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International audience; Air traffic management (ATM) systems around the world are being modernized to accommodate shifts towards performance-and trajectory-based operations. These shifts will require new indices for safety, efficiency and complexity. The authors have been developing an index for evaluating air traffic control (ATC) difficulty that utilizes the relative positions and velocity vectors of aircraft pairs as input data. Prior to practical application of the index, it is necessary to understand the effects of input data error, i.e. errors in the positions and velocities of a pair of aircraft, on the estimated difficulty value. Two sensitivity analyses were therefore performed for a pair of aircraft cruising at constant speeds on intersecting linear tracks at the same altitude. Sensitivity analysis examines how uncertainty in inputs relates to uncertainty in outputs. Firstly, an analysis of propagation error was carried out. The formula of the propagation error at a certain point was derived based on the assumed input error, and the distribution of propagation error was investigated for all possible situations and compared with the distribution of difficulty values to clarify its characteristics. Secondly, a sensitivity analysis based on variance was carried out that evaluated the effect of each input parameter using a conditional variance value called the Sobol indices. Using a Monte Carlo method, we investigated the effect of each input parameter on the calculated difficulty value for all possible situations of aircraft pairs on intersecting trajectories. As a result, it was found that the parameter that most affects the difficulty value is the intersection angle of the trajectories.

International audience; As the number of vehicles equipped with radars sensors is rapidly increasing, the risk of harmful interference is increasing, especially since the radar waveform parameters are not regulated. Interference mitigation techniques are becoming important for radars to operate properly in this complex environment. We presented in a previous study that the use of V2X technology to communicate radars physical properties as well as the parameters of their waveform allows for new anticipation strategies. These strategies focus on identifying potential interferers thanks to V2X communications and adapt the radar waveform to minimize the risk of interference. This article investigates the importance of time synchronization between the radar's waveform and the V2X messages emissions when using such a cooperative strategy.

Air traffic controllers have to make quick decisions to keep air traffic safe. Their behaviors have a significant impact on the operation of the air traffic management (ATM) system. Automation tools have enhanced the ATM system’s capability by reducing the controller’s task-load. Much attention has been devoted to developing advanced automation in the last decade. However, less is known about the impact of automation on the behaviors of air traffic controllers. Here, we empirically tested the effects of three levels of automation—including manual, attention-guided, and automated—as well as varying traffic levels on eye movements, situation awareness and mental workload. The results showed that there are significant differences in the gaze and saccade behaviors between the attention-guided group and automated group. Traffic affected eye movements under the manual mode or under the attention-guided mode, but had no effect on eye movements under the automated mode. The results also supported the use of automation for enhancing situation awareness while reducing mental workload. Our work has potential implications for the design of automation and operation procedures.

International audience; This paper presents an innovative approach that combines optimization and simulation techniques for solving scheduling problems under uncertainty. We introduce an Opt–Sim closed-loop feedback framework (Opt–Sim) based on a sliding-window method, where a simulation model is used for evaluating the optimized solution with inherent uncertainties for scheduling activities. The specific problem tackled in this paper, refers to the airport capacity management under uncertainty, and the Opt–Sim framework is applied to a real case study (Paris Charles de Gaulle Airport, France). Different implementations of the Opt–Sim framework were tested based on: parameters for driving the Opt–Sim algorithmic framework and parameters for riving the optimization search algorithm. Results show that, by applying the Opt–Sim framework, potential aircraft conflicts could be reduced up to 57% over the non-optimized scenario. The proposed optimization framework is general enough so that different optimization resolution methods and simulation paradigms can be implemented for solving scheduling problems in several other fields.

Paris Charles de Gaulle Airport was the second European airport in terms of traffic in 2019, having transported 76.2 million passengers. Its large infrastructures include four runways, a large taxiway network, and 298 aircraft parking stands (131 contact) among three terminals. With the current pandemic in place, the European air traffic network has declined by −65% flights when compared with 2019 traffic (pre-COVID-19), having a severe negative impact on the aviation industry. More and more often taxiways and runways are used as parking spaces for aircraft as consequence of the drastic decrease in air traffic. Furthermore, due to safety reasons, passenger terminals at many airports have been partially closed. In this work we want to study the effect of the reduction in the physical facilities at airports on airspace and airport capacity, especially in the Terminal Manoeuvring Area (TMA) airspace, and in the airport ground side. We have developed a methodology that considers rare events such as the current pandemic, and evaluates reduced access to airport facilities, considers air traffic management restrictions and evaluates the capacity of airport ground side and airspace. We built scenarios based on real public information on the current use of the airport facilities of Paris Charles de Gaulle Airport and conducted different experiments based on current and hypothetical traffic recovery scenarios. An already known optimization metaheuristic was implemented for optimizing the traffic with the aim of avoiding airspace conflicts and avoiding capacity overloads on the ground side. The results show that the main bottleneck of the system is the terminal capacity, as it starts to become congested even at low traffic (35% of 2019 traffic). When the traffic starts to increase, a ground delay strategy is effective for mitigating airspace conflicts, however, it reveals the need for additional runways.

The COVID-19 pandemic has had a significant impact on the air transportation system worldwide. This paper aims at analyzing the effect of the travel restriction measures implemented during the COVID-19 pandemic from a passenger perspective on the US air transportation system. Four metrics based on data generated by passengers and airlines on social media are proposed to measure how the travel restriction measures impacted the relation between passengers and airlines in close to real-time. The proposed metrics indicate that each airline has reacted differently to the COVID-19 travel restriction measures from a passenger perspective, therefore they can be used by airlines and passengers to improve their decision making process. This report comes ahead of official data related to the same sequence of events, thereby showing the value of passenger-borne data in an industry where corporate priorities, institutional prudence, and passenger satisfaction come close together., Highlights • Passenger-generated data can be harnessed earlier than official flight data. • Four passenger-centric metrics are proposed and extracted from the Twitter flow. • These metrics can be used to improve passenger and airline decisions. • US airlines have reacted differently to COVID-19 travel restriction measures. • Each airline has its own passenger communication Twitter profile.

