Ignacio Parra Alonso

TL;DR: A components-based learning approach is proposed in order to better deal with pedestrian variability, illumination conditions, partial occlusions, and rotations and suggest a combination of feature extraction methods as an essential clue for enhanced detection performance.

TL;DR: The use of automatic steering as a promising solution to avoid accidents in the future is suggested, and the viability of the proposed collision avoidance system for autonomous vehicles is proved.

TL;DR: A method to predict future pedestrian paths, poses, and intentions up to 1 s in advance based on balanced Gaussian process dynamical models (B-GPDMs), which reduce the 3-D time-related information extracted from key points or joints placed along pedestrian bodies into low-dimensional spaces.

TL;DR: The main conclusion is that cooperative autonomous driving is feasible among very different implementations of the communication protocols and using completely different autonomous vehicles.

TL;DR: The definition of a new concept of AT is proposed within the context of the ITS, Assistive Intelligent Transportation System (AITS), analyzing its intrinsic requirements and providing a set of examples, and a specific procedure to guarantee anonymity while identifying the type of disability.