Browsing by Author "de la Escalera, Arturo"
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Item Environmental perception for intelligent vehicles(Elsevier, 2017-01-01) Armingol, José M.; Alfonso, Jorge; Aliane, Nourdine; Clavijo, Miguel; Campos-Cordobés, Sergio; de la Escalera, Arturo; del Ser, Javier; Fernández, Javier; García, Fernando; Jiménez, Felipe; López, Antonio M.; Mata, Mario; Martín, David; Menéndez, José M.; Sánchez-Cubillo, Javier; Vázquez, David; Villalonga, Gabriel; LABORATORIO DE TRANSFORMACIÓN URBANA; SMART_TRANSPORT; Tecnalia Research & InnovationEnvironmental perception represents, because of its complexity, a challenge for Intelligent Transport Systems due to the great variety of situations and different elements that can happen in road environments and that must be faced by these systems. In connection with this, so far there are a variety of solutions as regards sensors and methods, so the results of precision, complexity, cost, or computational load obtained by these works are different. In this chapter some systems based on computer vision and laser techniques are presented. Fusion methods are also introduced in order to provide advanced and reliable perception systems.Item Positioning and digital maps(Elsevier, 2017-01-01) Toledo-Moreo, Rafael; Armingol, José M.; Clavijo, Miguel; de la Escalera, Arturo; del Ser, Javier; Jiménez, Felipe; Musleh, Basam; Naranjo, José E.; Olabarrieta, Ignacio Iñaki; Sánchez-Cubillo, Javier; IA; Tecnalia Research & InnovationA reliable positioning system is essential for the development of intelligent vehicles. This chapter provides an overview of different technologies and techniques that are crucial to understand modern positioning systems onboard road vehicles. It is written for the purpose of serving as a guide to students, engineers, and researchers in the field of vehicular technology or Intelligent Transportation Systems. In Section 4.1, after an introduction to the problem, a handy list of key definitions is provided, and some of the most relevant Location-Based Services mentioned. Section 4.2 presents the fundamentals of GNSS-based positioning. Aiding technologies, such as odometers and inertial sensors, and techniques for GNSS-based hybridized positioning are discussed in Section 4.3. Later, Section 4.4 analyzes the role of digital maps, map-matching, and map-aided positioning. Finally, Section 4.5 introduces alternatives to GNSS, such as visual odometry, with a brief mention of wireless networks and RFID.