International audience; Airport capacity has become a constraint in the air transportation networks, due to the growth of air traffic demand and the lack of resources able to accommodate this demand. This paper presents the algorithmic implementations of a decision support system for making a more efficient use of the airspace and ground capacity. The system would be able to provide support for air traffic controllers in handling large amount of flights while reducing to a minimum the potential conflicts. In this framework, airspace together with ground airport operations are considered. Conflicts are defined as separation minima violation between aircraft for what concerns airspace and runways, and as capacity overloads for taxiway network and terminals. The methodology proposed in this work consists of an iterative approach that couples optimization and simulation to find solutions that are resilient to perturbations due to the uncertainty present in different phases of the arrival and departure process. An optimization model was employed to find a (sub)optimal solution while a discrete event-based simulation model evaluated the objective function. By coupling simulation with optimization, we generate more robust solutions resilient to variability in the operations, this is supported by a case study of Paris Charles de Gaulle Airport.

This paper introduces a novel approach for synchronised demand-capacity balancing within a proposed Collaborative Air Traffic Flow Management framework. The approach is aimed to realise optimising traffic flow and scheduling airspace configuration in a more harmonised manner. Options such as delay assignment and alternative trajectories (generated and submitted by Airspace Users) are intended for regulating the traffic flow. Airspace reconfiguration involves, on the other side, adjusting the opening schemes of predefined configurations, or creating new ones (if needed) through dynamic sectorisation. Results suggest that, using the proposed approach, the required system delay can be reduced remarkably, whereas the number of opened sectors (and thus operating cost) and the total capacity provision (supplied by the Air Navigation Service Providers) decrease at the same time, due to the increased capacity utilisation per operating sector.

International audience; Departure metering has the potential to mitigate airport surface congestion and decrease flight delays. This paper considers several candidate departure metering techniques, including a trajectory-based optimization approach using a node-link model and three aggregate queue-based approaches (a scheduler meant to represent NASA's Airspace Technology Demonstration-2 (ATD-2) logic, an optimal control approach, and a robust control approach). The outcomes of these different approaches are compared for two major airports: Paris Charles De Gaulle airport (CDG) in Europe and Charlotte Douglas International airport (CLT) in the United States. These two airports have similar aggregate demand and capacity, but the banking of demand at CLT leads to congestion, resulting in higher taxi-out delays and more potential for departure metering at CLT. Stochastic simulations are used to show that departure metering with the robust control approach best accommodates operational uncertainties, and that departure metering yields higher taxi-out time savings at CLT compared to CDG, irrespective of the approach. Nomenclature ∆t = Time step ∆v = Speed increment s = Minimum taxi separation distance V min = Minimum allowed taxi speed V max = Maximum allowed taxi speed N∆t = Maximum allowed holding time, N a for arrivals and N d for departures

As environmental awareness has increased, airlines are paying attention to fuel consumption during daily flight operations with the hope of reducing consumption. Because the direction and strength of the wind affects the fuel consumption of an aircraft, airlines are seeking to minimize the adverse effects of headwinds or maximize the beneficial effect of tailwinds when planning flight trajectories. According to the jet stream profile of the world, it is easy to notice that the jet streams flow in the eastwest direction instead of the north-south direction. Therefore, the flights on east-west routes are affected more by en route winds than the flights on north-south routes. In order to achieve the best flight performance in terms of flight time and fuel consumption, airlines may adjust the flight trajectories based on en route wind profiles. Consequently, it is necessary to consider en route wind effects when planning flight trajectories. However, it is difficult to identify the most suitable trajectory in a complex wind field because such field is not easy to estimate [17], [25], [8], [9], [26]. The wind directions and strength are varying in different regions, at different altitudes, and different times. Even though the problem is complex, solving it may benefit airlines in terms of fuel cost and on-time performance.

International audience; With the continuous air traffic growth and limits of resources, there is a need for reducing the congestion of the airspace systems. Nowadays, several projects are launched, aimed at modernizing the global air transportation system and air traffic management. In recent years, special interest has been paid to the solution of the dynamic airspace configuration problem. Airspace sector configurations need to be dynamically adjusted to provide maximum efficiency and flexibility in response to changing weather and traffic conditions. The main objective of this work is to automatically adapt the airspace configurations according to the evolution of traffic. In order to reach this objective, the airspace is considered to be divided into predefined 3D airspace blocks which have to be grouped or ungrouped depending on the traffic situation. The airspace structure is represented as a graph and each airspace configuration is created using a graph partitioning technique. We 2 optimize airspace configurations using a genetic algorithm. The developed algorithm generates a sequence of sector configurations for one day of operation with the minimized controller workload. The overall methodology is implemented and successfully tested with air traffic data taken for one day and for several different airspace control areas of Europe.

Best Student Paper Award; International audience; This paper aims at investigating further the use of the social media Twitter as a real-time estimator of the US Air Transportation system. Two different machine learning regressors have been trained on this 2017 passenger-centric dataset and tested on the first two months of 2018 for the estimation of air traffic delays at departure and arrival at 34 different US airports. Using three different levels of content-related features created from the flow of social media posts led to the extraction of useful information about the current state of the air traffic system. The resulting methods yield higher estimation performances than traditional state-of-the-art and off-the-shelf time-series forecasting techniques performed on flight-centric data for more than 28 airports. Moreover the features extracted can also be used to start a passenger-centric analysis of the Air Transportation system. This paper is the continuation of previous works focusing on estimating air traffic delays leveraging a real-time publicly available passenger-centered data source. The results of this study suggest a method to use passenger-centric data-sources as an estimator of the current state of the different actors of the air transportation system in real-time.

Best of session paper; International audience; This paper presents a data-driven study of wait time patterns for international arriving passengers across all 61 terminals from the 44 airports of entry of the United States. Each airport is an independent entity which operates with various airlines and handles demand volumes differently. This induces seasonal variation in service quality from one airport to another. Exploring six years worth of data, this paper investigates the current and long-term performance trends-an increasing number of flights versus a decreasing number of customs booths-of all airports of entry from a passenger perspective. A performance analysis is then conducted that compares average wait times of incoming passengers, considering incoming traffic ratios and allocated resources. Leveraging machine learning algorithms, six regression algorithms are trained and tested to accurately predict passenger wait times through customs at selected airports. An analysis of the performance of these models shows that the best approach-using a Gradient Boosting regressor for each terminal of entry-can capture the daily and seasonal variations of traffic patterns and immigration booth availabilities with a mean absolute error of less or equal to 5 minutes for twenty-eight terminals of entry and less than 10 minutes for all terminals. Observations show significant disparities across airports that may be explained by the foreign/US passenger ratio and the quality of booth management.

