Streamlining Connected Automated Vehicle Test Data Collection and Evaluation in the Hardware-in-the-Loop Environment

Research Team: Hao Liu (lead), Xiao-Yun Lu, and Zhe Fu

UC Campus(es): UC Berkeley

Problem Statement: With the rapid development of Connected Automated Vehicles (CAV) technologies, it is urgent for both researchers and policy makers to obtain and evaluate good quality CAV data to better understand CAV impacts. CAV hardware-in-the-loop (HIL) tests can expedite CAV performance evaluation and system implementation.

Project Description: This project equipped an existing HIL test tool with data management functions. The improved HIL test tool is able to streamline CAV data collection and quality so that it is beneficial for performance analysis. A detailed comparison and selection of available database tools, database instance design and implementation were also performed to help other California institutes develop and improve their own systems. A user-friendly test tool setup guide and a specific user guide was also developed to help potential users get started using the data management functions. In addition, two example CAV tests were performed to demonstrate the detailed data collection and performance evaluation procedure. These examples can serve as a guide to assist other users with applying the HIL test tool in their own CAV tests.

Status: Completed

Budget: $79,901