Towards Affordable On-track Testing for Autonomous Vehicle - A Kriging-based Statistical Approach
For autonomous vehicle developers, this work offers a method to lower testing costs, though it is an incremental application of existing Kriging techniques.
The paper proposes a Kriging-based statistical approach to reduce the number of experiments or simulations needed for autonomous vehicle on-track testing, demonstrating its application in lane change scenarios.
This paper discusses the use of Kriging model in Automated Vehicle evaluation. We explore how a Kriging model can help reduce the number of experiments or simulations in the Accelerated Evaluation procedure. We also propose an adaptive sampling scheme for selecting samples to construct the Kriging model. Application examples in the lane change scenario are presented to illustrate the proposed methods.