Cette thèse est consacrée au domaine interdisciplinaire des Systèmes de Transport Intelligents et des technologies de Réalité Virtuelle. Elle se concentre sur l’amélioration des stratégies de commande des véhicules intelligents en tenant compte des impacts de l’environnement naturel ainsi que sur l’analyse de performance, la visualisation et la vérification de la validité des algorithmes de commande sur la plateforme de véhicules intelligents réalité virtuelle (IVVR).La plateforme IVVR comprend trois sous-systèmes : un sous-système de commande de véhicules intelligents, un sous-système de visualisation et un sous-système virtuel sans fil. Le synthétique environnement naturel a été modélisé et simulé pour la simulation et l’analyse de performance des stratégies de commande sous conditions environnementales complexes. Ensuite, les expérimentations concernant le trafic équipé du régulateur de vitesses adaptatives (ou coopérative) sont exécutés et ils montrent que les systèmes existants ont échoué à maintenir une espace inter-véhiculaire de sécurité lorsque les conditions d’environnement naturel sont défavorables. Dans ce cas, nous proposons un nouvel algorithme de commande appelé NECACC pour le contrôle longitudinal du véhicule en maintenant une espace inter-véhiculaire de sécurité et garantissant une capacité de circulation optimisée même dans des conditions environnementales complexes. Cet algorithme est ensuite simulé, vérifié et validé sur la plateforme IVVR. Enfin, les démonstrations de trafic virtuel effectuant des manœuvres communes de circulation contrôlés par les systèmes de commande intégrés proposées sont présentées sous diverse conditions environnementales / This thesis is dedicated to the interdisciplinary area of Intelligent Transportation Systems and Virtual Reality technologies. It focuses on the improvement of intelligent vehicles control strategies by considering the natural environment impacts as well as the visualization, the verification and performance analysis of proposed control algorithms on the proposed Intelligent Vehicles Virtual Reality (IVVR) platform.The IVVR platform includes three subsystems: Vehicle Intelligent Control Subsystem, Visualization Subsystem and Virtual Wireless Subsystem. For realizing the control strategy simulation and performance analysis under complex natural environment conditions, Synthetic Natural Environment has been modeled and simulated in this IVVR platform. Therefore, experiments of Adaptive Cruise Control (ACC) or Cooperative ACC system equipped traffic are executed and show that normal ACC/CACC system fails to keep a safe inter-vehicle space when the natural environment condition is variable or adverse especially in stiff conditions. For solving this problem, we propose a new control algorithm called NECACC (Natural Environment based CACC) for longitudinal vehicle control in maintaining a safe inter-vehicle distance as well as guaranteeing an appropriate traffic capacity even under complex environmental conditions. This algorithm is then simulated and verified in IVVR platform as a “proof of concept”. Finally, some virtual traffic demonstrations performing common traffic maneuvers are presented in IVVR platform under various environmental conditions. The vehicle platoon is controlled by proposed integrated control system and the safety can be ensured all the time

This master's thesis deals with development of mobile app for measuring the range from the preceding vehicle in traffic using visual-based methods. This paper describes implementation of computer vision algorithms of detection and tracing objects, detection of horizon on desktop and mobile devices. Also deals with visual-based range measuring without any other mechanisms. The output of the work is implemented detectors of vihicles and horizon using OpenCV library on the Windows platfom and draft of user inerface of a mobile phone aplication on the Android platform.

