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

Zhe Fu, Hao PhD Liu and Xiao-Yun PhD Lu

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: Quality data collection, processing, and analysis are foundational to good research, policy making and regulation development. 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. This research aims at equipping an existing HIL test tool with data management functions. To this end, a database instance on MySQL has been integrated with an existing HIL test tool. The improved HIL test tool can greatly 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 have been performed to help other California institutes develop and improve their own systems. A user-friendly test tool setup guide and a specific user guide have been provided to enable potential users to easily get started using the data management functions. In addition, two example CAV tests are presented to demonstrate the detailed data collection and performance evaluation procedure. Those examples can serve as a guide to assist users in applying the HIL test tool in their own CAV tests.

Keywords: Engineering; Connected vehicles; automated vehicles; data collection; hardware in loop simulation; databases; data management; data quality (search for similar items in EconPapers)
Date: 2020-12-01
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