Intelligent Sensor Validation and Sensor Fusion for Reliability and Safety Enhancement in Vehicle Control

In this report the authors present an evaluation of methods for validation and fusion of sensor readings obtained from multiple sensors, to be used in tracking automated vehicles and avoidance of obstacle in its path. The validation and fusion is performed in two modules which are part of a larger five-module hierarchical supervisory control architecture. This supervisory control architecture operates at two levels of the Automated Vehicle Control Systems (AVCS): the regulation and the coordination level. Supervisory control activities at the regulation layer deal with validation and fusion of the sensor data, as well as fault diagnosis of the actuators, sensors, and the vehicle itself. Supervisory control activities at the coordination layer deal with detecting potential hazards, recommending the feasibility of potential maneuvers and making recommendations to avert accidents in emergency situations. The authors formulated the need for an hierarchical approach and then focused in depth on the two modules: sensor validation and sensor fusion. Tracking models were introduced for the various operating states of the automated vehicle, namely vehicle following, maneuvering, i.e. split, merge, lane change, emergencies, and for the lead vehicle in a platoon. The Probabilistic Data Association Filter (based on Kalman filtering) is proposed for the formation of real time validation gates and for fusing the validated readings. A topology for an influence diagram which captures the interaction of the various vehicle components and the sensing equipment, as well as the algorithmic sensor validation algorithms were developed. Furthermore, experiments for characterization of the optical triangulation longitudinal sensor were carried out. The other two longitudinal sensors, namely the radar and the sonar sensor, were tested as well. These tests were conducted under both dynamic and static test conditions as well as under vibrations

• Record URL:
  https://escholarship.org/uc/item/5bc922tn
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/10551425
• Corporate Authors:

  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
  Richmond Field Station, 1357 South 46th Street
  Richmond, CA  United States  94804-4648

  University of California, Berkeley

  Department of Mechanical Engineering
  Berkeley, CA  United States  94720-1740

  California Department of Transportation

  Office of Research, P.O. Box 942873
  Sacramento, CA  United States  94273-0001
• Authors:
  • Agogino, Alice
  • Goebel, Kai
  • Alag, Satnam
• Publication Date: 1995-6-30

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final report
• Features: Appendices; Figures; References;
• Pagination: 55p
• Serial:
  • PATH Research Report
  • Publisher: University of California, Berkeley
  • ISSN: 1055-1425

Subject/Index Terms

• TRT Terms: Advanced vehicle control systems; Data fusion; Kalman filtering; Validation
• Subject Areas: Data and Information Technology; Highways; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01567251
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Report/Paper Numbers: UCB-ITS-PRR-95-40
• Files: CALTRANS, TRIS, ATRI, STATEDOT
• Created Date: Jun 26 2015 1:37PM