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Future vehicles are expected to be equipped with wireless communication technology, that enables them to be “connected” to each others and road infrastructures. Complementing current autonomous vehicles and automated driving systems, the wireless communication allows the vehicles to interact, cooperate, and be aware of its surroundings beyond their own sensors’ range. Such sys- tems are often referred to as Cooperative Intelligent Transport Systems (C-ITS), which aims to provide extra safety, efficiency, and sustainability to transporta- tion systems. Several C-ITS applications are under development and will require thorough testing and evaluation before their deployment in the real-world. C- ITS depend on several sub-systems, which increase their complexity, and makes them difficult to evaluate. Simulations are often used to evaluate many different automotive applications, including C-ITS. Although they have been used extensively, simulation tools dedicated to determine all aspects of C-ITS are rare, especially human factors aspects, which are often ignored. The majority of the simulation tools for C-ITS rely heavily on different combinations of network and traffic simulators. The human factors issues have been covered in only a few C-ITS simulation tools, that involve a driving simulator. Therefore, in this thesis, a C-ITS simulation framework that combines driving, network, and traffic simulators is presented. The simulation framework is able to evaluate C-ITS applications from three perspectives; a) human driver; b) wireless communication; and c) traffic systems. Cooperative Adaptive Cruise Control (CACC) and its applications are chosen as the first set of C-ITS functions to be evaluated. Example scenarios from CACC and platoon merging applications are presented, and used as test cases for the simulation framework, as well as to elaborate potential usages of it. Moreover, approaches, results, and challenges from composing the simulation framework are presented and discussed. The results shows the usefulness of the proposed simulation framework.

Autonomous Driving Systems (ADS), a subcategory of Cyber-Physical Systems (CPS) are becoming increasingly popular with ubiquitous deployment. They provide advanced operational functions for perception and control, but this also raises the question of their safety capability. Such questions include if the vehicle can stay within its lane, keep a safe distance from the leading vehicle, or avoid obstacles, especially under the presence of uncertainties. In this master thesis, the operational safety of ADS will be addressed, more specifically on the Adaptive Cruise Control (ACC) system by modeling an optimal control problem based on Control Barrier Function (CBF) unified with Model Predictive Control (MPC). The corresponding optimal control problem is robust against measurement uncertainties for an Autonomous Vehicle (AV) driving on a highway, where the measurement uncertainties will represent the common faults in the perception system of the AV. A Kalman Filter (KF) is also added to the system to investigate the performance difference. The resulting framework is implemented and evaluated on a simulation scenario created in the open-source autonomous driving simulator CARLA. Simulations show that MPC-CBF is indeed robust against measurement uncertainties for well-selected horizon and slack variable values. The simulations also show that adding a KF improves the overall performance. The higher the horizon, the more confident the system becomes as the distance to the leading vehicle decreases. However, this may cause infeasibility where there are no solutions to the optimal control problem during sudden braking as the AV cannot brake fast enough before it crashes. Meanwhile, the smaller the slack variable, the more restrictive becomes CBF where it impacts more on the control input than desired which could also cause infeasibility. The results of this thesis will help to facilitate safety-critical CPS development to be deployed in real-world applications. / Autonoma körsystem (ADS), som är en del av cyberfysiska system (CPS), har blivit alltmer populär med allestädes närvarande användning. Det bidra med avancerade operativa funktioner för perception och styrning, men samtidig väcker detta också frågan om dess säkerhetsförmåga. Sådana frågor inkluderar om fordonet kan hålla sig inom sitt körfält, om det kan hålla ett säkert avstånd till det ledande fordonet eller om det kan undvika hinder, speciellt under osäkerheter hos systemet. I detta examensarbete kommer driftsäkerheten hos ADS att behandlas, mer specifik på adaptiv farthållare (ACC) genom att modellera ett optimalt kontrollproblem baserat på kontrollbarriärfunktion (CBF) förenat med modellförutsägande styrning (MPC). Motsvarande optimalt kontrollproblem är robust mot mätosäkerheter för ett autonomt fordon som kör på en motorväg, där mätosäkerheterna representerar vanliga fel i AV:s perceptionssystem. Ett Kalmanfilter (KF) läggs också till i systemet för att undersöka skillnaden i prestanda. Det resulterande ramverket implementeras och utvärderas på ett simuleringsscenario som skapats i den öppna källkodssimulatorn för autonom körning CARLA. Simulationer visar att MPC-CBF är robust mot mätosäkerheter för väl valda värden för horisont och slackvariabler. Det visar också att systemets prestanda förbättrats ännu mer om ett KF läggs till. Ju större horisont, desto mer självsäkert blir systemet när avståndet till det ledande fordonet minskar. Detta kan dock leda till att det inte finns några lösningar på det optimala kontrollproblemet vid plötslig inbromsning, eftersom fordonet inte hinner bromsa tillräckligt snabbt innan det kraschar. Ju mindre slackvariabeln är, desto mer restriktiv blir CBF som påverkar styrningen mer än vad som är önskvärt vilket också kan leda till olösbart optimalt kontrollproblem. Resultatet från detta examensarbete bär syftet att gynna utvecklingen av säkerhetkritisk CPS som ska användas i praktiska tillämpningar.

