Toward Perception-Driven Urban Environment Modeling for Automated Road Vehicles

Automated driving is a widely discussed topic nowadays. Impressive demonstrations have shown the potentials of vehicle automation. However, many projects in the context of automated driving use a priori data in order to compensate insufficiencies in perceiving and understanding the vehicle's environment. Additionally, in terms of functional safety and redundancy, it is not yet known whether such localization- and map-based approaches are really path breaking. This is the reason why the authors focus on on-board perception also of the stationary urban environment. While object tracking is a commonly used approach, the combination of grid-based and object-based representations for environment perception is still a research topic. The sufficient perception of lanes and drivable areas is an unsolved issue in urban environment. Several perception modules have to collaborate for a suitable representation of the vehicles' surroundings. In this paper, the authors present the latest contributions of the project Stadtpilot to a perception-driven modeling of urban environments. The authors propose a lane detection approach which is based on a grid-based representation of different environmental features. Their approach is able to detect multi-lane structures and it is capable to deal with complex lane structures which are typical of urban roads. The extracted features are stabilized by a tracking module. Additionally, the authors incorporate a free-space representation which data are not derived implicitly from detected targets, but based on an explicit ground representation. Extensions of the authors' dynamic classification module focus on the start/stop behavior of other road users in order to enhance the completeness of track list (mobile objects) and grid (stationary environment). The presented algorithms run in real-time on a standard PC and are evaluated with real sensor data.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 731-738
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01601910
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:24PM