International audience; We tackle the problem of minimizing the number of aircraft potential conflicts via speed regulations and taking into account uncertainties on aircraft position due to wind and temperature. The resolution is done at a strategic level, before any of the aircraft has departed. Owing to the complexity of this kind of optimisation problem, a simulated annealing metaheuristic approach is employed. A scenario with four hours of traffic overflying the Spanish (structured, continental) airspace has been selected. Inputted traffic provides routes, Mach profiles (considered to be constant), and altitude profiles as in their flight plans. Probabilistic weather forecasts from an Ensemble Prediction System are employed. Solutions provide constant speed profiles that slightly differ from those in the flight plans. It is shown that the number of conflicts can be significantly reduced by slightly modifying flight plan speeds while not altering the routes, nor the altitudes, both selected by the airspace user. The impact of this resolution strategy in flight efficiency is also analyzed.

International audience; The North Atlantic oceanic airspace is considered the most congested oceanic airspace in the world. For many years, air traffic control in this airspace has experienced difficulties due to the limited radar coverage. To support conflict-free flight progress, a structure of routes, called the organized track system, is established in the North Atlantic airspace and very restrictive separation standards are applied. The development of the automated dependent surveillance-broadcast system provides an opportunity to improve the flight planning operations over the oceans by reducing separation norms. The aim of this study is to improve the traffic efficiency in the North Atlantic airspace by developing new approaches to organize the transatlantic traffic at the strategic level. The first considered approach proposes a new route structure, referred to as the wind-optimal track network, to replace the organized track system, whereas the second one is based on the wind-optimal free routes. The problem is modeled as an optimization problem and resolved further via simulated annealing combined with a sliding window algorithm. The results of the simulations performed on the real traffic data prove that about 76% of flights decrease their cruising times by more than half of an hour when flying wind-optimal tracks rather than using their great circle routes from the departure to the destination. Furthermore, by comparing the two proposed methods, it is concluded that using wind-optimal free routes implies lower cruising times, whereas the wind-optimal track network is much more robust under changing wind fields.

International audience; Airports and surrounding airspaces are limited in terms of capacity and represent the major bottlenecks of the air traffic management system. This paper addresses the problems of terminal airspace management and airport congestion management at the macroscopic level through the integrated control of arrivals and departures. Conflict detection and resolution methods are applied to a predefined terminal route structure. Different airside components are modeled using network abstraction. Speed, arrival and departure times, and runway assignment are managed by using an optimization method. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on case studies of Paris Charles De-Gaulle airport show some potential improvements: First, when the airport capacity is decreased, until a certain threshold, the overload can be mitigated properly by adjusting the aircraft entry time in the Terminal Maneuvering Area and the pushback time. Second, landing and take-off runway assignments in peak hours with imbalanced runway throughputs can significantly reduce flight delays. A decrease of 37% arrival delays and 36% departure delays was reached compared to baseline case.

ISBN: 978-1-5386-6573-2; International audience; The following paper presents an innovative approach for dealing with complex capacity problems in aviation. We introduce a sliding window framework composed by an optimization method with a simulation component. By applying this framework in diverse problems that are dependent on time it is possible to find feasible and close-to-reality solutions in shorter time than the ones that could be achieved by evaluating the problem in the complete time-horizon. The framework can be applied to solve diverse problems in aviation or similar industries. We exemplify the approach with a model of Paris Charles de Gaulle Airport in France.

This paper is an extension of work originally reported in SESAR Innovation Days 2018 : Zhengyi Wang, Man Liang, Daniel Delahaye. Automated Data-Driven Prediction on Aircraft Estimated Time of Arrival. SID 2018, 8th Sesar Innovations Days, Dec 2018, Salzburg, Austria. ⟨hal-01944608⟩; International audience; 4D trajectory prediction is the core element of the future air transportation system. It aims to improve the operational ability and the predictability of air traffic. In this paper, a novel automated data-driven framework to deal with the prediction of Estimated Time of Arrival (ETA) on the runway at the entry point of Terminal Manoeuvring Area (TMA) is introduced. The proposed framework mainly consists of data preprocessing and machine learning models. Firstly, the dataset is divided, analyzed, cleaned, and estimated. Then, the flights are clustered into partitions according to different runway-in-use (QFU). Several candidate machine learning models are trained and selected on the corresponding dataset of each QFU. Feature engineering is conducted to transform raw data into features. After that, the experiments are performed on real ADS-B data in Beijing TMA with nested cross validation. By comparing the prediction performance on the preprocessed and un-preprocessed datasets, the results demonstrate that the proposed data preprocessing is able to improve the data quality. It is also robust to outliers, missing data, and noise. Finally, an ensemble learning strategy named stacking is introduced. Compared to other individual models, the stacked model has a more complex structure and performs best in ETA prediction. This fact reveals that the framework proposed in this study could make accurate and reliable ETA predictions.

International audience; Airports Terminal Maneuvering Areas (TMA) and Control Traffic Regions (CTR) are characterized by a dense air traffic flow with high complexity. In nominal operations, approach flight path safety management consists in procedures which guide the aircraft to intercept the final approach axis, and the runway slope with an expected configuration in order to land. Some abnormal flights are observed and considered as Non Compliant when the intermediate and the final leg intercepting conditions do not comply with the prescription of the operational documentation. This kind of trajectories generates difficulties for both crew and Air Traffic Control (ATC) and may induce undesirable events such as Non Stabilized Approaches or ultimate events like Control Flight Into Terrain (CFIT), in the worst cases. There is a real need for atypical flights detection tools in order to improve safety. In this paper, a post-operational detection method based on functional principal component analysis and unsupervised learning will be presented and compared to geometric features.

International audience; An Airport-Sector Network Delays model is developed in this paper for flight delay estimation within air transport network. This model takes both airports and airspace capacities into account by iterating among its three main components: a queuing engine, which treats each airport in the network as a queuing system and is used to compute delays at individual airport, a Link Transmission Model, which computes delays at individual sector and transmits all air delays into ground delays, and a delay propagation algorithm that updates flight itineraries and demand rates at each airport on the basis of the local delays computed by the queuing engine and flow control delays computed by the Link Transmission Model. The model has been implemented to a network consisting of the 21 busiest airports in China and 2962 links that represent to 151 enroute control sectors in mainland China, and its performance is evaluated by comparing with the actual delay data and results of Airport Network Delays model. It is found that the proposed model is well-suited for simulating delays in air transport system where either airports or airspace could be the bottleneck of the system.; 143575

