Automating the Process of Traffic Orientation Through Mobile Devices and Ontologies

Mobile devices are used in all activities undertaken by users and 90% of them have used at least once a mobile device to search for local information navigation and acted on the basis of data. In this material is presented the use of mobile applications for traffic navigation or assistance and how they can contribute to the automation of orientation in traffic through traffic signs. Traffic signs around the globe are very different, even if some countries ratified conventions or adopted common specifications. In addition to that, a part of traffic signs differ from country to country even if they have the same road signal convention. This paper work aims to establish a global knowledge base with traffic signs and traffic rules dictated by them. In this way when a driver travels in foreign countries by car he can be helped by the mobile device in order to recognize the traffic signs. The ontology design is made by using Protégé software together with an RDF/RDFS approach. It uses a class hierarchy with classes like RoadSign and TrafficRule in the top of it. SPAQRL is the query language used to clean the knowledge base. At the beginning it will be populated with traffic signs from Romania. Ontology will be the backend of the mobile application that provides recognition of traffic signs and assists drivers from around the world in traffic navigation. In order to motivate the users to be active in the community and add new signs in the application a gamification approach is used

Path planning and map monitoring for self-driving vehicles based on HD maps

Este trabajo ha sido realizado dentro del contexto del proyecto Techs4AgeCar en el grupo de investigación Robesafe, cuyo objetivo es el desarrollo de un vehículo de conducción autónoma. Forma parte de dos líneas distintas del proyecto, la de mapeado y la de planificación, ya que ambas están directamente relacionadas. Se ha desarrollado un planificador de rutas global basado en mapas de alta defición (HD Maps) offline previamente generados. Por otro lado, también se ha cubierto toda la parte de generación de mapas que posteriormente son utilizados por el planificador. Además, se ha desarrollado un módulo capaz de aprovechar la información proporcionado por el mapa, de forma que se monitorizan los elementos relevantes y cercanos al coche que afectan a la ruta, como son carriles, intersecciones y elementos regulatoriosThis work has been done within the context of the Techs4AgeCar project in the Robesafe research group, whose project focuses on the development of an autonomous driving vehicle. This work is part of two different layers of the project, mapping and planning layers, since both are directly related. A global route planner has been developed based on previously generated offline HD Maps. Therefore, the entire part of generating maps that are later used by the planner has also been covered. In addition, a module capable of taking advantage of the information provided by the map has been developed, so that the relevant elements close to the vehicle that affect the route such as lanes, intersections and regulatory elements are monitored.Máster Universitario en Ingeniería Industrial (M 141

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Sensor Integration in a Low Cost Land Mobile Mapping System

Mobile mapping is a multidisciplinary technique which requires several dedicated equipment, calibration procedures that must be as rigorous as possible, time synchronization of all acquired data and software for data processing and extraction of additional information. To decrease the cost and complexity of Mobile Mapping Systems (MMS), the use of less expensive sensors and the simplification of procedures for calibration and data acquisition are mandatory features. This article refers to the use of MMS technology, focusing on the main aspects that need to be addressed to guarantee proper data acquisition and describing the way those aspects were handled in a terrestrial MMS developed at the University of Porto. In this case the main aim was to implement a low cost system while maintaining good quality standards of the acquired georeferenced information. The results discussed here show that this goal has been achieved

A Systematic Review of Urban Navigation Systems for Visually Impaired People

Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In~addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches. Our aim in this article is to present a comprehensive review of research directly in, or relevant to, assistive outdoor navigation for BVIP. We breakdown the navigation area into a series of navigation phases and tasks. We then use this structure for our systematic review of research, analysing articles, methods, datasets and current limitations by task. We also provide an overview of commercial and non-commercial navigation applications targeted at BVIP. Our review contributes to the body of knowledge by providing a comprehensive, structured analysis of work in the domain, including the state of the art, and guidance on future directions. It will support both researchers and other stakeholders in the domain to establish an informed view of research progress

Conditional Affordance Learning for Driving in Urban Environments

Most existing approaches to autonomous driving fall into one of two categories: modular pipelines, that build an extensive model of the environment, and imitation learning approaches, that map images directly to control outputs. A recently proposed third paradigm, direct perception, aims to combine the advantages of both by using a neural network to learn appropriate low-dimensional intermediate representations. However, existing direct perception approaches are restricted to simple highway situations, lacking the ability to navigate intersections, stop at traffic lights or respect speed limits. In this work, we propose a direct perception approach which maps video input to intermediate representations suitable for autonomous navigation in complex urban environments given high-level directional inputs. Compared to state-of-the-art reinforcement and conditional imitation learning approaches, we achieve an improvement of up to 68 % in goal-directed navigation on the challenging CARLA simulation benchmark. In addition, our approach is the first to handle traffic lights and speed signs by using image-level labels only, as well as smooth car-following, resulting in a significant reduction of traffic accidents in simulation.Comment: Accepted for Conference on Robot Learning (CoRL) 201

Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.Uno de los principales problemas de la interacción de los robots autónomos es el conocimiento de la escena. El reconocimiento es fundamental para solventar este problema y permitir a los robots interactuar en un escenario no controlado. En este documento, presentamos una aplicación práctica de captura del objeto, normalización y clasificación de señales triangulares y circulares. El sistema es introducido en el robot Aibo de Sony para mejorar el comportamiento de la interacción del robot. La metodología presentada ha sido testeada en simulaciones y problemas de categorización reales, como es la clasificación de señales de tráfico, con resultados muy prometedores.One of the main problems of autonomous robots interaction is the scene knowledge. Recognition is concerned to deal with this problem and to allow robots to interact in uncontrolled environments. In this paper, we present a practical application for object fitting, normalization and classification of triangular and circular signs. The system is introduced in the Aibo robot of Sony to increase the robot interaction behaviour. The presented methodology has been tested in real simulations and categorization problems, as the traffic signs classification, with very promising results.Nota: Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia