%0 Book Section
%T Data for Training Models, Domain Adaptation
%A Antonio Lopez
%A David Vazquez
%A Gabriel Villalonga
%B Intelligent Vehicles.  Enabling Technologies and Future Developments
%D 2018
%F Antonio Lopez2018
%O ADAS; 600.118
%O exported from refbase (http://158.109.8.37/show.php?record=3047), last updated on Wed, 20 Jan 2021 11:48:38 +0100
%X Simulation can enable several developments in the field of intelligent vehicles. This chapter is divided into three main subsections. The first one deals with driving simulators. The continuous improvement of hardware performance is a well-known fact that is allowing the development of more complex driving simulators. The immersion in the simulation scene is increased by high fidelity feedback to the driver. In the second subsection, traffic simulation is explained as well as how it can be used for intelligent transport systems. Finally, it is rather clear that sensor-based perception and action must be based on data-driven algorithms. Simulation could provide data to train and test algorithms that are afterwards implemented in vehicles. These tools are explained in the third subsection.
%K Driving simulator
%K hardware
%K software
%K interface
%K traffic simulation
%K macroscopic simulation
%K microscopic simulation
%K virtual data
%K training data
%U https://doi.org/10.1016/B978-0-12-812800-8.00010-2
%P 395–436