International audience; This paper proposes an effective approach for modelling and assessing the risks associated with unmanned aerial vehicles (UAVs) integrated into national airspace system (NAS). Two critical hazards with UAV operations are considered and analyzed, which are ground impacts and midair collisions. Threats to fatalities that result from the two hazards are the focus in the proposed method. In order to realize ground impact assessment, a multifactor risk model is designed by calculating system reliability required to meet a target level of safety for different UAV categories. Both fixed-wing and rotary-wing UAVs are taken into account under a real scenario that is further partitioned into different zones to make the evaluation more precise. Official territory and population data of the operation scenario are incorporated, as well as UAV self-properties. Casualty area of impacting debris can be obtained as well as the probability of fatal injuries on the ground. Sheltering factors are not neglected and defined as four types based on the real scenario. When midair collision fatality risk is estimated, a model of aircraft collisions based on the density of civil flight in different regions over Chinese airspace is proposed. In the model, a relative collision area and flying speed between UAVs and manned aircraft are constructed to calculate expected frequency of fatalities for each province correspondingly. Truthful data with different numbers of UAVs is incorporated in the model with the expected number of fatalities after a collision is included. Experimental simulations are made to evaluate the ground impacts and midair collisions when UAVs operate in the NAS.

In this paper, an efficient trajectory planning system is proposed to solve the integration of arrivals and departures on parallel runways with a novel route network system. Our first effort is made in designing an advanced Point Merge (PM) route network named Multi-Level Point Merge (ML-PM) to meet the requirements of parallel runway operations. Then, more efforts are paid on finding a complete and efficient framework capable of dynamically modelling the integration of arrival and departure trajectories on parallel runways, modelling the conflict detection and resolution in presence of curved trajectory and radius-to-fix merging process. After that, a suitable mathematical optimization formulation is built up. Receding Horizon Control (RHC) and Simulated Annealing (SA) algorithms are proposed to search the near-optimal solution for the large scale trajectories in routine dense operations. Taking Beijing Capital International Airport (BCIA) as a study case, the experimental results show that our system shows good performances on the management of arrivals and departures. It can automatically solve all the potential conflicts in presence of dense traffic flows. With its unique ML-PM route network, it can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, an economical climbing for departure aircraft, an easier runway allocation together with trajectory control solutions. It shows a good and dynamic sequencing efficiency in Terminal Manoeuvring Area (TMA). In mixed ML-PM mode, under tested conditions, our proposed system can increase throughput at BCIA around 26%, compared with baseline. The methodology defined here could be easily applied to airports worldwide. Refereed/Peer-reviewed

International audience; 4D trajectory prediction is the core element of future air transportation system, which is intended to improve the operational ability and the predictability of air traffic. In this paper, we introduce a novel hybrid model to address the short-term trajectory prediction problem in Terminal Manoeuvring Area (TMA) by application of machine learning methods. The proposed model consists of two parts: clustering-based preprocessing and Multi-Cells Neural Network (MCNN)-based prediction. Firstly, in the preprocessing part, after data cleaning, filtering and data re-sampling, we applied principal Component Analysis (PCA) to reduce the dimension of trajectory vector variable. Then, the trajectories are clustered into several patterns by clustering algorithm. Using nested cross validation, MCNN model is trained to find out the appropriate prediction model of Estimated Time of Arrival (ETA) for each individual cluster cell. Finally, the predicted ETA for each new flight is generated in different cluster cells classified by decision trees. To assess the performance of MCNN model, the Multiple Linear Regression (MLR) model is proposed as the comparison learning model, and K-means++ and DBSCAN are proposed as two comparison clustering models in preprocessing part. With real 4D trajectory data in Beijing TMA, experimental results demonstrate that our proposed model MCNN with DBSCAN in preprocessing is the most effective and robust hybrid machine learning model, both in trajectory clustering and short-term 4D trajectory prediction. In addition, it can make an accurate trajectory prediction in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) with regards to comparison models.

This paper was partially funded by grants from the CSC No 201506830050 and by the SESAR Joint Undertaking under grant agreement No 699338. —This paper proposes a method to synchronize traffic flow optimization and sector opening scheduling, with the aim of achieving flexible demand and capacity balancing (DCB). Delay assignment, trajectory options and sector collapsing are used to manage the traffic demand, while sector opening schemes are to affect the airspace capacity. Mixed Integer Programming (MIP) model is built to incorporate these initiatives. Three model variants are presented to illustrate the synchronization process, and their results in a real-world case study demonstrate some promising improvements for the DCB performances. Index Terms—air traffic flow management, trajectory options, dynamic sectorization, demand and capacity balancing

International audience; Functional airspace blocks (FAB) concept is adopted by the European airspace to allows cooperation between airspace users to manage the air trac ow, while ensuring eciency, safety, and fairness without the constraints of geographical boundaries. This integration of airspaces allow for exibility in airspace management and aircraft tra-jectory planning. This paper proposes a distributed air-trac ow management model to address four-dimensional (4D) trajectory planning over the European FAB. The proposed method is based on a meta-heuristic approach which uses a hybrid algorithm of simulated annealing and hill-climbing local search to separate a given set of aircraft trajectories in space and time domain (we term this as ight interaction), by allocating an alternative ight plan (route and departure time) to each ight. An innovative data structure, termed as FAB-Flight interaction matrix, captures the ight interaction in-1 Associate Professor, School of Mechanical and Aerospace Engineering, 1 formation between and within FABs. The proposed distributed model is implemented and tested with two air trac data sets comprising of 4,000 ights (3 hours trac) and 26,000 ights (one full day trac data over the European airspace). The performance of the model is then compared with a centralized air-trac ow management model on scalability and interaction minimization. Results indicates that, though both the approaches were able to achieve interaction-free trajectory planning within computational time acceptable for the operational context, distributed model converges faster to interaction-free solution as trac size increases; which shows the viability of the distributed model for eective FAB implementation.

