Dans le contexte du futur système de gestion du trafic aérien, un des objectifs consiste à réduire l’impact environnemental du trafic aérien. Pour respecter ce but, le concept de “free-route”, introduit dans les années 1990, semble bien adapté aujourd’hui. Les avions ne seraient plus contraints à voler le long de routes aériennes, mais pourraient suivre des trajectoires optimales en terme de consommation. L’objectif de cette thèse est d’introduire une nouvelle méthode de planification du trafic à l’horizon pré-tactique avec des objectifs quelques fois contradictoires, c’est-à-dire avec pour but de minimiser la consommation ou de façon équivalente la durée de trajet en tenant compte des conditions météorologiques et de minimiser l’encombrement de l’espace aérien.La méthode a été mise au point en deux étapes. La première étape a été consacrée au calcul d’une seule trajectoire optimale en terme de temps de vol en tenant compte du vent et de contraintes celles des zones interdites de survol. Cette optimisation est basée sur une adaptation de l’algorithme Ordered Upwind. La deuxième étape introduit un algorithme hybride développé, basé sur un algorithme de recuit simulé et sur l’algorithme déterministe développé dans la première étape, afin de minimiser un compromis entre la congestion et la consommation. L’algorithme combine ainsi la capacité d’atteindre la solution optimale globale via une recherche locale qui permet d’accélérer la convergence.Des simulations numériques avec des prévisions de vent sur du trafic européen donnent des résultats encourageants qui démontrent que la méthode globale est à la fois viable et bénéfique en terme du temps de vol total comme de la congestion globale donc de la diminution des conflits / In the context of the future Air Traffic Management system (ATM), one objective is to reduce the environmental impact of air traffic. With respect to this criterion, the “freeroute” concept, introduced in the mid 1990’s, is well suited to improve over nowadays airspace based ATM. Aircraft will no longer be restricted to fly along airways and may fly along fuel-optimal routes. The objective of this thesis is to introduce a novel pretactical trajectory planning methodology which aims at minimizing airspace congestion while taking into account weather conditions so as to minimize also fuel consumption.The development of the method was divided in two steps. The first step is dedicated to compute a time-optimal route for one aircraft taking into account wind conditions. This optimization is based on an adaptation of the Ordered Upwind Method on the sphere.The second step introduces a hybrid algorithm, based on simulated annealing and on the deterministic algorithm developed in the first step, in order to minimize congestion. Thus the algorithm combines the ability to reach a globally-optimal solution with a local-search procedure that speeds up the convergence.

Road network of a region is of a paramount importance in the overall development. Management of road traffic is a key factor for the city authority and reducing the road traffic congestion is a significant challenge in this perspective. In this thesis, a Wireless Sensor Network (WSN) based road-traffic monitoring scheme with dynamic mathematical traffic model is presented that will not necessarily include all adjacent intersections of a block; rather the important major intersections of a city. The objective of this scheme is to reduce the congestion by re-routing the vehicles to better performing road-segments by informing the down-stream drivers through broadcasting the congestion information in a dedicated radio channel. The dynamic model can provide with the instantaneous status of the traffic of the road-network. The scheme is a WSN based multi-hop relay network with hierarchical architecture and composed of ordinary nodes, Cluster-Head nodes, Base Stations, Gateway nodes and Monitoring and Control Centers (MCC) etc. Through collecting the traffic information, MCC will check the congestion status and in defining the congestion, threshold factors have been used in this model. For the congested situation of a road-segment, a cost function has been defined as a performance indicator and estimated using the weight factors (importance) of these selected intersections. This thesis considered a traffic network with twelve major intersections of a city with four major directions. Traffic arrivals in these intersections are assumed to follow Poisson distribution. Model was simulated in Matlab with traffic generated through Poisson Random Number Generator and cost function was estimated for the congestion status of the road-segments over a simulation period of 1440 minutes starting from midnight. For optimization purpose we adopted two different approaches; in the first approach, performance of the scheme was evaluated for all threshold factor values iteratively one at a time, applying a threshold factor value to define threshold capacities of all the road segments; traffic was generated and relative cost has been estimated following the model specifications with the purpose of congestion avoidance. In the second approach, different values of threshold factor have been used for different road segments for determining the optimum set-up, and exhaustive search technique has been applied with a smaller configuration in order to keep computations reachable. Simulation results show the capacity of this scheme to improve the traffic performance by reducing the congestion level with low congestion costs.

Road network of a region is of a paramount importance in the overall development. Management of road traffic is a key factor for the city authority and reducing the road traffic congestion is a significant challenge in this perspective. In this thesis, a Wireless Sensor Network (WSN) based road-traffic monitoring scheme with dynamic mathematical traffic model is presented that will not necessarily include all adjacent intersections of a block; rather the important major intersections of a city. The objective of this scheme is to reduce the congestion by re-routing the vehicles to better performing road-segments by informing the down-stream drivers through broadcasting the congestion information in a dedicated radio channel. The dynamic model can provide with the instantaneous status of the traffic of the road-network. The scheme is a WSN based multi-hop relay network with hierarchical architecture and composed of ordinary nodes, Cluster-Head nodes, Base Stations, Gateway nodes and Monitoring and Control Centers (MCC) etc. Through collecting the traffic information, MCC will check the congestion status and in defining the congestion, threshold factors have been used in this model. For the congested situation of a road-segment, a cost function has been defined as a performance indicator and estimated using the weight factors (importance) of these selected intersections. This thesis considered a traffic network with twelve major intersections of a city with four major directions. Traffic arrivals in these intersections are assumed to follow Poisson distribution. Model was simulated in Matlab with traffic generated through Poisson Random Number Generator and cost function was estimated for the congestion status of the road-segments over a simulation period of 1440 minutes starting from midnight. For optimization purpose we adopted two different approaches; in the first approach, performance of the scheme was evaluated for all threshold factor values iteratively one at a time, applying a threshold factor value to define threshold capacities of all the road segments; traffic was generated and relative cost has been estimated following the model specifications with the purpose of congestion avoidance. In the second approach, different values of threshold factor have been used for different road segments for determining the optimum set-up, and exhaustive search technique has been applied with a smaller configuration in order to keep computations reachable. Simulation results show the capacity of this scheme to improve the traffic performance by reducing the congestion level with low congestion costs.