Andrea Saroldi

TL;DR: In this article, a method for avoiding collision between a motor vehicle and obstacles placed in the path of the vehicle comprises the stages of forming a radar map of the area in front of a vehicle, reconstructing the geometry of the road, identifying its edges, detecting the position and speed of vehicle with respect to the road and determining the vehicle's presumed path on the basis of road geometry and the manoeuvre being carried out by the vehicle at that instant.

TL;DR: A novel driver-support system that helps to maintain the correct speed and headway (distance) with respect to lane curvature and other vehicles ahead and has been shown to cause prompt reactions and significant speed correction before getting into really dangerous situations.

TL;DR: This position paper identifies a range of application fields of the co-driver technology, showing how it constitutes a universal enabling technology for both smart vehicles and cooperative systems, and naturally sets out a program for future research.

TL;DR: In this paper, an experimental investigation of human control of vehicles carried out on the basis of general theories on human movement is presented, and their relations with theories of motor optimality principles, such as minimum jerk, minimum variance, and the two-thirds power law are highlighted.

TL;DR: A “warning manager” has been developed, acting like a referee who lets the ADAS applications work standalone and then combines the requests of each application, prioritizes them, and manages the interaction with the user.