International audience; Congestion in Terminal Maneuvering Area (TMA) in hub airports is the main problem in Chinese air transportation. In this paper we propose a new system to integrated sequence and merge aircraft to parallel runways at Beijing Capital International Airport (BCIA). This system is based on the advanced avionics capabilities. Our methodology integrates a Multi-Level Point Merge (ML-PM) system, an economical descent approaches procedure, and a tailored heuristic algorithm to find a good, systematic, operationally-acceptable solution. First, Receding Horizontal Control (RHC) technique is applied to divide the entire 24 h of traffic into several sub-problems. Then in each sub-problem, it is optimized on given objectives (conflict, deviation from Estimated Time of Arrival (ETA) on the runway and makespan of the arrival flow). Four decision variables are designed to control the trajectory: the entry time, the entry speed, the turning time on the sequencing leg, and the landing runway allocation. Based on these variables, the real time trajectories are generated by the simulation module. Simulated Annealing (SA) algorithm is used to search the best solution for aircraft to execute. Finally, the conflict-free, least-delay, and user-preferred trajectories from the entry point of TMA to the landing runway are defined. Numerical results show that our optimization system has very stable de-conflict performance to handle continuously dense arrivals in transition airspace. It can also provide the decision support to assist flow controllers to handle the asymmetric arrival flows on different runways with less fuel consumption, and to assist tactical controllers to easily re-sequence aircraft with more relaxed position shifting. Moreover, our system can provide the fuel consumption prediction, and runway assignment information to assist airport and airlines managers for optimal decision making. Theoretically, it realizes an automated, cooperative and green control of routine arrival flows. Although the methodology defined here is applied to the airport BCIA, it could also be applied to other airports in the world.

En Normandie, la connaissance des dynamiques hydrosédimentaires des cours d'eau pendant la mise en place des nombreux aménagements hydrauliques au cours du Moyen-Âge et de l’Époque moderne est très fragmentaire. On connaît mal les rythmes d'érosion et de sédimentation des cours d'eau normands durant les deux derniers millénaires ainsi que les forçages anthropiques et climatiques qui ont influencé ces processus. L'enjeu est aujourd'hui de comprendre et de mesurer la part des héritages hydrauliques dans le fonctionnement actuel des cours d’eau afin d’aider à leur gestion contemporaine. Pour apporter des éléments de réponse, des recherches géomorphologiques et géoarchéologiques ont été menées dans la moyenne vallée de la Seulles. Celles-ci mettent en exergue le poids des aménagements hydrauliques et notamment les aménagements liés aux moulins dans la mise en place de la plaine alluviale. La structuration complète du cours d'eau depuis le Moyen-Âge central a complètement transformé le tracé de la Seulles ainsi que la pente de la ligne d'eau. Elle a cloisonné le lit mineur favorisant sa stabilité latérale et la sédimentation par débordement dans la plaine alluviale. Cela est visible en de nombreux sites comme celui du Heuzé. Cette structuration et l'accélération de la sédimentation limoneuse qui l’accompagne depuis 600 ans sont à l'origine de la mise en place d'un équilibre dynamique et des formes hydrosédimentaires de la Seulles actuelle. L'abandon de la gestion des installations hydrauliques ou leur destruction depuis une cinquantaine d'années viennent remettre en cause cet équilibre. There is fragmentary knowledge of the hydrosedimentary dynamics of rivers in Normandy during the installation of numerous watermills dating from the Middle-Ages and onwards. The rates of erosion and sedimentation that have occurred in Norman Rivers over the last two millennia are poorly understood as are the anthropogenic and climatic forces which have influenced these processes. The current issue is to understand and measure the inheritances in the current functioning of rivers in order to help with their contemporary management. To provide answers, geomorphological and geoarchaeological research has been carried out in the middle of the Seulles valley. These studies highlight the effects of the hydraulic structures, particularly mills in the past floodplain dynamics. Indeed, the complete control of water flow since the Middle-Ages has completely artificialized the riverbed, the channel slope and partitioned the river favouring lateral stability and overbank sedimentation. Watermill construction was locally accompanied by a simplification of the course of the Seulles as on the Heuzé site where a large part of the current course is artificial. These artificial changes to the river course and the acceleration of silt sedimentation in the floodplain since the medieval period are responsible for the establishment of a new and lasting dynamic equilibrium and the hydrosedimentary forms of the current Seulles River. The end of the management of these hydraulic structures and their destruction during the last fifty years has had its effect on the natural balance of the river.

International audience; Air traffic across the North Atlantic airspace has witnessed an incessant increase over the last decades. However, the efficiency of trans-Atlantic air traffic management is still low nowadays due to the limited radar coverage. Automated Dependent Surveillance-Broadcast systems represents an opportunity to enhance the strategic flight planning over the oceans by reducing separation standards between aircraft. Besides, the strong winds present a challenge for oceanic flights. Therefore, flying on the wind-optimal routes will save significantly both fuel and time. In this paper, we propose a new trans-Atlantic route structure that benefits from the jetstreams in order to construct wind-optimal flight trajectories. Then, we introduce an optimization model for detecting and resolving conflicts. The analysis is carried out on real traffic data to prove the efficiency of the proposed method. Experimental findings show an improvement in terms of conflict resolution and induced delays.

International audience; Traditionally airport systems have been studied using an approach in which the different elements of the system are studied independently. Until recently scientific community has put attention in developing models and techniques that study the system using holistic approaches for understanding cause and effect relationships of the integral system. This chapter presents a case of an airport in which the authors have implemented an approach for improving the turnaround time of the operation. The novelty of the approach is that it uses a combination of simulation, parameter analysis and optimization for getting to the best amount of vehicles that minimize the turnaround time of the airport under study. In addition, the simulation model is such that it includes the most important elements within the aviation system, such as terminal manoeuvring area, runway, taxi networks, and ground handling operation. The results show clearly that the approach is suitable for a complex system in which the amount of variables makes it intractable for getting good solutions in reasonable time.

Passengers' experience is becoming a key metric to evaluate the air transportation system's performance. Efficient and robust tools to handle airport operations are needed along with a better understanding of passengers' interests and concerns. Among various airport operations, this paper studies airport gate scheduling for improved passengers' experience. Three objectives accounting for passengers, aircraft, and operation are presented. Trade-offs between these objectives are analyzed, and a balancing objective function is proposed. The results show that the balanced objective can improve the efficiency of traffic flow in passenger terminals and on ramps, as well as the robustness of gate operations., This paper is submitted to the tenth USA/Europe ATM 2013 seminar

Although advance future avionics will enable full compliance with the given trajectory, there are many uncertainty sources that can deflect aircraft from their intended positions. In this article, we investigate potential of robust trajectory planning, considered as an additional demand management action, as a means to alleviate the en route congestion in airspace. Robust trajectory planning (RTP) involves generation of congestion-free trajectories with minimum operating cost taking into account uncertainty of trajectory prediction and unforeseen event. The model decision variables include ground delay, change of horizontal route, and vertical profile (flight level) to resolve congestion problem. The article introduces a novel approach for route generation (3D trajectory) based on homotopic feature of continuous functions. It is shown that this approach is capable of generating a large number of route shapes with a reasonable number of decision variables. RTP problem is modeled as a mixed-variable optimization problem, and it is solved using stochastic methods. The model is tested on a real-life example from the French airspace. The results indicate that, under certain conditions, at the expense of a small increase of total planned costs, it is possible to increase robustness of the proposed solution providing a good alternative to the solutions given by existing conflict-free trajectory planning models.

