Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-01-10T15:45:26Z No. of bitstreams: 1 BrunnoFreireDantasDeOliveira_TESE.pdf: 6640940 bytes, checksum: ad49d75685e2ea80ce1bd97392f6f888 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-01-11T16:14:37Z (GMT) No. of bitstreams: 1 BrunnoFreireDantasDeOliveira_TESE.pdf: 6640940 bytes, checksum: ad49d75685e2ea80ce1bd97392f6f888 (MD5) / Made available in DSpace on 2017-01-11T16:14:37Z (GMT). No. of bitstreams: 1 BrunnoFreireDantasDeOliveira_TESE.pdf: 6640940 bytes, checksum: ad49d75685e2ea80ce1bd97392f6f888 (MD5) Previous issue date: 2016-07-26 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Determinar os mecanismos respons?veis pelos padr?es espaciais de biodiversidade t?m sido um dos maiores desafios para ec?logos e bioge?grafos. Durante a ?ltima d?cada houve um grande aumento no n?mero de estudos documentando padr?es de biodiversidade em larga escala. Atualmente, padr?es globais de riqueza de esp?cies s?o bem conhecidos para v?rios grupos de organismos. Entretanto, biodiversidade inclui v?rias dimens?es al?m da riqueza de esp?cies, como a diversidade filogen?tica e a diversidade funcional. Estas dimens?es s?o mais informativas do que simples medidas de riqueza de esp?cies e, consequentemente, podem permitir testes mais poderosos acerca de teorias de biodiversidade. Particularmente importante, conservar a biodiversidade em suas m?ltiplas dimens?es ? necess?rio para garantir a resili?ncia dos servi?os ecossist?micos e manter as hist?rias evolutivas das esp?cies. Neste contexto, a presente tese se configura na interface entre macroecologia e conserva??o, utilizando uma abordagem integradora que considera a conex?o entre mais de uma dimens?o da biodiversidade. No primeiro cap?tulo foram avaliadas hip?teses que invocam din?micas de equil?brio ou n?o-equil?brio para explicar a riqueza de esp?cies e diversidade funcional de mam?feros globalmente. Integrando informa??es sobre riqueza de esp?cies e diversidade funcional, eu abordo estas quest?es e clarifico os mecanismos que geraram e mant?m a diversidade de mam?feros e suas hist?rias de vida. O segundo cap?tulo representam uma base de dados sobre caracter?sticas biol?gicas de anf?bios globalmente: AmphiBIO. Esta base de dados centraliza informa??es sobre 19 caracter?sticas relacionadas ? ecologia, morfologia e reprodu??o de anf?bios. Os dados foram agregados a partir de mais de 1.500 fontes, e t?m potencial para auxiliar pesquisas mais amplas em ecologia de comunidades, evolu??o, biogeografia e conserva??o de anf?bios. No terceiro cap?tulo, utilizando o AmphiBIO, testo a suposi??o de que a perda de diversidade filogen?tica estaria associada ? perda de diversidade funcional. Para isso, a extin??o de anf?bios amea?ados foi simulada, as perdas de diversidade filogen?tica e funcional calculadas, e sua correla??o verificada. As perdas de diversidade foram analisadas atrav?s da filogenia dos anf?bios e do espa?o geogr?fico global. Esta tese contribui para um melhor entendimento dos mecanismos que originaram e mant?m os gradientes globais de riqueza de esp?cies, servindo de est?mulo para estudos futuros em ecologia e evolu??o, e para auxiliar decis?es pol?ticas visando a minimiza??o dos efeitos das extin??es sobre a perda de biodiversidade. / Determining the mechanisms underlying spatial variation in biodiversity has long been the main challenge for ecologists and biogeographers. The past decade has seen a veritable explosion of studies documenting broad-scale spatial patterns in biodiversity. Nowadays, broad-scale patterns of species richness (SR) are well documented for several groups. However, biodiversity encompass variation in several aspects beyond SR, such as phylogenetic diversity (PD) and functional (or trait) diversity (FD). These dimensions have been argued to aid more powerful tests of biodiversity theories because they can capture the diversity of life better than simple measures of SR. Particularly important, the conservation of biodiversity and its multiple dimensions have been advocated as necessary to ensure the resilience of ecosystem services and maintain important evolutionary history. The present thesis is set on the interface between macroecology and biodiversity conservation, and uses integrated approaches that consider the connection between more than one dimension of biodiversity. In the first chapter, I we evaluate four prominent hypotheses