A New Vehicle Motion Model for Improved Predictions and Situation Assessment

Reliable and accurate vehicle motion models are of vital importance for automotive active safety systems for a number of reasons. First of all, these models are necessary in tracking algorithms that provide the safety system with information. Second, the motion model is often used by the safety application to make long-term predictions about the future traffic situation. These predictions are then part of the basic data used by the system to determine if, when, and how to intervene. In this paper, we suggest a framework for designing accurate vehicle motion models. The resulting models differ from conventional models in that the expected control input from the driver is included. By also providing a methodology for a formal treatment of the uncertainties, a model structure well suited, e.g., in a tracking algorithm, is obtained. To utilize the framework in an application will require careful design and validation of submodels to calculate the expected driver control input. We illustrate the potential of the framework by examining the performance for a specific model example using real measurements. The properties are compared with those of a constant acceleration model. Evaluations indicate that the proposed model yields better predictions and that it has an ability to estimate the prediction uncertainties.

• Record URL:
  • https://doi.org/10.1109/TITS.2011.2160342
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Sorstedt, Joakim
  • Svensson, Lennart
  • Sandblom, Fredrik
  • Hammarstrand, Lars
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: pp 1209-1219
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 12
  • Issue Number: 4
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Acceleration (Mechanics); Active safety systems; Drivers; Mathematical models; Mathematical prediction; Motion
• Subject Areas: Data and Information Technology; Highways; I71: Traffic Theory;

Filing Info

• Accession Number: 01361273
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: TLIB
• Created Date: Jan 25 2012 2:23PM