In Sudanian savannas, frequent fires are required to maintain a mix of trees and grasses. After a century of long conflict over fire utilisation and resource management, arising from colonial scientists reacting against traditional practice, fire has become a management tool used to shape tropical vegetation. Many examples show that fire is allowed and used in protected areas, and more recently, tolerated in West African countrysides. If fires are no longer viewed as 'evil' for African landscapes, fire setting remains a problem. Nowadays, fire ecology and the savanna concept focus on fire seasonal temporality, and create a new and more specific category of contested fires, or late-season fire, referred to in this paper as 'bad fires'. This specific category generally conceives fire as a biophysical element, which leads to savanna degradation. This paper examines the reality of 'bad fires' in the Western Burkina Faso through a space-time analysis to investigate the existence of an annually seasonal pattern of fires created by peasants. Using spatial association (I_Moran) on active fire MODIS products, we are able to demonstrate a deterministic regional pattern occurring over six years (from 2004 to 2009). Results of this study confirm the importance of a close study of fire in its temporal dimension with respect to temporality in burning practices. Conclusions show that the details of timing in fire-setting are key and also bring us new perspectives to understanding fire collective management at a local scale and new elements for climate modelling at a global scale.

International audience; Hydrosedimentary fluxes that run from agricultural plots down to the water streams are currently associated with many social, economic and environmental issues such as diffuse pollution, soil infertility, soil loss, floods, etc. While the genesis of these transfers are well-known at the scale of the agricultural plot, flow dynamics occurring on slopes remain poorly understood. This is especially the case in the small basins located in the north-western part of France, where the landscape mosaic, which includes linear networks (hedges, roads, ditches...), tends to complicate the processes. Analyzing the transfer conditions is important for a further integrated watershed management. Hence, in this paper, we propose to use a multi-agent system as a support decision tool to understand the role of anthropogenic linear networks on runoff pathways. We carried out a so-called bottom-up approach, to measure the effects of the local interactions between each linear element on the global hydrological behavior of the watershed. A first spatial analysis index, characterizing the impact of linear networks in the path of runoff, is constructed here from numerical simulations. The results of this study also tend to demonstrate the relevance of Multi-Agent Systems as diagnostic tools to the hydrosedimentary transfers and processes.; De nombreux enjeux socio-économiques et environnementaux sont associés aux transferts hydro-sédimentaires qui s’organisent au sein des hydrosystèmes, depuis les parcelles agricoles jusqu’aux cours d’eau: pollution diffuse, diminution de la fertilité des sols, pertes en sol, crues turbides, etc. Si les conditions d’initiation de ces transferts sont bien connues à l’échelle de la parcelle agricole, les dynamiques d’écoulements qui se produisent sur les versants restent mal connues, et ce particulièrement dans les petits hydrosystèmes bocagers du nord-ouest de la France, où la mosaïque paysagère et notamment la présence plus ou moins importante de réseaux linéaires (haies, routes, fossés…) tend à complexifier leur dynamique spatiale. Connaître les conditions de transfert est pourtant nécessaire en vue d’une gestion intégrée des bassins versants. Aussi, cette étude propose d’utiliser la simulation multi-agents comme outils d’aide à la décision pour mieux appréhender le rôle des réseaux linéaires d’origines anthropiques sur le parcours des écoulements de surface. L’approche menée, dite ascendante, permet d’analyser l’importance des interactions locales qui ont lieu entre chaque entité linéaire pour mieux comprendre le comportement hydrologique global d’un bassin versant. Un premier indice d'analyse spatiale, caractérisant l’impact des réseaux linéaires sur le parcours des écoulements de surface, est proposé ici à partir des simulations numériques. Cet article ouvre également une discussion méthodologique en analysant la pertinence des systèmes multi-agents en tant qu’outils de diagnostic et d’aide à la gestion des espaces sensibles aux processus de transferts hydro-sédimentaires.

This article won two awards : Best of Session (SE/TFM) Award Best Undergraduate Student Paper Award; International audience; Air Traffic Flow Management (ATFM) aims at structuring traffic in order to reduce congestion in airspace. Congestion being linked to aircraft located at the same position at the same time, ATFM organizes traffic in the spatial dimension (e.g. route network) and/or in the time dimension (sequencing and merging in TMA, Miles-in-Trail for en-route airspace). The objective of this paper is to develop a methodology that allows the traffic to self-organize in the time dimension when demand is high. This structure disappears when the demand diminishes. In order to reach this goal, a multi-agent system has been developed. In this system, aircraft agents regulate speed and delay departure time in order to reduce the number of conflicts, thus decreases overall traffic complexity, which becomes easier to manage by air traffic controllers. This algorithm was applied on realistic examples.

The North Atlantic Airspace (NAT) accommodates traffic between Europe and North America. This area is considered as the most congested oceanic airspace in the world. Radar-Based surveillance is not applied in the most of the oceanic area due to its limited coverage. So, aircraft become obliged to follow predefined routes called Organized Track System (OTS). These routes require very restrictive separation standards which limit the traffic of aircraft. Thus, a new kind of communication system, called Automated Dependence Surveillance Broadcast (ADS-B), has been introduced in order to afford the aircraft a reliable communication with both controllers and surrounding traffic. Hence, aircraft crossing the NAT will be able to follow more flexible routes, which will improve significantly the air traffic situation over this area. In this paper, we propose a strategic planning 1 model that overcomes the constraints of the OTS system in order to produce the closest routes to the direct ones of aircraft. This method is based on flocking boid model. It provides us with satisfying results on a portion of one day traffic over the NAT airspace.

International audience; The need for increasing air-traffic capacity motivates planning air- craft trajectories in 4D (space+time). In order to generate sets of conflict-free 4D trajectories, we introduce a new natural-paradigm al- gorithm: the light propagation algorithm (LPA). This algorithm is a wavefront propagation method that yields natural solutions for the path planning problem, specifically in the case of air-traffic congestion. Indeed, LPA yields very encouraging results on real-world day of traffic over France while satisfying the specific constraints of air-traffic management.