which invoke either equilibrium (more individuals, niche diversity) or non-equilibrium dynamics (diversification rate, evolutionary time) to explain species richness and functional diversity of mammals worldwide. While equilibrium and non-equilibrium hypotheses have received considerable attention in the literature and some empirical support, it remains unknown whether they can explain the diversity of species and their traits alike. By integrating information on species richness and functional diversity, I address these issues and shed light on the mechanisms that generated the diversity of mammals and their life histories. The second chapter represents a database on natural history traits for amphibians worldwide: AmphiBIO. This database centralizes information on 19 traits related to ecology, morphology and reproduction features of amphibians. Data were assembled from more than 1,500 sources, and has potential to support a more comprehensive research in evolution, community ecology, biogeography and conservation of amphibians. The third chapter uses information from AmphiBIO to test the assumption that loss of PD is associated with loss of FD. We simulated species extinction scenarios based on IUCN criteria, calculated the loss of PD and FD, and verified the correlation. Analyzes were carried out across the complete amphibian tree and across worldwide amphibian assemblages. This study highlights for the possible negative consequences of local amphibians extinctions that may impact the continuous provision of ecosystem services. This thesis adds to better understand the mechanisms on the origination of global gradients of species diversity. Finally, I hope this thesis can be used to stimulate future studies on ecology and evolution, and support political decisions on minimizing the effects of projected species extinctions on biodiversity loss.

Submitted by Patricia Barros (patricia.barros@ufes.br) on 2017-04-13T13:58:14Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao Rodrigo Ferreira Berriel.pdf: 18168750 bytes, checksum: 52805e1f943170ef4d6cc96046ea48ec (MD5) / Approved for entry into archive by Patricia Barros (patricia.barros@ufes.br) on 2017-04-13T14:00:19Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao Rodrigo Ferreira Berriel.pdf: 18168750 bytes, checksum: 52805e1f943170ef4d6cc96046ea48ec (MD5) / Made available in DSpace on 2017-04-13T14:00:19Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) dissertacao Rodrigo Ferreira Berriel.pdf: 18168750 bytes, checksum: 52805e1f943170ef4d6cc96046ea48ec (MD5) / FAPES / A detecção e análise da faixa de trânsito são tarefas importantes e desafiadoras em sistemas avançados de assistência ao motorista e direção autônoma. Essas tarefas são necessárias para auxiliar veículos autônomos e semi-autônomos a operarem com segurança. A queda no custo dos sensores de visão e os avanços em hardware embarcado impulsionaram as pesquisas relacionadas a faixa de trânsito –detecção, estimativa, rastreamento, etc. – nas últimas duas décadas. O interesse nesse tópico aumentou ainda mais com a demanda por sistemas avançados de assistência ao motorista (ADAS) e carros autônomos. Embora amplamente estudado de forma independente, ainda há necessidade de estudos que propõem uma solução combinada para os vários problemas relacionados a faixa do veículo, tal como aviso de saída de faixa (LDW), detecção de troca de faixa, classificação do tipo de linhas de divisão de fluxo (LMT), detecção e classificação de inscrições no pavimento, e detecção da presença de faixas ajdacentes. Esse trabalho propõe um sistema de análise da faixa do veículo (ELAS) em tempo real capaz de estimar a posição da faixa do veículo, classificar as linhas de divisão de fluxo e inscrições na faixa, realizar aviso de saída de faixa e detectar eventos de troca de faixa. O sistema proposto, baseado em visão, funciona em uma sequência temporal de imagens. Características das marcações de faixa são extraídas tanto na perspectiva original quanto em images mapeadas para a vista aérea, que então são combinadas para aumentar a robustez. A estimativa final da faixa é modelada como uma spline usando uma combinação de métodos (linhas de Hough, filtro de Kalman e filtro de partículas). Baseado na faixa estimada, todos os outros eventos são detectados. Além disso, o sistema proposto foi integrado para experimentação em um sistema para carros autônomos que está sendo