A receding horizon approach to string stable cooperative adaptive cruise control

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Model Predictive Control of Highway Emergency Maneuvering and Collision Avoidance

Autonomous emergency maneuvering (AEM) is an active safety system that automates safe maneuvers to avoid imminent collision, particularly in highway driving situations. Uncertainty about the surrounding vehicles’ decisions and also about the road condition, which has significant effects on the vehicle’s maneuverability, makes it challenging to implement the AEM strategy in practice. With the rise of vehicular networks and connected vehicles, vehicles would be able to share their perception and also intentions with other cars. Therefore, cooperative AEM can incor- porate surrounding vehicles’ decisions and perceptions in order to improve vehicles’ predictions and estimations and thereby provide better decisions for emergency maneuvering. In this thesis, we develop an adaptive, cooperative motion planning scheme for emergency maneuvering, based on the model predictive control (MPC) approach, for vehicles within a ve- hicular network. The proposed emergency maneuver planning scheme finds the best combination of longitudinal and lateral maneuvers to avoid imminent collision with surrounding vehicles and obstacles. To implement real-time MPC for the non-convex problem of collision free motion planning, safety constraints are suggested to be convexified based on the road geometry. To take advantage of vehicular communication, the surrounding vehicles’ decisions are incorporated in the prediction model to improve the motion planning results. The MPC approach is prone to loss of feasibility due to the limited prediction horizon for decision-making. For the autonomous vehicle motion planning problem, many of detected ob- stacles, which are beyond the prediction horizon, cannot be considered in the instantaneous de- cisions, and late consideration of them may cause infeasibility. The conditions that guarantee persistent feasibility of a model predictive motion planning scheme are studied in this thesis. Maintaining the system’s states in a control invariant set of the system guarantees the persis- tent feasibility of the corresponding MPC scheme. Specifically, we present two approaches to compute control invariant sets of the motion planning problem; the linearized convexified ap- proach and the brute-force approach. The resulting computed control invariant sets of these two approaches are compared with each other to demonstrate the performance of the proposed algorithm. Time-variation of the road condition affects the vehicle dynamics and constraints. Therefore, it necessitates the on-line identification of the road friction parameter and implementation of an adaptive emergency maneuver motion planning scheme. In this thesis, we investigate coopera- tive road condition estimation in order to improve collision avoidance performance of the AEM system. Each vehicle estimates the road condition individually, and disseminates it through the vehicular network. Accordingly, a consensus estimation algorithm fuses the individual estimates to find the maximum likelihood estimate of the road condition parameter. The performance of the proposed cooperative road condition estimation has been validated through simulations

Adaptive Cooperative Highway Platooning and Merging

As low-cost reliable sensors are introduced to market, research efforts in autonomous driving are increasing. Traffic congestion is a major problem for nearly all metropolis'. Assistive driving technologies like cruise control and adaptive cruise control are widely available today. While these control systems ease the task of driving, the driver still needs to be fully alert at all times. While these existing structures are helpful in alleviating the stress of driving to a certain extent, they are not enough to improve traffic flow. Two main causes of congestion are slow response of drivers to their surroundings, and situations like highway ramp merges or lane closures. This thesis will address both of these issues. A modified version of the widely available adaptive cruise control systems, known as cooperative adaptive cruise control, can work at all speeds with additional wireless communication that improves stability of the controller. These structures can tolerate much smaller desired spacing and can safely work in stop and go traffic. This thesis proposes a new control structure that combines conventional cooperative adaptive cruise control with rear end collision check. This approach is capable of avoiding rear end collisions with the following car, as long as it can still maintain the safe distance with the preceding vehicle. This control structure is mainly intended for use with partially automated highways, where there is a risk of being rear-ended while following a car with adaptive cruise control. Simulation results also shows that use of bidirectional cooperative adaptive cruise control also helps to strengthen the string stability of the platoon. Two different control structures are used to accomplish this task: MPC and PD based switching controller. Model predictive control (MPC) structure works well for the purpose of bidirectional platoon control. This control structure can adapt to the changes in the plant with the use of a parameter estimator. Constraints are set to make sure that the controller outputs are always within the boundaries of the plant. Also these constraints assures that a certain gap will always be kept with the preceding vehicle. PD based switching controller offers an alternative to the MPC structure. Main advantage of this control structure is that it is designed to be robust to certain level of sensor noise. Both these control structures gave good simulation results. The thesis makes use of the control structures developed in the earlier chapters to continue developing structures to alleviate traffic congestions. Two merging schemes are proposed to find a solution to un-signaled merging and lane closures. First problem deals with situations where necessary levels of communication is not present to inform surrounding drivers of merging intention. Second structure proposes a merging protocol for cases where two platoons are approaching a lane closure. This structure makes use of the modified cooperative adaptive cruise control structures proposed earlier in the thesis

