Real-time Sensor Validation                               image of Cooperative Systems Section logo

image of Direct sunlight causing a minor failure in an optoelectric sensor

Direct sunlight causes a minor failure in an optoelectric sensor. Current systems do not respond to this degradation.

Overview

Sensing systems have a variety of failure modes, many of which can’t be easily detected. These failures can cause safety-critical events, such as missed obstacles or unnecessary emergency braking. Many systems operate using a “good faith” approach, accepting sensor data at face value. However, to achieve a commercially acceptable level of robustness, a substantially more intelligent approach to data analysis is necessary.

Approach

Nominal and degraded operational data is collected for the sensing system to be analyzed. Using a combination of machine learning techniques, this data is analyzed to create an accurate, efficient, description of healthy operation. This description is then used for real-time, on-vehicle analysis to determine the likelihood of the received data being usable. This measure of confidence can be used to intelligently fuse sensors, or provide insight about how a vehicle should respond to incoming data.

image of Nominal (left) and degraded (center and right) images with confidence values overlaid

Nominal (left) and degraded (center and right) images with confidence values overlaid. Confidence calculations were performed in real time.

Key Elements of the Real-time Sensor Validation

  • Provides a measure of sensor health in real time for diagnostics or decision making
  • Intelligent configuration selection mechanism ensures optimal performance
  • Flexible structure allows for easy integration with multiple sensor types
  • Does not require comprehensive failure mode analysis

Results

SwRI has developed a set of tools and procedures that allow for increased awareness of the health of a sensor. The system is capable of detecting and responding to both critical and subtle failures in real time.

Related Patent

  • Patent Pending:
    Lemmer, S., and Chambers, D., inventors; Southwest Research Institute, assignee. Sensor Data Confidence Estimation Based on Statistical Analysis. United States patent application 14732002, filed June 5, 2015.

Robert Heller, Ph.D., Program Director, (210) 522-3824, rheller@swri.org

07/13/16