Thomas Michalke

The narrow road assistant - Next generation advanced driver assistance in inner-city

With the availability of novel sensor technologies, as e.g. stereo vision, advanced driver assistance systems (ADAS) for highly complex urban scenarios get increasingly into focus. In this contribution, with the “narrow road assistant” an inner-city ADAS is presented that supports the driver in safely passing narrow road passages based on offering early scenario-specific information and automated steering support. The focus of the contribution will be on system design aspects and first concepts for scene analysis that aim at recognizing and considering the driver intention. The named ADAS is realized in the context of the publicly-funded project UR:BAN, which started in 2012.

Environment perception for inner-city driver assistance and highly-automated driving

While driver assistance systems mainly targeted highway or parking scenarios in the past, systems assisting in inner-city traffic increasingly get into focus today. Since driving in urban areas is characterized by a larger variety of situations that have to be covered, finding an adequate representation of the vehicle surrounding is a challenging task for the perception of these systems. In this paper we present our perception system that has been specifically designed for the demands of inner-city driving. It first features a plugin-based architecture by which multiple sensor setups as well as different driver assistance functions can be supported. Second, it is characterized by a hybrid modeling approach that combines the well known model-based object tracking technique with model-free representations in terms of grids. We will present details on a specific implementation of the system using a 3D lidar sensor. Finally, it is shown how the system is used in the Narrow Road Assistant - a next-generation driver assistance system supporting the driver in safely passing narrow road passages in inner-city.

The narrow road assistant - evolution towards highly automated driving in inner city

With the “narrow road assistant” (NRA), this contribution elaborates on an inner-city ADAS that supports the driver in safely passing narrow road passages. The system offers early scenario-specific information together with automated support in steering and braking. The solved challenges and gathered experiences will ease and accelerate the development of future functions for piloted inner-city driving. In this sense, the function is an important evolutionary step towards highly automated driving in urban areas. The ADAS was realized in the context of the publicly-funded project UR:BAN, which started in 2012. In October 2015 the project UR:BAN reached its peak in a public presentation in Düsseldorf Germany. Numerous driving demonstrations allowed guests an independent evaluation on a larger scale. The Bosch NRA performed in all situations reliably surpassing the expectations of many guests. The focus of the contribution will be on the detailed description of the system and its evaluation.

Evolution in Advanced Driver Assistance: From Steering Support in Highway Construction Zones to Assistance in Urban Narrow Road Scenarios

With the advances in environment sensor technology, advanced driver assistance systems (ADAS) that target increasingly complex scenarios such as inner-city traffic get into focus. Such novel ADAS will offer assistance in a wide range of urban traffic scenarios and, thus, will further decrease the number and severity of accidents. In this contribution, the evolution of an ADAS for lateral guidance in highway construction zones (i.e. the “construction zone assistant”) towards assistance in narrow urban road scenarios (i.e. the “urban narrow road assistant”) is presented. The focus of the contribution will be on the challenges of these two scenario types and their respective requirements on the system concept and design. While steering support in highway construction zones will be available on the market soon, its functional extension to inner-city traffic is still characterized by numerous technological challenges. Due to that, the emphasis in terms of algorithmic details will be on the “urban narrow road assistant”.