A cooperative advanced driver assistance and safety system for connected and automated vehicles

Konfliktsituationen mit mehreren Beteiligten sind für Fahrzeugführer und konventionelle Fahrerassistenz- und Sicherheitssysteme durch ihre hohe Komplexität schwer beherrschbar. So geschehen viele Unfälle auf den Straßen dieser Welt, die durch gemeinschaftlich abgestimmte Fahrmanöver verhindert oder in ihren Unfallfolgen gemindert werden könnten. Die vorliegende Arbeit adressiert dieses Potenzial und beschäftigt sich mit der Entwicklung und prototypischen Umsetzung eines fahrzeugübergreifenden kooperativen Fahrerassistenz- und Sicherheitssystems, welches mehrere Fahrzeuge über eine funkbasierte Kommunikation miteinander verbindet, sowie unfallfreie Lösungen berechnet und durchführt. In diesem Zusammenhang werden drei Forschungsfragen aufgestellt, die eine Definition von kooperativem Verhalten, eine Methode zur Koordination der anfallenden Aufgaben (Aufgabenkoordination) und eine Methode zur gemeinsamen Fahrmanöverplanung (Fahrmanöverkoordination) adressieren. Der Stand der Wissenschaft und Technik bezüglich der Forschungsfragen wird mithilfe einer systematischen Literaturstudie ermittelt, die für den Leser in einem Überblick dargestellt und hinsichtlich einer möglichen Beantwortung der Forschungsfragen ausgewertet wird. Es zeigt sich, dass die drei Forschungsfragen mit ihren Anforderungen bislang unbeantwortet sind. Zur Definition von kooperativem Verhalten werden Eigenschaften von diesem aufgezeigt, die in notwendige und hinreichende Bedingungen überführt werden. Mit der zusätzlichen Berücksichtigung von Reziprozität ergibt sich eine Definition von kooperativem Verhalten, welche durch die Steigerung des Gesamtnutzens die Unterscheidung zwischen unkooperativem Verhalten auf der einen Seite und rational-kooperativem, altruistisch-kooperativem bzw. egoistisch-kooperativem Verhalten auf der anderen Seite ermöglicht. Ein Vergleich mit den aus dem Stand der Technik bekannten Definitionen zeigt den Neuigkeitswert der entwickelten Definition. In ausgewählten Situationen wird die Definition in Simulationen angewandt.Critical situations involving multiple vehicles are rarely controlled by the associated drivers. This is one reason for the remaining number of accidents which could possibly be prevented or at least mitigated with jointly planned and conducted driving maneuvers. This potential is addressed in the dissertation at hand by developing a prototypical cooperative driver assistance and safety system coordinating multiple vehicles cooperatively using vehicle-to-vehicle-communication. In this context, three research questions reflect challenges on the road towards such a system. The research questions deal with defining a cooperative behavior, creating a method allowing to allocate coordinative tasks (task coordination), and generating a method enabling to plan joint cooperative maneuvers (maneuver coordination). Regarding the proposed research questions, a systematic literature review reveals the state-of-the-art which is first presented in an overview and afterwards used to derive open issues. The result is that the three research questions remain relevant and unanswered. In order to define cooperative behavior, properties are identified and categorized in sufficient and necessary conditions. An additional consideration of reciprocity enables the derivation of a definition of cooperative behavior which aims to increase the total utility. Cooperative behavior may further be separated into rational-cooperative, altruistic-cooperative, and egoistic-cooperative behavior. A comparison with known definitions of the state-of-the-art demonstrates the innovation of the novel definition, which is applied in chosen situations

Fahrerassistenzsysteme zur energieeffizienten Längsregelung - Analyse und Optimierung der Fahrsicherheit

Die Steigerung der Fahrsicherheit und Energieeffizienz gehören zu den wichtigsten Treibern der Fahrerassistenz. Dabei impliziert eine energieeffiziente Fahrweise häufig auch eine sichere Fahrweise. Dagegen existieren jedoch auch Fahrstrategien, die zu einer Verschlechterung der Fahrsicherheit führen können. Die vorliegende Arbeit beschäftigt sich daher mit der Fragestellung, ob sich die Sicherheit verschlechtert, wenn das vorausfahrende Fahrzeug eine energieeffiziente Fahrweise anwendet