The SALI project aimed at investigating how challenging runtime factors such as unpredictability, faults and limited resources affect and could be managed in self-driving vehicles (SDVs). In order to achieve that, a series of experiments have
Author(s)
Edith Zavala, Christian Berger, Xavier Franch, Jordi Marco
Smart self-driving vehicle The project goal: SALI aims at providing an open software engineering solution to integrate self-*capabilities, e.g. self-healing and self-optimization, to self-driving vehicles in order to deal with runtime factors such as unpredictability, faults
A pilot project with three substudies (a literature survey, a workshop, and a field experiment at test track) is reported. The intent is to develop realistic and prototypical driving scenarios with associated patient-care tasks, for use
Akutvård under ambulansfärd: Naturalistiska data från simulerade typsituationer vid körning på testbana? Målen för detta projekt var att undersöka det aktuella kunskapsläget om akutsjukvård under ambulansfärd samt att samla in naturalistiska fordonsdynamiska data samt beteendedata vid
Since the rapid ourish of automobiles in the 21st century, the need for easier and faster transportation by means of automobiles has risen. In recent years, driving has ranged from being a daily routine task to
How drivers respond if steering automation fails? We studied how drivers respond when steering automation fails. Especially, we were interested in where drivers look when they need to detect a steering automation failure and prepare for
The topic of this paper is the bigger picture of vehicle dynamics and handling characteristics of cars, with a focus on driving safety. More specifically, the directional stability gain obtained using the semi-active differential (DSLD) is
Connected to the road with the Direction Sensitive Locking Differential (DSLD). The topic of this project is the bigger picture of vehicle dynamics and handling characteristics of cars and more specifically about highlighting a hidden potential
