Intelligent Transportation System (ITS) provides a great platform for the planners to reduce environmental externalities from auto. We now have access to real time data. We have been using shortest path to provide route choice to the user. But we have the potential to add more variables in choosing routes. Real time data can be used to measure carbon di-oxide emission during a trip. Also, fuel efficiency can be measured using the real time data. Planners should use this potential of ITS to reduce the environmental impact. This paper thus try to evaluate if considering three variables shortest path, environmental impact and fuel efficiency together instead of only shortest path will change the route choice or not. It provides case studies on different types of routes and between different sets of origin /destination to evaluate the combined influence of these three variables on route choice.

Le besoin de se déplacer est un besoin fondamental dans la vie de tous les jours. Avec l’extension continue des zones urbaines, l’augmentation de la population et l’amélioration du niveau de vie des citoyens, le nombre de voitures ne cesse d’augmenter. Ceci étant, la plupart des transports publics proposés aujourd’hui obéissent à des règles qui manquent de souplesse et qui incluent rarement le caractère dynamique, en temps et en espace, de la demande. Cela réduit ainsi l’attractivité de ces services et les rendant même parfois difficilement supportables. De ce fait, la majorité des usagers utilisent encore leur propre véhicule. Ce grand nombre de véhicules, qui est en augmentation continue sur les réseaux routiers, provoque de nombreux phénomènes de congestion induisant une surconsommation de carburant, des émissions inutiles de gaz à effet de serre et une perte de temps importante. Pour y remédier, nous proposons dans cette thèse de nouveaux systèmes de déplacement des usagers avec différents modèles d’optimisation pour la mobilité partagée (covoiturage et taxis-partagés) ainsi que la combinaison de la mobilité partagée avec les transports publics. Les expérimentations sont réalisées sur de vrais réseaux routiers ainsi que sur des données réelles. Ces nouveaux systèmes améliorent considérablement la qualité de service des systèmes classiques existants en termes de coût et de flexibilité tout en ayant un temps de calcul raisonnable. / The travelling is a fundamental part of everyday life. The continuous expansion of urban areas combined with the population increasing and the improvement of life standards increases the need of mobility and the use of private cars. Furthermore, the majority of public transportations are subject to rules lacking of flexibility and rarely taking into account the dynamic context. The attractiveness of public transportation is therefore reduced and, as a consequence, its financial support, resulting in a further deterioration of the public services quality and flexibility. Therefore, the majority of users still use their own vehicles. The number of vehicles is continuously increasing on road networks causing important phenomena of congestion, high fuel consumption and emissions of greenhouse gases, time loss. This unpleasant situation forces communities to consider alternative solutions for the mobility such as ride-sharing, an interesting alternative to solo car use. The overall objective of this thesis is to propose new travel systems for users through the introduction of optimization models for shared mobility (ride-sharing and taxi-sharing) and the combination of shared mobility and public transportation. The computational experiments are carried out on real road networks and real data. Our numerical results show the effectiveness of our approach, which improves the quality of service compared to the traditional systems in terms of cost and flexibility. The running time remains reasonable to allow using our framework in real-time transportation applications.

Software engineering projects that utilize inappropriate pathfinding algorithms carry a significant risk of poor runtime performance for customers. Using social network theory, this experimental study examined the impact of algorithms, frameworks, and map complexity on elapsed time and computer memory consumption. The 1,800 2D map samples utilized were computer random generated and data were collected and processed using Python language scripts. Memory consumption and elapsed time results for each of the 12 experimental treatment groups were compared using factorial MANOVA to determine the impact of the 3 independent variables on elapsed time and computer memory consumption. The MANOVA indicated a significant factor interaction between algorithms, frameworks, and map complexity upon elapsed time and memory consumption, F(4, 3576) = 94.09, p < .001, h2 = .095. The main effects of algorithms, F(4, 3576) = 885.68, p < .001, h2 = .498; and frameworks, F(2, 1787) = 720,360.01, p .001, h2 = .999; and map complexity, F(2, 1787) = 112,736.40, p < .001, h2 = .992, were also all significant. This study may contribute to positive social change by providing software engineers writing software for complex networks, such as analyzing terrorist social networks, with empirical pathfinding algorithm results. This is crucial to enabling selection of appropriately fast, memory-efficient algorithms that help analysts identify and apprehend criminal and terrorist suspects in complex networks before the next attack.