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In dieser Arbeit wurden nutzbringende Anwendungsmöglichkeiten für monoskopische und (auto)stereoskopische 3D-Anzeigen in Fahrzeugen theoretisch hergeleitet und empirisch überprüft. Zur Ableitung der Hypothesen wurde für jede Teilaufgabe anhand eines Fragenkatalogs zu den Vor- und Nachteilen von 3D-Anzeigen untersucht, inwieweit deren Bearbeitung davon profitiert, dass Informationen räumlich abgebildet werden. Die erwiesenen 3D-Vorteile wurden zu fünf Kategorien zusammengefasst: Integration, räumliche Kompatibilität, Aufmerksamkeitslenkung, Bildhaftigkeit und Attraktivität. Da der wesentliche 3D-Vorteil für Anzeigen in Fahrzeugen in einer räumlich kompatiblen Informationsdarstellung aus der Fahrerperspektive gesehen wurde, lag der Schwerpunkt der empirischen Arbeit auf 3D-Anzeigen für Fahrerassistenzsysteme (FAS). Am Beispiel einer 3D-Anzeige des Abstandsregeltempomaten (ART) wurde nachgewiesen, dass die Vorteile von 3D-Anzeigen für FAS in einer Erhöhung der Attraktivität und Akzeptanz sowie in einer Verbesserung des unmittelbaren Verständnisses im Vergleich zu 2D-Anzeigen liegen. Gleichzeitig wurden mit optimal gestalteten 3D-Anzeigen keine Nachteile in der Wahrnehmungssicherheit und Ablenkungswirkung festgestellt. Anhand der Literaturanalyse und der empirischen Ergebnisse wurden Gestaltungshinweise für 3D-Anzeigen in Fahrzeugen formuliert. Der erwartete 3D-Vorteil einer kompatiblen Darstellung stellte sich bei einer konstanten Anordnung der Informationen nicht ein, bleibt aber für Aufgaben mit einem kontinuierlichen Abgleich (z.B. Navigation) zu überprüfen. Die stereoskopische Darbietung erbrachte keinen besonderen Nutzen. Das fahrzeugtaugliche ASD erhöhte sogar die Reaktionszeiten. Insgesamt sprechen die Ergebnisse für eine gezielte Verwendung bildhafter monoskopischer 3D-Anzeigen für FAS und ausgewählte räumliche Funktionen, welche sich anhand von Begriffen und abstrakten Symbolen nur schwer erläutern lassen. / This thesis consists of the theoretical deduction and empirical evaluation of useful applications for monoscopic and (auto)stereoscopic 3D-displays in vehicles. For deducting hypotheses concerning the benefits and limits of 3D-displays, each subtask was tested for its potential benefits from a 3D-information presentation using a catalogue of confirmed advantages and disadvantages of 3D-displays. The proven 3D-advantages were summarized in five categories: integration, spatial compatibility, direction of attention, concreteness and attractiveness. Because it was presumed, that 3D-displays in vehicles are especially favorable for representing information about the vehicle surrounding in a 3D-perspective compatible to the drivers view, the empirical part was mainly focused on the application of 3D-displays for driver assistance systems. Using a 3D-display for adaptive cruise control (ACC), a general increase of attractiveness, acceptance and immediate comprehension for 3D-displays in comparison to conventional 2D-displays was confirmed. Simultaneously, well designed 3D-displays did not compromise perceptional safety and driver distraction. Design guidelines for 3D-displays in vehicles were concluded from the evaluation results and from literature analysis. Even though the expected 3D-benefit of spatially compatible information displays from the driver’s perspective was not confirmed for driver assistance systems like ACC with a constant layout of information, it still remains to be tested for continuous matching tasks like navigational checking in cars. The stereoscopic presentation of 3D-displays did not show advantages. On the contrary, an in-vehicle ASD even increased reaction times. In summery, the results suggest a distinctive application of well designed concrete and monoscopic 3D-displays for driver assistance systems and selected spatial functions which are difficult to explain using abstract notions or symbols.