desenvolvido pelo Laboratório de Computação de Alto Desempenho (LCAD) da Universidade Federal do Espírito Santo (UFES). Para validar os algorítmos propostos e cobrir a falta de base de dados para essas tarefas na literatura, uma nova base dados com mais de 20 cenas diferentes (com mais de 15.000 imagens) e considerando uma variedade de cenários (estrada urbana, rodovias, tráfego, sombras, etc.) foi criada. Essa base de dados foi manualmente anotada e disponilizada publicamente para possibilitar a avaliação de diversos eventos que são de interesse para a comunidade de pesquisa (i.e. estimativa, mudança e centralização da faixa; inscrições no pavimento; cruzamentos; tipos de linhas de divisão de fluxo; faixas de pedestre e faixas adjacentes). Além disso, o sistema também foi validado qualitativamente com base na integração com o veículo autônomo. O sistema alcançou altas taxas de detecção em todos os eventos do mundo real e provou estar pronto para aplicações em tempo real. / Lane detection and analysis are important and challenging tasks in advanced driver assistance systems and autonomous driving. These tasks are required in order to help autonomous and semi-autonomous vehicles to operate safely. Decreasing costs of vision sensors and advances in embedded hardware boosted lane related research – detection, estimation, tracking, etc. – in the past two decades. The interest in this topic has increased even more with the demand for advanced driver assistance systems (ADAS) and self-driving cars. Although extensively studied independently, there is still need for studies that propose a combined solution for the multiple problems related to the ego-lane, such as lane departure warning (LDW), lane change detection, lane marking type (LMT) classification, road markings detection and classification, and detection of adjacent lanes presence. This work proposes a real-time Ego-Lane Analysis System (ELAS) capable of estimating ego-lane position, classifying LMTs and road markings, performing LDW and detecting lane change events. The proposed vision-based system works on a temporal sequence of images. Lane marking features are extracted in perspective and Inverse Perspective Mapping (IPM) images that are combined to increase robustness. The final estimated lane is modeled as a spline using a combination of methods (Hough lines, Kalman filter and Particle filter). Based on the estimated lane, all other events are detected. Moreover, the proposed system was integrated for experimentation into an autonomous car that is being developed by the High Performance Computing Laboratory of the Universidade Federal do Espírito Santo. To validate the proposed algorithms and cover the lack of lane datasets in the literature, a new dataset with more than 20 different scenes (in more than 15,000 frames) and considering a variety of scenarios (urban road, highways, traffic, shadows, etc.) was created. The dataset was manually annotated and made publicly available to enable evaluation of several events that are of interest for the research community (i.e. lane estimation, change, and centering; road markings; intersections; LMTs; crosswalks and adjacent lanes). Furthermore, the system was also validated qualitatively based on the integration with the autonomous vehicle. ELAS achieved high detection rates in all real-world events and proved to be ready for real-time applications.

Research and development on vehicle safety has lately started to direct its focus towards how to actively support the driver and make it easier for her to drive safely through letting Advanced Driver Assistance Systems (ADAS) have effect on how the driver interacts with the vehicle and the surrounding traffic. This requires research on both how the driver and vehicle perform in different situations, in terms of psychology, cognition and individual differences. In addition, physical limitations and requirements of the driver and the vehicle must be taken into account. Therefore scenarios for evaluation of these systems are required. In the area of user-centered design a rather new method, Personas, is being adopted. This thesis tries to explore if the Persona method is a viable tool for creating scenarios for such evaluations. Experiences after completing this work imply that personas indeed is a viable way to include aspects and raise issues concerning individual variability and situational context in ADAS scenarios.