International audience; This paper first introduces an original trajectory model using B-splines and a new semi-infinite programming formulation of the separation constraint involved in air traffic conflict problems. A new continuous optimization formulation of the tactical conflict-resolution problem is then proposed. It involves very few optimization variables in that one needs only one optimization variable to determine each aircraft trajectory. Encouraging numerical experiments show that this approach is viable on realistic test problems. Not only does one not need to rely on the traditional, discretized, combinatorial optimization approaches to this problem, but, moreover, local continuous optimization methods, which require relatively fewer iterations and thereby fewer costly function evaluations, are shown to improve the performance of the overall global optimization of this non-convex problem.

International audience; Pricing policies could encourage airline companies to modify departure times and routes of their flights in order to reach a route-slot allocation target that minimizes the en-route congestion. The problem of restricting the number of price levels and the assignment of one price level to each sector at each time period is studied using a simulation based on a Logit discrete choice model. In this model, an option is defined as the combination of a departure time and a route. For each flight, a utility is associated to each option and takes into account the flying cost, the cost of ground delay and the prices of crossed sectors. The optimization of the pricing policy considers average flows and minimizes the quadratic difference between desired and expected flows on each option. A heuristic algorithm that involves successive iterations of simulated annealing and gradient methods performs this optimization. The simulated annealing assigns a price level to each sector at each time period, and the gradient algorithm computes new values of price levels. The test of the method on constructed examples indicates that the use of only four price levels does not significantly deteriorate the performance of the system with respect to the use of independent prices.

International audience; In the SESAR framework (Single European Sky ATM Research), the need to increase the air traffric capacity motivated the 4D (space + time) aircraft trajectory planning. This paper deals with an important Air Traffic Management (ATM) problem that consists in generating sets of 4D conflict-free trajectories (the tactical planning problem). The Light Propagation Algorithm (LPA) was introduced in [1] to deal with this problem. LPA has recently been shown to manage successfully a full day of traffic over the French airspace, removing all conflicts while satisfying ATM constraints. In this paper, we adapt the LPA to take into account uncertainties in trajectory prediction. We introduce and test a new algorithm called u/LPA (LPA under uncertainty) on the same day of traffic. For some situations, uncertainties reduce so much the search space that the standard algorithm cannot guarantee conflict free situation. As a consequence, one must include some time constraints for few trajectories (so-called RTA points: Real Time of Arrival constraints) in order to remove the remaining conflicts. The goal of RTA points is to impose an aircraft to be at a specified position at some given time. This results into a new optimization formulation of the tactical trajectory planning problem involving the decision as to where/when RTA points should be imposed. In order to solve this new problem, here we are content with a simple heuristic that yields encouraging results.

Les campagnes cotonnières de l’ouest du Burkina Faso ont été bouleversées durant les cinquante dernières années. Une transition agraire et démographique a conduit à une forte diminution des espaces de brousse. Nous avons mené une phase de photo interprétation sur une « petite région » comprenant une dizaine de villages le long de la forêt classée du Tui. Nous proposons une description des tendances spatiales à l’aide de différents indicateurs (forme, structure, etc.), puis une synthèse sur les interactions entre l’espace protégé et les espaces villageois. Nous montrons que, même si depuis plus de cinquante ans l’espace de la forêt classée est protégé, les habitants n’ont pas toujours connu les mêmes règles d’accès à cette zone. Les droits de culture accordés dans les années 1950/60 n’existent plus et les déguerpissements des champs se sont accélérés au cours des années 1990. La transition agraire couplée à la forte volonté de protection a conduit à la différenciation récente de deux unités, l’une agricole et l’autre de conservation de la nature. A cette échelle d’observation, la saturation agricole apparaît forte. Une seconde approche basée sur les cycles cultures/jachères à une échelle plus fine distingue alors différents patrons spatiaux. Cette échelle montre que la forte augmentation des surfaces cultivées ne fait pas disparaitre les brousses de manière systématique, certaines exploitations semblent continuer la pratique de la culture temporaire. Au final, ce travail met en évidence l’importance de l’articulation entre les échelles spatiales et temporelles pour l’étude des dynamiques dans ces régions. Cotton countryside in the Western Burkina Faso has rapidly evolved over the last fifty years. Agrarian and demographic transition has led to an important decline in bush areas. A phase of photo interpretation was conducted on a spatial extent comprising a dozen villages along the protected area of the Tui. After a description of spatial patterns with the help of various indicators (shape, structure ...), a summary of the interactions between the protected area and humanized places is proposed. This study shows that even if this area has been protected for 50 years, rules of access to this area have evolved. The rights for cropping of in the 1950’s and 60’s did not exist, and fields eviction were accelerated in the 1990’s. The agrarian transition coupled with strong desire of protection produce then a recent differentiation of two units, one agricultural and one of nature conservation. On this scale of observation, space competition seems to be important. A second approach based on crop/fallow cycles on a finer scale then distinguishes different spatial and dynamics patterns. This broader scale shows that the large increase in cultivated area does not lead to bush extinction. Some farm units continue the practice of shifting cultivation. Ultimately, this work highlights the importance of the relationship between spatial and temporal scales for studying dynamics in this region.

Best student paper award. Best paper in the ATM Capacity Improvements track award. Best paper of session award.; International audience; This paper presents a new approach for merging multiple aircraft flows in a Terminal Maneuvering Area (TMA). This work is motivated by the current overloaded airspace near large airports and the need of more efficient methods to help controllers. Some attempts to alleviate airspace congestion such as the minimum spacing requirements, negotiation of voluntary reductions in scheduled service, and the construction of additional runways at major airports have been done. Even though, more fundamental changes are needed to improve the use of available air capacity. Present research consists of a new approach to optimize a set of aircraft planned to land at a given airport; it is proposed to merge the incoming flows from different routes by mean of speed and path changes. Due to the high combinatoric induced by such a problem, a stochastic optimization algorithm has been developed in order to propose to each aircraft a new route and speed profile. Those changes aim to remove conflicts at merging points and to maintain separation of aircraft following the same route link according to their wake turbulence constraint. The optimization criteria is based on the minimum deviation from the initial path planning. This algorithm has been successfully applied to Gran Canaria airport in Spain with real traffic demand samples for which conflict free flow merging is produced smoothly with optimal runway feeding.