Vehicular ad hoc networks (VANETs) are a hot topic in the intelligent transport system (ITS) area. The introduction of wireless communications between vehicles will enable many useful applications to enhance road traffic safety as well to increase efficiency. The standardization of IEEE 802.11p, being an amendment to IEEE 802.11 intended for VANETS, faces many challenges. In Europe a 30 MHz spectrum at 5.9 GHz have been dedicated for ITS and this spectrum has to be used to its full potential. For this reason this thesis compares a 20 MHz wide frequency channel with a 10 MHz wide through measurements using 802.11p hardware. The measurements were conducted on a highway with relative speeds of up to 240 km/h. The results from these initial measurements show that a 20 MHz channel does not perform worse than a 10 MHz channel despite the high relative speeds and large metal signs scattering the signals. What enabled this thesis to do the measurements was Halmstad University‟s participation in the Grand Cooperative Driving Challenge (GCDC) 2011. In GCDC nine teams mostly from Europe competed in having the vehicle that had the best behaviour in a platoon of vehicles using cooperative adaptive cruise control (CACC), the CACC algorithm controlled the vehicles‟ acceleration and breaking autonomously based on in-vehicle sensors and communicated messages between the vehicles in the platoon using 802.11p. This thesis implemented the communication part of Halmstad University‟s vehicle. The challenge was held in Helmond, Holland, May 14-15, 2011. Halmstad University‟s team finished in second place. / CoAct

The thesis is composed of two main parts. The first part deals with a microscopic traffic flow theory. Models describing the individual acceleration, deceleration and lane-changing behavior are formulated and the emerging collective traffic dynamics are investigated by means of numerical simulations. The models and simulation tools presented provide the methodical prerequisites for the second part of the thesis in which a novel concept of a traffic-adaptive control strategy for ACC systems is presented. The impact of such systems on the traffic dynamics can solely be investigated and assessed by traffic simulations. The focus is on future adaptive cruise control (ACC) systems and their potential applications in the context of vehicle-based intelligent transportation systems. In order to ensure that ACC systems are implemented in ways that improve rather than degrade traffic conditions, the thesis proposes an extension of ACC systems towards traffic-adaptive cruise control by means of implementing an actively jam-avoiding driving strategy. The newly developed traffic assistance system introduces a driving strategy layer which modifies the driver's individual settings of the ACC driving parameters depending on the local traffic situation. Whilst the conventional operational control layer of an ACC system calculates the response to the input sensor data in terms of accelerations and decelerations on a short time scale, the automated adaptation of the ACC driving parameters happens on a somewhat longer time scale of, typically, minutes. By changing only temporarily the comfortable parameter settings of the ACC system in specific traffic situations, the driving strategy is capable of improving the traffic flow efficiency whilst retaining the comfort for the driver. The traffic-adaptive modifications are specified relative to the driver settings in order to maintain the individual preferences. The proposed system requires an autonomous real-time detection of the five traffic states by each ACC-equipped vehicle. The formulated algorithm is based on the evaluation of the locally available data such as the vehicle's velocity time series and its geo-referenced position (GPS) in conjunction with a digital map. It is assumed that the digital map is complemented by information about stationary bottlenecks as most of the observed traffic flow breakdowns occur at these fixed locations. By means of a heuristic, the algorithm determines which of the five traffic states mentioned above applies best to the actual traffic situation. Optionally, inter-vehicle and infrastructure-to-car