9,814 research outputs found
Decision-Making for Automated Vehicles Using a Hierarchical Behavior-Based Arbitration Scheme
Behavior planning and decision-making are some of the biggest challenges for
highly automated systems. A fully automated vehicle (AV) is confronted with
numerous tactical and strategical choices. Most state-of-the-art AV platforms
implement tactical and strategical behavior generation using finite state
machines. However, these usually result in poor explainability, maintainability
and scalability. Research in robotics has raised many architectures to mitigate
these problems, most interestingly behavior-based systems and hybrid
derivatives. Inspired by these approaches, we propose a hierarchical
behavior-based architecture for tactical and strategical behavior generation in
automated driving. It is a generalizing and scalable decision-making framework,
utilizing modular behavior blocks to compose more complex behaviors in a
bottom-up approach. The system is capable of combining a variety of scenario-
and methodology-specific solutions, like POMDPs, RRT* or learning-based
behavior, into one understandable and traceable architecture. We extend the
hierarchical behavior-based arbitration concept to address scenarios where
multiple behavior options are applicable but have no clear priority against
each other. Then, we formulate the behavior generation stack for automated
driving in urban and highway environments, incorporating parking and emergency
behaviors as well. Finally, we illustrate our design in an explanatory
evaluation
From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation
Context: Competitions for self-driving cars facilitated the development and
research in the domain of autonomous vehicles towards potential solutions for
the future mobility.
Objective: Miniature vehicles can bridge the gap between simulation-based
evaluations of algorithms relying on simplified models, and those
time-consuming vehicle tests on real-scale proving grounds.
Method: This article combines findings from a systematic literature review,
an in-depth analysis of results and technical concepts from contestants in a
competition for self-driving miniature cars, and experiences of participating
in the 2013 competition for self-driving cars.
Results: A simulation-based development platform for real-scale vehicles has
been adapted to support the development of a self-driving miniature car.
Furthermore, a standardized platform was designed and realized to enable
research and experiments in the context of future mobility solutions.
Conclusion: A clear separation between algorithm conceptualization and
validation in a model-based simulation environment enabled efficient and
riskless experiments and validation. The design of a reusable, low-cost, and
energy-efficient hardware architecture utilizing a standardized
software/hardware interface enables experiments, which would otherwise require
resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table
Validation of trajectory planning strategies for automated driving under cooperative, urban, and interurban scenarios.
149 p.En esta Tesis se estudia, diseña e implementa una arquitectura de control para vehículos automatizados de forma dual, que permite realizar pruebas en simulación y en vehículos reales con los mínimos cambios posibles. La arquitectura descansa sobre seis módulos: adquisición de información de sensores, percepción del entorno, comunicaciones e interacción con otros agentes, decisión de maniobras, control y actuación, además de la generación de mapas en el módulo de decisión, que utiliza puntos simples para la descripción de las estructuras de la ruta (rotondas, intersecciones, tramos rectos y cambios de carril)Tecnali
iTETRIS: An Integrated Wireless and Traffic Platform for Real-Time Road Traffic Management Solutions
Wireless vehicular cooperative systems have been identified as an attractive solution to improve road traffic management, thereby contributing to the European goal of safer, cleaner, and more efficient and sustainable traffic solutions. V2V-V2I communication technologies can improve traffic management through real-time exchange of data among vehicles and with road infrastructure. It is also of great importance to investigate the adequate combination of V2V and V2I technologies to ensure the continuous and costefficient operation of traffic management solutions based on wireless vehicular cooperative solutions. However, to adequately design and optimize these communication protocols and analyze the potential of wireless vehicular cooperative systems to improve road traffic management, adequate testbeds and field operational tests need to be conducted.
Despite the potential of Field Operational Tests to get the first insights into the benefits and problems faced in the development of wireless vehicular cooperative systems, there is yet the need to evaluate in the long term and large dimension the true potential benefits of wireless vehicular cooperative systems to improve traffic efficiency. To this aim, iTETRIS is devoted to the development of advanced tools coupling traffic and wireless communication simulators
A Modular Approach for a Family of Ground Mobile Robots
This paper deals with Epi.q, a family of mobile robots whose main characteristic is a wheel-legged hybrid locomotion. These multi-purpose robots can be successfully exploited for security and surveillance tasks. The document presents state of the art security robotics, the Epi.q mechanical architecture, the concept behind the robot driving unit, three prototypes and the design of a new on
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