Real-Time Road-Slope Estimation Based on Integration of Onboard Sensors With GPS Using an IMMPDA Filter

This paper proposes a road-slope estimation algorithm to improve the performance and efficiency of intelligent vehicles. The algorithm integrates three types of road-slope measurements from a GPS receiver, automotive onboard sensors, and a longitudinal vehicle model. The measurement integration is achieved through a probabilistic data association filter (PDAF) that combines multiple measurements into a single measurement update by assigning statistical probability to each measurement and by removing faulty measurement via the false-alarm function of the PDAF. In addition to the PDAF, an interacting multiple-model filter (IMMF) approach is applied to the slope estimation algorithm to allow adaptation to various slope conditions. The model set of the IMMF is composed of a constant-slope road model (CSRM) and a constant-rate slope road model (CRSRM). The CSRM assumes that the slope of the road is always constant, and the CRSRM assumes that the slope of the road changes at a constant rate. The IMMF adapts the road-slope model to the driving conditions. The developed algorithm is verified and evaluated through experimental and case studies using a real-time embedded system. The results show that the performance and efficiency of the road-slope estimation algorithm is accurate and reliable enough for intelligent vehicle applications.

• Record URL:
  • https://doi.org/10.1109/TITS.2013.2266438
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Jo, Kichun
  • Kim, Junsoo
  • Sunwoo, Myoungho
• Publication Date: 2013-12

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 1718-1732
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 14
  • 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: Advanced vehicle control systems; Algorithms; Data fusion; Highway grades; Statistical distributions
• Subject Areas: Data and Information Technology; Highways; I71: Traffic Theory; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01527813
• Record Type: Publication
• Files: TLIB, TRIS
• Created Date: Jun 5 2014 9:08AM