communication technologies can be used to further improve the accuracy of determining the respective traffic state by providing non-local information. By means of simulation, we found that the automatic traffic-adaptive driving strategy improves traffic stability and increases the effective road capacity. Depending on the fraction of ACC vehicles, the driving strategy "passing a bottleneck" effects a reduction of the bottleneck strength and therefore delays (or even prevents) the breakdown of traffic flow. Changing to the driving mode "leaving the traffic jam" increases the outflow from congestion resulting in reduced queue lengths in congested traffic and, consequently, a faster recovery to free flow conditions. The current travel time (as most important criterion for road users) and the cumulated travel time (as an indicator of the system performance) are used to evaluate the impact on the quality of service. While traffic congestion in the reference scenario was completely eliminated when simulating a proportion of 25% ACC vehicles, travel times were significantly reduced even with much lower penetration rates. Moreover, the cumulated travel times decreased consistently with the increase in the proportion of ACC vehicles. / In der Arbeit wird ein neues verkehrstelematisches Konzept für ein verkehrseffizientes Fahrverhalten entwickelt und als dezentrale Strategie zur Vermeidung und Auflösung von Verkehrsstaus auf Richtungsfahrbahnen vorgestellt. Die operative Umsetzung erfolgt durch ein ACC-System, das um eine, auf Informationen über die lokale Verkehrssituation basierende, automatisierte Fahrstrategie erweitert wird. Die Herausforderung bei einem Eingriff in das individuelle Fahrverhalten besteht - unter Berücksichtigung von Sicherheits-, Akzeptanz- und rechtlichen Aspekten - im Ausgleich der Gegensätze Fahrkomfort und Verkehrseffizienz. Während sich ein komfortables Fahren durch große Abstände bei geringen Fahrzeugbeschleunigungen auszeichnet, erfordert ein verkehrsoptimierendes Verhalten kleinere Abstände und eine schnellere Anpassung an Geschwindigkeitsänderungen der umgebenden Fahrzeuge. Als allgemeiner Lösungsansatz wird eine verkehrsadaptive Fahrstrategie vorgeschlagen, die ein ACC-System mittels Anpassung der das Fahrverhalten charakterisierenden Parameter umsetzt. Die Wahl der Parameter erfolgt in Abhängigkeit von der lokalen Verkehrssituation, die auf der Basis der im Fahrzeug zur Verfügung stehenden Informationen automatisch detektiert wird. Durch die Unterscheidung verschiedener Verkehrssituationen wird ein temporärer Wechsel in ein verkehrseffizientes Fahrregime (zum Beispiel beim Herausfahren aus einem Stau) ermöglicht. Machbarkeit und Wirkungspotenzial der verkehrsadaptiven Fahrstrategie werden im Rahmen eines mikroskopischen Modellierungsansatzes simuliert und hinsichtlich der kollektiven Verkehrsdynamik, insbesondere der Stauentstehung und Stauauflösung, auf mehrspurigen Richtungsfahrbahnen bewertet. Die durchgeführte Modellbildung, insbesondere die Formulierung eines komplexen Modells des menschlichen Fahrverhaltens, ermöglicht eine detaillierte Analyse der im Verkehr relevanten kollektiven Stabilität und einer von der Stabilität abhängigen stochastischen Streckenkapazität. Ein tieferes Verständnis der Stauentstehung und -ausbildung wird durch das allgemeine Konzept der Engstelle erreicht. Dieses findet auch bei der Entwicklung der Strategie für ein stauvermeidendes Fahrverhalten Anwendung. In der Arbeit wird die stauvermeidende und stauauflösende Wirkung eines individuellen, verkehrsadaptiven Fahrverhaltens bereits für geringe Ausstattungsgrade nachgewiesen. Vor dem Hintergrund einer zu erwartenden Verbreitung von ACC-Systemen ergibt sich damit eine vielversprechende Option für die Steigerung der Verkehrsleistung durch ein teilautomatisiertes Fahren. Der entwickelte Ansatz einer verkehrsadaptiven Fahrstrategie ist unabhängig vom ACC-System. Er erweitert dessen Funktionalität im Hinblick auf zukünftige, informationsbasierte Fahrerassistenzsysteme um eine neue fahrstrategische Dimension. Die lokale Interpretation der Verkehrssituation kann neben einer verkehrsadaptiven ACC-Regelung auch der Entwicklung zukünftiger Fahrerinformationssysteme dienen.