Les nouvelles voitures sont pourvues d’aides à la conduite qui améliorent le confort et la sécurité. Bien que ces systèmes contribuent à la réduction des accidents de la route, leur déploiement montre que leurs performances sont encore limitées par leur faible compréhension de situation. Cela est principalement lié aux limites des capteurs de perception, et à la non prise en compte du contexte. Ces limites se traduisent par des détections de risques tardives, et donc en assistances sous forme d’alertes ou de freinages automatiques. Cette thèse se concentre sur l’introduction d’informations contextuelles dans le processus de décision des systèmes d’aides à la conduite. Le but est de détecter des risques plus tôt que les systèmes conventionnels, ainsi que d’améliorer la confiance qu’on peut avoir dans les informations générées.Le comportement d’un véhicule dépend de divers éléments tels que le réseau routier, les règles de la circulation, ainsi que de la cohabitation avec d’autres usagers de la route. Ces interactions se traduisent par une interdépendance forte entre chaque élément. De plus, bien que chaque conducteur doive suivre les mêmes règles de circulation, ils peuvent réagir de façon différente à une même situation. Cela implique qu’un même comportement peut être considéré comme sûr ou risqué, selon le conducteur. Ces informations doivent être prises en compte dans le processus de prise de décision des systèmes. Cette thèse propose un cadre qui combine les informations a priori contenues dans les cartes de navigation numériques avec l’information temps réel fournie par les capteurs de perception et/ou communications sans fil, pour permettre une meilleure compréhension de situation et ainsi mieux anticiper les risques. Ce principe est comparable aux tâches qu’un copilote doit accomplir. Ces travaux se répartissent en deux principales étapes : la compréhension de situation, et l’estimation des risques.L’étape de compréhension de situation consiste à donner du sens aux différentes observations réalisées par les capteurs de perception, en exploitant des informations a priori. Le but est de comprendre comment les entités perçues interagissent, et comment ces interactions contraignent le comportement du véhicule. Cette étape établit les relations spatio-temporelles entre les entités perçues afin d’évaluer leur pertinence par rapport au véhicule, et ainsi extraire les entités les plus contraignantes. Pour cela, une ontologie contenant des informations a priori sur la façon dont différentes entités de la route interagissent est proposée. Cette première étape a été testée en temps réel, utilisant des données enregistrées sur un véhicule évoluant en environnements contraints.L’étape de détection des risques s’appuie sur la situation perçue, et sur les signes annonciateurs de risques. Le cas d’usage choisi pour cette étude se concentre sur les intersections, puisqu’une grande majorité des accidents de la route y ont lieux. La manière de réagir d’un conducteur lorsqu’il se rapproche d’une intersection est apprise par des Processus Gaussiens. Cette connaissance à priori du conducteur est ensuite exploitée, avec les informations contextuelles, par un réseau Bayésien afin d’estimer si le conducteur semble interagir comme attendu avec l’intersection. L’approche probabiliste qui a été choisie permet de prendre en compte les incertitudes dont souffrent chacune des sources d’information. Des tests ont été réalisés à partir de données enregistrées à bord d’un véhicule afin de valider l’approche. Les résultats montrent qu’en prenant en compte les individualités des conducteurs, leurs actions sur le véhicule, ainsi que l’état du véhicule, il est possible de mieux estimer si le conducteur interagit comme attendu avec l’environnement, et donc d’anticiper les risques. Finalement, il est montré qu’il est possible de générer une assistance plus préventive que les systèmes d’aide à la conduite conventionnels. / Modern vehicles include advanced driving assistance systems for comfort and active safety features. Whilst these systems contribute to the reduction of road accidents, their deployment has shown that performance is constrained by their limited situation understanding capabilities. This is mainly due to perception constraints and by ignoring the context within which these vehicles evolve. It results in last minute risk assessment, and thus in curative assistance in the form of warning alerts or automatic braking. This thesis focuses on the introduction of contextual information into the decision processes of driving assistance systems. The overall purpose is to infer risk earlier than conventional driving assistance systems, as well as to enhance the level of trust on the information provided to drivers.Several factors govern the vehicle behaviour. These include the road network and traffic rules, as well as other road users such as vehicles and pedestrians with which the vehicle interacts. This results in strong interdependencies amongst all entities, which govern their behaviour. Further, whilst traffic rules apply equally to all participants, each driver interacts differently with the immediate environment, leading to different risk level for a given behaviour. This information must be incorporated within the decision-making processes of these systems. In this thesis, a framework is proposed that combines a priori information from digital navigation maps with real time information from on board vehicle sensors and/or external sources via wireless communications links, to infer a better