Adaptive Filtering for Advanced Vehicle Control

Details

• Alternative Title:
  IDEA PROJECT FINAL REPORT, ADAPTIVE FILTERING FOR ADVANCED VEHICLE CONTROL
• Creators:
  Ray, Laura R.
• Corporate Creators:
  Christian Brothers University
• Corporate Contributors:
  United States. Federal Highway Administration ; ITS IDEA Program
• Subject/TRT Terms:
  • Intelligent transportation systems
  • Advanced vehicle control systems
  • Kalman filtering
  • Adaptive control
  • Automated vehicles
  • Self-driving vehicles
• Publication/ Report Number:
  EDL # 4984
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  United States. Federal Highway Administration ; ITS IDEA Program
• Abstract:
  This Innovations Deserving Exploratory Analysis (IDEA) project bridges the gap between proposed Intelligent Transportation System (ITS) decision-making methods and the proposed Advanced Vehicle Control System (AVCS) by providing numerical techniques for determining information necessary to make and implement intelligent driving decisions. The results have application to ITS products for automated driving, emergency intervention, and driver safety aids. In addition, the numerical techniques provide feedback signals that make implementation of AVCS feasible. The major components of this project include a set of transducers, an Extended Kalman Filter (EKF), a Bayesian Hypothesis Selection algorithm, and a Vehicle Parameter Determination block. This IDEA investigation is a feasibility study conducted to develop and validate the EKF and Bayesian Hypothesis Selection algorithms using both computer simulation and field test data. 41 p.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/38252/dot_38252_DS1.pdf
• File Type:
  [PDF - 841.46 KB]
• Collection(s):
  Autonomous Vehicles ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:b5d16367f8ec3bf61428a1bfd21fc278f4a9b82c29e60ba080917fbd03fd9fbe6bfceeb0fed0342596a9963ad81f932c0fef9d28a6a4054e9c92ee9fac17e84b