Elena Cardarelli

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— This paper presents the preliminary results of VIAC, the VisLab Intercontinental Autonomous Challenge, a test of autonomous driving along an unknown route from Italy to China. It took 3 months to run the entire test; all data have been logged, including all data generated by the sensors, vehicle data, and GPS info. This huge amount of information has been(More)
— Future requirements for drastic reduction of CO2 production and energy consumption will lead to significant changes in the way we see mobility in the years to come. However, the automotive industry has identified significant barriers to the adoption of electric vehicles, including reduced driving range and greatly increased refueling times. Automated cars(More)
— This paper describes a method for classifying road signs based on a single color camera mounted on a moving vehicle. The main focus will be on the final neural network based classification stage of the candidates provided by an existing traffic sign detection algorithm. Great attention is paid to image preprocessing in order to provide a more simple and(More)
—Vision-based perception has been explored as low-cost, flexible technology for industrial applications such as factory automation and ADAS in the automotive market. The inherent flexibility of these systems presents a challenge quantifying performance and often even quantifying increases or decreases in system performance as conditions change. Experience(More)
— This paper presents the control system of an autonomous vehicle capable of perceiving and describing the environment using different inputs, such as GPS waypoints, roadways borders and lines, leader vehicles, and obstacles to be avoided. The controller has been implemented and tested for the VisLab Intercontinental Autonomous Challenge, a long(More)
— Autonomous Ground Vehicles designed for extreme environments (e.g mining, constructions, defense, exploration applications) require a reliable estimation of terrain traversability, in terms of both terrain slope and obstacles presence. In this paper we present a new technique to build, in real time and only from a 3D points cloud, a dense terrain(More)
Road Sign Detection is a major goal of the Advanced Driving Assistance Systems. Most published work on this problem share the same approach by which signs are first detected and then classified in video sequences , even if different techniques are used. While detection is usually performed using classical computer vision techniques based on color and/or(More)
— Color has proved to be an important feature to be exploited for road signs detection on images; however, not all road signs have distinctive color characteristics. This paper presents a shape-based approach for Italian de-restriction signs detection; the developed algorithm uses a black band extractor to highlight regions of interest, where a circle shape(More)
This paper presents a method for triangular and rectangular shapes detection in a road sign recognition system based on a three step algorithm: color segmentation, shape detection and neural network classification. The shape detector is based on the evaluation of the Sobel edges and Hough images in a region of interest detected by the color-based stage.(More)
All journeys have secret destinations of which the traveler is unaware. won a five-year Advanced Investiga-tors' Grant from the European Research Council for his laboratory project proposal " Open Intelligent Systems for Future Autonomous Vehicles. " The project's main goal was to design a perception layer to be implemented in vehicles so that each sensor(More)