Learn More
This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that successfully entered the finals of the 2007 DARPA Urban Challenge competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algorithms.(More)
Cognitive automobiles consist of a set of algorithms that cover a wide range of processing levels: from low-level image acquisition and feature extraction up to situation assessment and decision making. The modules implementing them are naturally characterized by decreasing data rates at higher levels, because raw data is discarded after evaluation, and(More)
This paper presents the design of the cognitive automobile in Munich. The focus of the capabilities shown here is the navigation on highways and rural roads. The emphasis on higher speed requires early detection of far field objects, so a multi focal active vision with gaze control is essential. For increased robustness lidar range sensors are combined with(More)
This paper describes the hardware and software framework of AnnieWAY, an autonomous vehicle successfully competing at all qualification stages up to the finals of the <i>DARPA</i> <i>Urban</i> <i>Challenge</i> <i>2007</i> competition. Besides the hardware premises for by-wire steering, braking, throttle control and sensors, two frameworks for high-level(More)
Intelligent vehicles comprise a large set of cognitive functions that form their intelligence. For the realization of every function, several software modules are needed, which exhibit a number of interdependencies. Because software is often contributed by different groups of developers, the collaboration requires manageable interfaces and makes the(More)