|Partner:||BMW Group Forschung und Technik|
|Ansprechpartner am Lehrstuhl:||Markus Straßberger|
The CAREDRIVE project aims to develop and evaluate generic strategies to realize dedicated and context-aware driver information, in order to reduce the number of accidents caused by human errors in complex road situations. Thereby, CAREDRIVE comprises several problem domains, ranging from the deduction of relevant context information and spatio-temporal situation inference to efficient context dissemination strategies in vehicular ad hoc networks and personalisation issues.
In many European countries, the Vision Zero has been issued as motto for traffic policy in the future. Vision Zero describes a traffic system, where eventually no one will be killed or seriously injured within the road transport system, meaning on the one hand that in future road infrastructure must adhere to improved safety standards. On the other hand, new driver assistance systems will play an increasingly important role to significantly reduce the number of accidents.
Today, nearly all vehicles are already equipped with sophisticated on-board sensors to detect critical driving conditions. However, corresponding systems only cover the vehicle’s current position. In other words, they are only reactive as they are not able to foresee any critical situations, which the vehicle may potentially encounter in future.
During the last decade, car manufactures and suppliers therefore put a lot of effort into developing predictive and proactive driver assistance systems such as ACC (adaptive cruise control), mainly based on near range sensing technologies such as radar, lidar, and ultra-sonic or optical image processing. Some of these systems are already available and perform very well. Unfortunately, these systems are typically quite expensive and available for upper-class vehicles only.
In addition, with the availability of new radio technologies, a new class of applications to increase safety in road traffic has emerged from research and development: vehicles communicate with each other in order to widen the driver’s horizon of perception, i.e. supporting the driver with important information to support the task of driving in complex and error-prone situations. Thus, inter-vehicle communication is widely considered as a promising complementary technology to support foresighted driving and accident avoidance. It is therefore one key issue of the vision of an accident-free traffic.
In this paradigm, the CAREDRIVE project (Context Aware Distributed Road-traffic Information System for Vehicular Environments) aims to develop and evaluate generic strategies to realize dedicated and context-aware driver information. Thereby, CAREDRIVE comprises several problem domains, ranging from the deduction of relevant context information and spatio-temporal situation inference to efficient context dissemination strategies in vehicular ad hoc networks and personalisation issues. The objective is to develop a robust and reliable framework for a variety of information and assistance applications, as for example collision avoidance, electronic emergency breaks, local danger warning, intersection assistance, real-time traffic information and dynamic navigation.