Energy is a limited source in wireless sensor networks and in most applications, it is non-renewable / so designing energy-effcient communication patterns is very important. In this thesis, we de

Disasters (e.g. earthquakes) and emergencies (e.g. fire) threaten the safety of occupants in the buildings and cause injuries and mortalities. These harmful effects are even more dangerous when secondary hazards (e.g. post-earthquake fires) emerge and it is commonly observed that the disasters/emergencies trigger secondary hazards.An effective indoor emergency guidance and navigation approach for occupants and first responders can decrease the number of injuries and mortalities during building emergencies by improving the evacuation process and response operations. For this reason, this research will propose a model-based guidance and vulnerability assessment approach for facilities that are under the threat of multi-hazard emergencies. The approach can be used to guide occupants from the facility affected by disasters/emergencies to safer zones and to direct the first responders by supplying them necessary building related information such as identified vulnerable locations in the indoor environments. An integrated utilization of Building Information Modeling tools, sensors, shortest path algorithms, and vulnerability assessment algorithms is proposed for the system in this research. The research steps of this thesis include (1) determination of requirements of an indoor navigation during emergency response and disaster management,(2) review, comparison, and evaluation of shortest path algorithms from an emergency response and disaster management point of view, (3) proposing a vulnerability assessment approach, and (4) proposing a real-time indoor emergency guidance and navigation system framework for buildings under the threat of multi-hazard emergencies. The findings of the research can be used in future studies on emergency response and disaster management domains.

L’utilisation des réseaux de transport est conditionnée par l’efficacité et la simplicité de leur utilisation. En réponse à une mobilité exacerbée, volontaire ou subie, l’offre de transport se développe et motive tout à la fois, en un cycle continu, des déplacements encore plus exigeants. De manière complémentaire, la mobilité est bousculée par l’arrivée de nouvelles modalités de transport pouvant faire émerger, comme dans le cadre du covoiturage, des acteurs ou des pratiques jusqu’alors inexistants. Si la technologie permet de suivre cette évolution dans les services d’information aux voyageurs, il reste toujours à satisfaire des attentes déterminées par des usages en constante évolution. C’est de ce point de vue que l’obtention de chemins multiples pour relier une origine à une destination est un facteur qui n’est plus à négliger, surtout dans des réseaux de transport denses et comportant de nombreux modes et lignes de transport. Une liberté dans le choix laissé à l’utilisateur du réseau réduit les sentiments d’exclusion, d’incompréhension ou d’anxiété qui peuvent survenir face à une application logicielle ou sur internet et qui effectuent des choix arbitraires de façon autoritaire. De plus, cela permet de vérifier la qualité de l’offre de transport, car plus il existe de moyens différents pour effectuer un trajet dans un intervalle de temps donné, meilleur est le service. Cette thèse s’intéresse au calcul de telles alternatives par le biais de l’énumération par coût croissant des chemins entre deux points, puis par le filtrage de ceux-ci suivant des critères, supposés quelconques et laissés à l’appréciation des professionnels de transport qui peuvent ainsi faire varier les angles d’analyses de leurs offres.Par ailleurs, la synchronisation de trajets de plusieurs utilisateurs, en vue d’usages sociaux ou de déplacements mutualisés, est étudiée dans ce manuscrit sous l’angle du covoiturage. En ne considérant que deux usagers, l’objectif est de minimiser le temps