Advanced Driver Assistance Systems

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高级驾驶辅助系统(ADAS)帮助驾驶员以便捷且安全的方式操作车辆。当前系统主要侧重于警告功能，但市场上已有一些系统能够启动规避动作。研究趋势表明，远程操控乃至自动驾驶已不再是遥不可及的梦想。这些趋势为现有系统集成及未来开发带来了新的挑战。

Advanced Driver Assistance Systems

from: http://www.rcs.ei.tum.de/en/research/driver-assistance/

Advanced Driver Assistance Systems (ADAS) are helping drivers to operate vehicles in a conveniant and safe way. While current systems mostly focus on a warning, some systems in the market are already initiating evasive actions. In research, tele-operated or even autonomous driving is no longer visionary.

This trends lead to new challeges in the integration with existing systems and for future developments, e.g.:

Integration of a growing numer of ADAS funcionalities per vehicle
Sensors are driving several applications with heterogeneous requirements
Sensor information gets shared among vehicles
Applications evolve from reactive systems to predictive and cognitive systems.
Highly specialized applications for adverse environmental conditions
Electric Vehicles have to cope with limited energy buffers

Many of our research areas are also highly relevant for the specific requirements in the ADAS domain, e.g.

Computer Vision for ADAS

Furthermore on an application level, we focus on vision-based ADAS. So far, many ADAS incorporating cameras heavily rely on a data fusion with other sensor information gathered by mostly active (= emmiting) sensory like radar and lidar. The latter are a major cost factor. Improving vision systems helps reducing overall vehicle costs. Human drivers mostly rely on the visual channel while operating a vehicle - improvements in image understanding are expected to lead to a sigificant better performace of ADAS.

Outdoor camera systems have to cope with a highly unstructured and changing environent (e.g. variety of objects and traffic infrastructure, intrinsic ambiguities, whether, daytime), which limits the range of application. While whether and daytime changes, the specific requirements for vision tasks change as well. One of our challenges is to manage and utilize sunligth effects and direct cast vehicle shadows for automotive vision systems.

Contact person:

Florian Rattei