A-VIP: Anonymous Verification and Inference of Positions in Vehicular Networks

MiniconferenceInternational audienceKnowledge of the location of vehicles and tracking of the routes they follow are a requirement for a number of applications, including e-tolling and liability attribution in case of accidents. However, public disclosure of the identity and position of drivers jeopardizes user privacy, and securing the tracking through asymmetric cryptography may have an exceedingly high computational cost. Additionally, there is currently no way an authority can verify the correctness of the position information provided by a potentially misbehaving car. In this paper, we address all of the issues above by introducing A-VIP, a lightweight framework for privacy preserving and tracking of vehicles. A-VIP leverages anonymous position beacons from vehicles, and the cooperation of nearby cars collecting and reporting the beacons they hear. Such information allows an authority to verify the locations announced by vehicles, or to infer the actual ones if needed. We assess the effectiveness of A-VIP through both realistic simulation and testbed implementation results, analyzing also its resilience to adversarial attacks

Hybrid Fusion Approach combining Autonomous and Cooperative Detection and Ranging methods for Situation-aware Driver Assistance Systems

Current driver assistance systems such as Adaptive Cruise Control (ACC) and in particular future assistance systems such as Collision Warning make high demands on reliability of detection and ranging methods for vehicles within the local vicinity. Autonomous systems such as Radar which are already integrated into a multitude of vehicles meet these requirements to only a limited extent. As an alternative, cooperative systems for detection and ranging will be enabled by future Vehicle-2-Vehicle communication. But cooperative detection and ranging also has drawbacks regarding reliability due to positioning and transmission errors if it is applied in a standalone way. Thus, the solution presented in this paper is a hybrid approach combining autonomous and cooperative methods for detection and ranging within a common architecture. A particle filter is used for state estimation. The results are a higher detection effectiveness and a lower position error compared to using standalone autonomous or cooperative detection and ranging methods

Hybrid Fusion Approach combining Autonomous and Cooperative Detection and Ranging methods for Situation-aware Driver Assistance Systems

Current driver assistance systems such as Adaptive Cruise Control (ACC) and in particular future assistance systems such as Collision Warning make high demands on reliability of detection and ranging methods for vehicles within the local vicinity. Autonomous systems such as Radar which are already integrated into a multitude of vehicles meet these requirements to only a limited extent. As an alternative, cooperative systems for detection and ranging will be enabled by future Vehicle-2-Vehicle communication. But cooperative detection and ranging also has drawbacks regarding reliability due to positioning and transmission errors if it is applied in a standalone way. Thus, the solution presented in this paper is a hybrid approach combining autonomous and cooperative methods for detection and ranging within a common architecture. A particle filter is used for state estimation. The results are a higher detection effectiveness and a lower position error compared to using standalone autonomous or cooperative detection and ranging methods

On Interdisciplinary Development of Safety-Critical Automotive Assistance and Automation Systems

Assistenz- und Automationssysteme im Automobil zeichnen sich verstärkt durch eine große Komplexität und einen hohen Vernetzungsgrad aus. Weiterhin existiert eine Vielzahl von Anforderungen anderer Fachdisziplinen an die Funktionsentwicklung, beispielsweise im Bereich der funktionalen Sicherheit. Somit ergibt sich für Entwickler nicht nur eine gestiegene Komplexität der Systeme, sondern auch der einzuhaltenden Entwicklungsprozesse. Die vorliegende Arbeit liefert eine neue Methode, die Entwickler bei der Bewältigung dieser Komplexität unterstützt. Dabei wird ihnen problemorientiert und zielgerichtet relevantes Wissen anderer Fachdisziplinen aufbereitet und zur Verfügung gestellt. Somit können Entwurfsalternativen früher als bisher im Kontext der Gesamtentwicklung bewertet werden, was sich positiv auf Produktqualität und Entwicklungszeit auswirkt. Die Basis dieser Methode ist die offen und flexibel gestaltete Formalisierung des Entwicklungsprozesses unter Verwendung der Web Ontology Language (OWL). Darauf aufbauend werden interdisziplinäre Entwicklungsaktivitäten verknüpft und die Analysierbarkeit des formalisierten Wissens wird für automatische Schlussfolgerungen genutzt. So werden insbesondere Einflussanalysen möglich, um über die eigene Domäne hinaus Änderungen bezüglich des Gesamtentwicklungsprozesses zu bewerten. Im Rahmen dieser Arbeit wurde eine prototypische Werkzeugkette implementiert, die die beschriebene Methode umsetzt und deren technische Realisierbarkeit demonstriert. Als Anwendungsbeispiel dient die angedeutete Weiterentwicklung eines radarbasierten Abstandsregeltempomaten zu einem Notbremssystem. Dabei wird insbesondere der Einfluss der funktionalen Sicherheit auf die Funktionsentwicklung beleuchtet, indem aus einem formalisierten Wissensmodell des Standards ISO 26262 notwendige Anforderungen und Methoden für den Gesamtentwicklungsprozess abgeleitet werden.Automotive assistance and automation systems increasingly present high levels of complexity and connectivity. In addition, more and more specific requirements in disciplines like functional safety have to be considered during functional development. Thus, developers have to cope with increasing levels of product complexity, but also complexity of the development process. This thesis presents a new method which supports developers in handling these dimensions of complexity. Therefore relevant knowledge of other disciplines is presented to them in a solution-oriented way. Thus, design alternatives can be assessed much earlier in the overall development process which has a positive impact on product quality and development cycles. The method’s base is an open and flexible formalization of the development process using the Web Ontology Language (OWL). OWL is used to link different interdisciplinary development activities whereas the analyzability of formalized knowledge enables automated reasoning. This especially introduces an impact analysis to assess major cross-cutting changes to the product in the context of the overall development process. For this thesis a prototype toolchain has been developed which implements the described method and demonstrates its technical feasibility. The extension of a radar-based adaptive cruise control system towards an emergency braking system is sketched as an example for the prototype toolchain. In this example, the impact of functional safety on the functional development is focused, involving a formalized model of requirements and methods from ISO 26262