situation understanding, which should enable to anticipate risks. This tenet is similar to the task of a co-pilot when using a priori notated road information. The proposed approach is constrained by using only data from close to production sensors. The framework proposed in this thesis consists of two phases, namely situation understanding and risk assessment.The situation understanding phase consists in performing a high level interpretation of all observations by including a priori information within the framework. The purpose is to understand how the perceived road entities interact, and how the interactions constrain the vehicle behaviour. This phase establishes the spatio-temporal relationships between the perceived entities to determine their relevance with respect to the subject vehicle motion, and then to identify which entities to be tracked. For this purpose, an ontology is proposed. It stores a priori information about the manner how different road entities relate and interact. This initial phase was tested in real time using data recorded on a passenger vehicle evolving in constrained environments.The risk assessment phase then looks into the perceived situation and into the manner how it becomes dangerous. To demonstrate the framework applicability, a use case applied to road intersections was chosen. Intersections are complex parts in the road network where different entities converge and most accidents occur. In order to detect risk situations, the manner how the driver reacts in a given situation is learned through Gaussian Processes. This knowledge about the driver is then used within a context aware Bayesian Network to estimate whether the driver is likely to interact as expected with the relevant entities or not. The probabilistic approach taken allows to take into consideration all uncertainties embedded in the observations. Field trials were performed using a passenger vehicle to validate the proposed approach. The results show that by incorporating drivers’ individualities and their actuations with the observation of the vehicle state, it is possible to better estimate whether the driver interacts as expected with the environment, and thus to anticipate risk. Further, it is shown that it is possible to generate assistance earlier than conventional safety systems.

Indiana University-Purdue University Indianapolis (IUPUI) / Autonomous Emergency Braking (AEB) system uses vehicle’s on-board sensors such as radar, LIDAR, camera, infrared, etc. to detect the potential collisions, alert the driver and make safety braking decision to avoid a potential collision. Its limitation is that it requires clear line-of-sight to detect what is in front of the vehicle. Whereas, in current V2V (vehicle-to-vehicle communication) systems, vehicles communicate with each other over a wireless network and share information about their states. Thus the safety of a V2V system is limited to the vehicles with communication capabilities. Our idea is to integrate the complementary capabilities of V2V and AEB systems together to overcome the limitations of V2V and AEB systems. In a V2V-AEB system, vehicles exchange data about the objects information detected by their onboard sensors along with their locations, speeds, and movements. The object information detected by a vehicle and the information received through the V2V network is processed by the AEB system of the subject vehicle. If there is an imminent crash, the AEB system alerts the driver or applies the brake automatically in critical conditions to prevent the collision. To make V2V-AEB system advance, we have developed an intelligent heart Monitoring system and integrated it with the V2V-AEB system of the vehicle. The advancement of wearable and implantable sensors enables them to communicate driver’s health conditions with PC’s and handheld devices. Part of this thesis work concentrates on monitoring the driver’s heart status in real time by using fitness tracker. In the case of a critical health condition such as the cardiac arrest of a driver, the system informs the vehicle to take an appropriate operation decision and broadcast emergency messages over the V2V network. Thus making other vehicles and emergency services aware of the emergency condition, which can help a driver to get immediate medical attention and prevent accident casualties. To ensure that the effectiveness of the V2V-AEB system is not reduced by a time delay, it is necessary to study the effect of delay thoroughly and to handle them properly. One common practice to control the delayed vehicle trajectory information is to extrapolate trajectory to the current time. We have put forward a dynamic system that can help to reduce the effect of delay in different environments without extrapolating trajectory of the pedestrian. This method dynamically controls the AEB start braking time according to the estimated delay time in the scenario. This thesis also addresses the problem of communication overload caused by V2V-AEB system. If there are n vehicles in a V2V network and each vehicle detects m objects, the message density in the V2V network will be n*m. Processing these many messages by the receiving vehicle will take considerable computation power and cause a delay in making the braking decision. To prevent flooding of messages in V2V-AEB system, some approaches are suggested to reduce the number of messages in the V2V network that include not sending information of objects that do not cause a potential collision and grouping the object information in messages.