de trajet global des participants sous la contrainte qu’ils partagent une partie de leur chemin entre un point de rencontre et un point de séparation qu’il faut alors déterminer. Sont également étudiées les variantes associées au changement des conditions de transport de chacun des participants comme l’établissement d’une origine ou d’une destination commune parallèlement à des contraintes sur les heures de départ ou d’arrivée des usagers. Enfin, puisque la voiture est très souvent pénalisée par la prise en charge d’un piéton, il convient d’étudier comment ce détour peut être contraint et les impacts sur les gains que cette limitation engendre.Cette thèse a été réalisée dans un contexte CIFRE pour la société MobiGIS. Lestravaux qui s’y rapportent ont fait l’objet de réalisations pratiques tant pour fournirdes solutions de mobilité dans le cadre des activités de l’entreprise que pour évaluerexpérimentalement les performances des algorithmes proposés pour les résoudre. / Efficiency and simplicity are two conditions upon which the use of a transportation system is relevant. May it be intentional or imposed, an increasing mobility triggers the need to enhance the transportation offer. In turn, such a response encourages an even more demanding mobility in a constantly adapting cycle. In parallel, new and forthcoming means of transportation emerge from time to time with unknown practices and renewed actors : exactly like what carpooling is stirring at the moment. Passenger information systems can technically deal with such evolutions thanks to improved technologies but they still struggle to keep up with constantly changing usage expectations.From this perspective the computation of several paths from an origin to a destination becomes increasingly relevant. This issue is even more crucial in dense transportation networks in which many modes and lines of transportation are combined. Indeed, giving some traveling choices to the end user reduces the feeling of exclusion, anxiety and the lack of understanding which may arise when facing arbitrary decisions dictated by a software or an Internet application. It is also helpful to estimate the quality of the transportation offer since the more paths exist to go from point A to point B within a fixed time window, the better the service is. This thesis focuses on the computation of such alternatives by the gradually increasing enumeration of paths between two points. Given this input, the pruning necessary to obtain such a diverse selection is assumed not to be known in advance. It is left up to transportation professionals who may choose a fitted solution based on their specific knowledge and objectives.Another subject studied in this thesis concerns the itinerary synchronization of several users for various social uses such as shared travels. It is here seen from the perspective of carpooling. Considering only two users, the problem is to minimize the traveling cost of the users under the constraint that they must share some part of their respective trips with one another. Solving this problem is equivalent to finding a pick up point and a drop off location between which both paths overlap. Multiple corner cases concerning the transportation conditions of each user as well as the special cases of shared origins or destinations are studied. The constraints on the arrival and/or departure times may also vary. Last but not least and since the driver is often penalized when giving up a lift, the restriction to a maximal detour the driver accepts, compared to his shortest path, is analyzed with respect to the benefits such a limitation generates.This thesis was funded by the MobiGIS company under the CIFRE (Industrial Agreement of Training through Research) researching context. The related work consisted in the practical implementation of mobility solutions within the framework of the company as well as the experimental performances evaluation of the algorithms proposed to solve them.

