A simulation platform calibration method for automated vehicle evaluation: accurate on both vehicle level and traffic flow level

TL;DR

This paper presents a fully automated calibration method for simulation platforms that significantly improves accuracy and efficiency in replicating vehicle interactions and traffic flow for automated vehicle testing.

Contribution

It introduces a novel calibration approach that ensures high accuracy at both vehicle and traffic flow levels, outperforming existing methods in efficiency and precision.

Findings

Enhances interaction replication accuracy by 83.53%

Increases calibration efficiency by 76.75%

Maintains high accuracy across vehicle and traffic flow metrics

Abstract

Simulation testing is a fundamental approach for evaluating automated vehicles (AVs). To ensure its reliability, it is crucial to accurately replicate interactions between AVs and background traffic, which necessitates effective calibration. However, existing calibration methods often fall short in achieving this goal. To address this gap, this study introduces a simulation platform calibration method that ensures high accuracy at both the vehicle and traffic flow levels. The method offers several key features:(1) with the capability of calibration for vehicle-to-vehicle interaction; (2) with accuracy assurance; (3) with enhanced efficiency; (4) with pipeline calibration capability. The proposed method is benchmarked against a baseline with no calibration and a state-of-the-art calibration method. Results show that it enhances the accuracy of interaction replication by 83.53% and boosts calibration efficiency by 76.75%. Furthermore, it maintains accuracy across both vehicle-level and traffic flow-level metrics, with an improvement of 51.9%. Notably, the entire calibration process is fully automated, requiring no human intervention.