International audience; This paper presents a new air traffic complexity metric based on dynamical systems. Based on a set of radar observations (position and speed) a vector field interpolating these data is constructed. Once the field has been obtained, the Lyapunov spectrum of the associated dynamical system is computed on points evenly spaced on a spatial grid. The results of the computations are summarized on complexity maps, with high values indicating areas to avoid or to carefully monitor. A first approach based on linear dynamical system enable to compute an aggregate complexity metric. In order to produce complexity maps, two extensions of the previous approach have been developed (one in space and another in space and time). Finally, an approximation is proposed in order to localize the computation of the vector field by the mean of Local Linear Models.

International audience; The objectives of Air Traffic Management (ATM) system is to ensure safe and efficient operation of an individual flight as well as to maximize the overall capacity and minimize the adverse environmental impacts of the air transportation system. To achieve these objectives, airspace capacity, which drives capacity and traffic flow management policies, should be more properly estimated according to the detailed traffic configuration. There have been some efforts to describe the complexity of a traffic situation based on the idea of modeling airspace onto a dynamical system. This paper extends the previous research efforts by accounting for uncertainties on aircraft's positions and velocities. The proposed method is illustrated with examples.

International audience; This paper presents a new method for 3D cutting of geometrical space with application to airspace sectoring. This problem comes from the air traffic management but the proposed method may be applied to many other areas. This problem consists in finding a cutting of a 3D volume into sectors in order to balance the weights of sectors and which minimizes the flow cut on sector boundaries. A mathematical modeling of this problem has been proposed for which state space, objective functions and constraints are defined. The complexity of such problem being NP_Hard, stochastic optimization have been used to address it. An Evolutionary Algorithm has been implemented for which chromosome coding and operators have been developed. Realistic problem instances have been tested on this algorithm for which the solutions produced fulfill our objective.

In the department of Seine-Maritime, in Northern France, muddy floods are flow phenomena widely observed causing property and sometimes dramatic human damages. Such type of floods remains still seldom analysed in this region because they present complex and single features, especially occurring on dry valleys where no permanent stream flows exist. This complexity is both due to hydrologic and morphological structures, and also to infraand inter- annual changes on land covers fluctuating with cropping practices. In this study, we propose to coupling with GIS the use of a Geographical Cellular Automata (RuiCells) for assessing the morphological behaviour of 4 studied catchments and creating diagnosis of erosion sensibility. Dynamic simulations of runoff waters and flow pathways also provide a mediation tool between farmers and scientifics in order to change practices for reducing soil erosion and runoff production in these small areas., En Seine-Maritime, le ruissellement érosif pose d'importants problèmes : source de pollution de la ressource en eau, il est également à l'origine d'événements chroniques, parfois catastrophiques, d'inondations par crue turbide. Ces phénomènes sont complexes et difficiles à quantifier : une complexité liée autant aux structures hydromorphologiques en place qu'à la variabilité infra- et interannuelle des couverts agricoles. En complément du SIG, l'utilisation d'un outil de modélisation à base d'automate cellulaire a permis d'apprécier plus finement le comportement des bassins et d'établir un diagnostic des sensibilités au ruissellement pour les espaces considérés. Au-delà de sa fonction de modélisation, cet outil est venu appuyer le « dialogue » et la concertation dans le cadre d'une recherche visant à modifier les pratiques individuelles des exploitants agricoles.

This article deals with the exploitation of statistical information from extremes values of an evolutionary algorithm.

In the past, the first way to reduce the congestion of the Air Traffic Control System was to modify the structure of the airspace in order to increase the capacity (increasing the number of runways, increasing the number of sectors by reducing their size). This method has a limit due to the cost involved by new runways and the way to manage traffic in too small sectors (a controller needs a minimum amount of airspace to solve conflicts). The other way to reduce congestion is to modify the flight plans in order to adapt the demand to the available capacity. So, to reduce congestion, demand has to be spread in spatial and time dimension (route-slot allocation). Our research addresses the general time-route assignment problem using a static and a dynamic approach. A state of the art of the existing methods shows that this general bi-allocation problem is usually partially treated and the whole problem remains unsolved due to the induced complexity. GAs are then adapted to the problem. A sector congestion measure has been developed which gather the major control workload indicators. This measure is then computed for each proposed planning by referring to an off-line simulation. New problem-based stochastic operators have been developed and successfully applied on real instances of the problem.

International audience; The ability of air traffic controllers to deal with complex situations is a limiting factor in airspace capacity. The underlying airspace structure and other procedural elements are thought to be important factors in reducing a controller's cognitive complexity through the use of structure based abstractions. Because cognitive complexity cannot be directly observed it must be investigated indirectly. This paper discusses and presents examples of how directly observable states and controllers' subjective responses can be used to indirectly probe and gain insight into how structure based abstractions are used to manage cognitive complexity.

International audience; This paper presents new concepts to address the air traffic complexity modeling problem. Two new geometrical metrics have been introduced and have been found very useful to capture typical features of traffic complexity. The covariance metric is very adapted to identify disorder in a set of speed vectors and can be applied for en route airspace (en route airspace is the airspace between airports). Similarly, the Koenig metric identifies easily the curl movement organizations and can be applied to areas around airports where air traffic control procedures impose turns on aircraft trajectories.

Morphological talweg analysis and scaling behaviour: applying non-integer dimension to physical geography. -- The organisation of the talweg network is fundamental to the erosion system on the silty loamy plateaux of north-western France. The morphology of the Pays de Caux is a good example of successive runoff concentration caused by the nesting of small dry valleys. These are inherited from a periglacial climate and their general direction is governed by tectonics. However the detailed pattern of these forms remains complex and without obvious explanation. Non-integer dimensions may offer a ceratin logic to this relatively chaotic pattern. This paper has therefore sought to demonstrate the fractal side of these talwegs by incorporating lithology as an explanatory variable., L'organisation du réseau de talwegs est fondamentale dans le fonctionnement du système d'érosion des plateaux limoneux du Nord-Ouest de la France. Le relief du pays de Caux montre la concentration croissante du ruissellement imposé par l'emboîtement des vallons secs. Ces derniers sont hérités d'un climat périglaciaire et leur direction générale est commandée par la tectonique. Toutefois, le dessin de ces formes dans le détail reste complexe et sans explication évidente. Ce tracé d'aspect désordonné semble trouver une certaine logique d'organisation au sein des dimensions non entières. C'est pourquoi nous avons cherché à démontrer le comportement sealant de ces talwegs, ainsi qu'à mesurer leur dimension fractale, tout en intégrant la lithologie et les symétries tectoniques comme variables explicatives.