No description available.

Models based on micro-simulation of traffic flows have proven to be useful tools in the study of various traffic systems. Today, there is a wealth of traffic microsimulation models developed for freeway and urban street networks. The road mileage is however in many countries dominated by rural highways. Hence, there is a need for rural road traffic simulation models capable of assessing the performance of such road environments. This thesis introduces a versatile traffic micro-simulation model for the rural roads of today and of the future. The developed model system considers all common types of rural roads including effects of intersections and roundabouts on the main road traffic. The model is calibrated and validated through a simulation study comparing a two-lane highway to rural road designs with separated oncoming traffic lanes. A good general agreement between the simulation results and the field data is established. The interest in road safety and the environmental impact of traffic is growing. Recent research has indicated that traffic simulation can be of use in these areas as well as in traditional capacity and level-of-service studies. In the road safety area more attention is turning towards active safety improving countermeasures designed to improve road safety by reducing the number of driver errors and the accident risks. One important example is Advanced Driver Assistance Systems (ADAS). The potential to use traffic simulation to evaluate the road safety effects of ADAS is investigated in the last part of this thesis. A car-following model for simulation of traffic including ADAS-equipped vehicles is proposed and the developed simulation framework is used to study important properties of a traffic simulation model to be used for safety evaluation of ADAS. Driver behavior for ADAS-equipped vehicles has usually not been considered in simulation studies including ADAS-equipped vehicles. The work in this thesis does however indicate that modeling of the behavior of drivers in ADAS-equipped vehicles is essential for reliable conclusions on the road safety effects of ADAS. / <p>Report code: LiU-Tek-Lic-2005:60.</p>

Advanced Vehicle Systems promise improved safety and comfort for drivers. Steady advancements in technology are resulting in increasing levels of vehicle automation capabilities, furthering safety benefits. In fact, some of these vehicle automation systems are already deployed and available, but with promised benefits, such systems can potentially change driving behaviors. There is evidence that drivers have increased secondary task engagements while driving with automated vehicle systems, but there is a need for a clearer scientific understanding of any potential correlations between the use of automated vehicle systems and potentially negative driver behaviors. Therefore, this thesis aims to understand the state of knowledge on automated vehicle systems and their possible impact on drivers’ distraction behaviors. I have conducted two systematic literature reviews to examine this question. This thesis reports these reviews and examines the effects of secondary task engagement on driving behaviors such as take-over times, visual attention, trust, and workload, and discusses the implications on driver safety.