This thesis examines some of the best known algorithms for solving the shortest point-to-point path problem, and evaluates their performance on real metropolitan area networks. The focus has mainly been on Dijkstra‟s algorithm and different variations of it, and the algorithms have been implemented in C# for the practical tests. The size of the networks used in this study varied between 358 and 2464 nodes, and both running time and representative operation counts were measured. The results show that many different factors besides the network size affect the running time of an algorithm, such as arc-to-node ratio, path length and network structure. The queue implementation of Dijkstra‟s algorithm showed the worst performance and suffered heavily when the problem size increased. Two techniques for increasing the performance were examined: optimizing the management of labelled nodes and reducing the search space. A bidirectional Dijkstra‟s algorithm using a binary heap to store temporarily labelled nodes combines both of these techniques, and it was the algorithm that performed best of all the tested algorithms in the practical tests. This project was initiated by Netadmin Systems i Sverige AB who needed a new path finding module for their network management system NETadmin. While this study is primarily of interest for researchers dealing with path finding problems in computer networks, it may also be useful in evaluations of path finding algorithms for road networks since the two networks share some common characteristics.

Dans cette thèse, nous étudions plusieurs modèles de routage efficaces en énergie. Pour chaque modèle, nous présentons une formulation en programmation linéaire mixte permettant de trouver une solution exacte. En outre, comme il s’agit de problèmes NP-Difficiles, nous proposons des heuristiques efficaces pour des réseaux de grande taille. Dans la première partie de cette thèse, nous étudions une solution de routage efficace en énergie dans laquelle nous ajoutons la possibilité d’éliminer des redondances dans les paquets transmis sur le réseau. Nous montrons premièrement que l’ajout de l’élimination des redondances permet d’améliorer l’efficacité énergétique des réseaux en éteignant plus de liens. Ensuite, nous étendons le modèle afin qu’il prenne en compte un certain niveau d’incertitudes dans le volume de trafic et le taux de redondances. La deuxième partie de cette thèse est consacrée aux problèmes qui se posent lors du déploiement de tels protocoles dans les réseaux. Plus particulièrement, nous proposons de minimiser les changements entre deux configurations réseaux consécutives lorsque plusieurs matrices de trafic sont considérées. Le routage des demandes étant alors assuré avec le protocole de routage OSPF (Open Shortest Path First). Ensuite, nous abordons le problème de la limitation du nombre de règles de routage dans les routeurs en utilisant une technologie de type SDN (Software Defined Networks). Enfin, nous présentons en annexe des travaux complémentaires réalisés au cours de cette thèse concernant le routage multicast et le contrôle de congestion TCP. / In this thesis, we study several models of energy-Aware routing. For each model, we present a linear programming formulation to find the exact solution. Moreover, since energy-Aware routing is NP-Hard problem, we also propose efficient heuristic algorithms for large scale networks. In the first part of this thesis, we deal with GreenRE - a new energy-Aware routing model with the support of redundancy elimination. We first present a deterministic model in which we show how to combine energy-Aware routing and redundancy elimination to improve energy efficiency for backbone networks. Then, we extend the model in order to take into account uncertainties in traffic volumes and redundancy rates. The second part of this thesis is devoted to the deployment issues of energy- aware routing in practice. In detail, to avoid service deterioration for end-Users, we limit changes of network configurations in multi-Period traffic matrices in Open Shortest Path First (OSPF) protocol. Next, we address the problem of limited rule space in OpenFlow switches when installing energy-Aware routing configurations. Finally, we present in the appendix other works developed during this thesis: multicast network protocol and TCP congestion control algorithm.

Data processing for Big Data plays a vital role for decision-makers in organizations and government, enhances the user experience, and provides quality results in prediction analysis. However, many modern data processing solutions make a significant investment in hardware and maintenance costs, such as Hadoop and Spark, often neglecting the well established and widely used relational database management systems (RDBMS's). In this dissertation, we study three fundamental graph problems in RDBMS. The first problem we tackle is computing shortest paths (SP) from a source to a target in large network graphs. We explore SQL based solutions and leverage the intelligent scheduling that a RDBMS performs when executing set-at-a-time expansions of graph vertices, which is in contrast to vertex-at-a-time expansions in classical SP algorithms. Our algorithms perform orders of magnitude faster than baselines and outperform counterparts in native graph databases. Second, we studied the PageRank problem which is vital in Google Search and social network analysis to determine how to sort search results and identify important nodes in a graph. PageRank is an iterative algorithm which imposes challenges when implementing it over large graphs. We study computing PageRank using RDBMS for very large graphs using a consumer-grade machine and compare the results to a dedicated graph database. We show that our RDBMS solution is able to process graphs of more than a billion edges in few minutes, whereas native graph databases fail to handle graphs of much smaller sizes. Last, we present a carefully engineered RDBMS solution to the problem of triangle enumeration for very large graphs. We show that RDBMS's are suitable tools for enumerating billions of triangles in billion-scale networks on a consumer grade machine. Also, we compare our RDBMS solution's performance to a native graph database and show that our RDBMS solution outperforms by orders of magnitude. / Graduate

Many modern mobile communication devices are equipped with a GPS receiver and anavigation tool. These devices are useful when a user seeks to reach a specified destinationas soon as possible, but may not be so when he/she only needs to arrive at thedestination in time and wants to focus on some activities on the way. To deal with thislatter situation, a method and device called “Space Time Alarm Clock” is presented forhelping the user reach the destination by a specified deadline and inform the user aboutthe consequences of his/her decisions. It does so by continuously and efficiently computinghow much more time the user may stay at his/her current location without failing toreach the destination by the deadline. Furthermore, it determines the possible movementchoices that a user can make with regards to an underlying road network, it computesthe shortest travel time associated with each choice and informs the user about the consequencesof his/her decisions. Advantage of this approach is that it works completelyin the background so that the user‘s en-route activities will never be interfered with. The“Space Time Alarm Clock” was implemented for Stockholm, where it was tested.