have not previously been reported in the literature. We developed a stated preference survey that includes round-trip fares based on flight schedule combinations and the number of days prior to departure fares was purchased. We applied modelling techniques using a set of stated preference data. A mixed logit model was tested for the presence of heterogeneity in passengers' preferences. Our results indicated that models with attributes related to return flight and its interaction with outbound flight attributes have a superior fit compared with models only based on attributes reported in the literature review. The model found shows that airfare, travel time, arrival preference schedule in the outward journey, departure preference in the return journey and the schedule combination of round-trip flight are significantly affecting passenger choice behaviour in international round-trip flights. Sensitivity analysis of airline service characteristics and their marketing implications are conducted. The analysis reports seven policies with the greatest impact on each airline choice probabilities. It shows that by reducing travel time and airfare and by adopting an afternoon and night schedule preference for outbound and return flight, respectively, the highest probability on airline choice would be reached. This research contributes to the current literature by enhancing the understanding of how passengers choose airlines, considering both outbound and inbound journey characteristics. Thus, this study provides an analytical tool designed to provide a better understanding of international round-trip flight demand determinants and support carrier decisions.

Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: A modelling analysis based on overseas cases and air travel data

As of March 1, 2020, Iran had reported 987 novel coronavirus disease (COVID-19) cases, including 54 associated deaths. At least six neighboring countries (Bahrain, Iraq, Kuwait, Oman, Afghanistan, and Pakistan) had reported imported COVID-19 cases from Iran. In this study, air travel data and the numbers of cases from Iran imported into other Middle Eastern countries were used to estimate the number of COVID-19 cases in Iran. It was estimated that the total number of cases in Iran was 16 533 (95% confidence interval: 5925–35 538) by February 25, 2020, before the UAE and other Gulf Cooperation Council countries suspended inbound and outbound flights from Iran.

An Empirical Study on Low Emission Taxiing Path Optimization of Aircrafts on Airport Surfaces from the Perspective of Reducing Carbon Emissions

Aircraft emissions are the main cause of airport air pollution. One of the keys to achieving airport energy conservation and emission reduction is to optimize aircraft taxiing paths. The traditional optimization method based on the shortest taxi time is to model the aircraft under the assumption of uniform speed taxiing. Although it is easy to solve, it does not take into account the change of the velocity profile when the aircraft turns. In view of this, this paper comprehensively considered the aircraft’s taxiing distance, the number of large steering times and collision avoidance in the taxi, and established a path optimization model for aircraft taxiing at airport surface with the shortest total taxi time as the target. The genetic algorithm was used to solve the model. The experimental results show that the total fuel consumption and emissions of the aircraft are reduced by 35% and 46%, respectively, before optimization, and the taxi time is greatly reduced, which effectively avoids the taxiing conflict and reduces the pollutant emissions during the taxiing phase. Compared with traditional optimization methods that do not consider turning factors, energy saving and emission reduction effects are more significant. The proposed method is faster than other complex algorithms considering multiple factors, and has higher practical application value. It is expected to be applied in the more accurate airport surface real-time running trajectory optimization in the future. Future research will increase the actual interference factors of the airport, comprehensively analyze the actual situation of the airport’s inbound and outbound flights, dynamically adjust the taxiing path of the aircraft and maintain the real-time performance of the system, and further optimize the algorithm to improve the performance of the algorithm.

There's No Place Like Home: Visual Teach and Repeat for Emergency Return of Multirotor UAVs During GPS Failure

Redundant navigation systems are critical for safe operation of UAVs in high-risk environments. Since most commercial UAVs almost wholly rely on GPS, jamming, interference, and multi-pathing are real concerns that usually limit their operations to low-risk environments and visual line-of-sight. This letter presents a vision-based route-following system for the autonomous, safe return of UAVs under primary navigation failure such as GPS jamming. Using a Visual Teach and Repeat framework to build a visual map of the environment during an outbound flight, we show the autonomous return of the UAV by visually localizing the live view to this map when a simulated GPS failure occurs, controlling the vehicle to follow the safe outbound path back to the launch point. Using gimbal-stabilized stereo vision and inertial sensing alone, without reliance on external infrastructure, Visual Odometry and localization are achieved at altitudes of 5–25 m and flight speeds up to 55 km/h. We examine the performance of the visual localization algorithm under a variety of conditions and also demonstrate closed-loop autonomy along a complicated 450 m path.