Autonomous driving is one of the key technologies for increasing road safetyand reducing traffic volumes. Therefore, science and industry are workingtogether on new innovative solutions in this field of technology. One importantcomponent in this context is the approval and testing of new solution concepts,with special focus on the ones for urban environments. Not only because ofthe high diversity of traffic situations, but also because of the close contactbetween vulnerable road users (VRU) and automated vehicles.In the course of this work, a novel approach for testing automated drivingfunctions and vehicle systems in urban environments is presented. The goal isto create a safe and valid environment in which the automated vehicle and theVRU can meet and interact. The basis is a highly realistic virtual model of acity center. The physical behavior of the vehicle and VRU is recorded usingmeasurement technology and transferred to the virtual city model.Based on representative urban traffic scenarios, the functionality of the urbantest field is investigated from various points of view. Thereby, the focus is onreal-time capability and the quality of interaction between the vehicle and theVRU.The investigations show that both the real-time capability and the interactionpossibilities could be demonstrated. Further, the developed methodologies aresuitable for real time applications. / CityInMotion

Pour résoudre les problèmes environnementaux et énergétiques liés au nombre croissant de véhicules en circulation, deux approches sont envisageables : l'une est technologique et vise à améliorer les composants du véhicule ou son architecture, l'autre est comportementale et cherche à changer la manière d'utiliser les véhicules. Dans ce contexte, l'éco-conduite représente une méthode, applicable immédiatement, permettant à chaque conducteur de réduire sa consommation. L'objectif de cette thèse est donc l'analyse des gains potentiels de l'éco-conduite pour les différents types de véhicules existant : thermique, électrique et hybride. Ainsi, la première partie de ce travail se focalise sur une étude théorique visant à calculer les gains potentiels et à déterminer les règles d'éco-conduite, avant d'aborder dans un second temps une mise en situation plus réaliste et une intégration des algorithmes dans un système d'assistance pour le conducteur. En s'appuyant sur une modélisation énergétique des différents types de véhicules, la détermination et la comparaison du fonctionnement optimal se base sur l'optimisation du profil de vitesse pour des trajets connus. La programmation dynamique a été mise enoeuvre pour calculer la trajectoire optimale énergétique en tenant compte de la contrainte temporelle afin de ne pas pénaliser l'intérêt d'une conduite économe. Evidemment, l'intégration de l'éco-conduite doit, d'une part, tenir compte du trafic à proximité du véhicule et d'autre part, ne pas aboutir à une augmentation des émissions de polluants. Ainsi, en nous appuyant sur des modèles de suivi de véhicules (trafic), nous avons montré que les principes d'éco-conduite restent valables et conduisent de toute façon à des gains énergétiques. Concernant les contraintes d'émissions, des résultats expérimentaux nous ont conduit à adapter nos algorithmes pour répondre simultanément aux aspects écologiques et économiques. Enfin, les connaissances acquises ont été appliquées à la conception d'un système d'assistance testé sur un simulateur de conduite. / The transportation sector has been identified as one of many sources of today's energetic and environmental problems. With constantly increasing numbers of vehicles on the road, non-renewable fossil fuels are becoming scarce and expensive. In addition, due to the pollutant emissions of internal combustion engines, the transportation sector is a major producer of greenhouse gas emissions. To resolve these problems researcher are looking for technological solutions, such as more efficient components and alternative drive train technologies, on one hand. On the other hand, work is being done to ensure the most efficient utilization of available technological resources. Eco driving is one way to immediately reduce a driver's energy consumption. In this thesis the potential gains of eco driving for passenger vehicles will be discussed. The main objective of this work is to, first, identify and compare drive train specific, optimal vehicle operation. Secondly, the effect of real-life constraints on potential gains of eco driving is evaluated. In addition, an approach to integrate mathematical optimization algorithms in an advanced driver assist system for eco driving is proposed. Physical vehicle models are developed for three representative vehicles: the conventional, electric and power-split hybrid vehicle. Using real-life and standard drive cycles a baseline mission is defined by specifying trip and road constraint. Applying the dynamic programming algorithms the trajectory optimization problem is solved, minimizing energy consumption for the trip. The effect of traffic on potential gains of eco driving is discussed, considering a vehicle following situation. Integrating emission constraints in the optimization algorithm the environmental advantages of eco driving are discussed. Finally, the developed algorithms were integrated in a driver assist system. Experimental tests on a driving simulator were used to verify the effectiveness of the system, as well as driver acceptance.