The L3Pilot Data Management Toolchain for a Level 3 Vehicle Automation Pilot
Journal article, 2020

As industrial research in automated driving is rapidly advancing, it is of paramount importance to analyze field data from extensive road tests. This paper investigates the design and development of a toolchain to process and manage experimental data to answer a set of research questions about the evaluation of automated driving functions at various levels, from technical system functioning to overall impact assessment. We have faced this challenge in L3Pilot, the first comprehensive test of automated driving functions (ADFs) on public roads in Europe. L3Pilot is testing ADFs in vehicles made by 13 companies. The tested functions are mainly of Society of Automotive Engineers (SAE) automation level 3, some of them of level 4. In this context, the presented toolchain supports various confidentiality levels, and allows cross-vehicle owner seamless data management, with the efficient storage of data and their iterative processing with a variety of analysis and evaluation tools. Most of the toolchain modules have been developed to a prototype version in a desktop/cloud environment, exploiting state-of-the-art technology. This has allowed us to efficiently set up what could become a comprehensive edge-to-cloud reference architecture for managing data in automated vehicle tests. The project has been released as open source, the data format into which all vehicular signals, recorded in proprietary formats, were converted, in order to support efficient processing through multiple tools, scalability and data quality checking. We expect that this format should enhance research on automated driving testing, as it provides a shared framework for dealing with data from collection to analysis. We are confident that this format, and the information provided in this article, can represent a reference for the design of future architectures to implement in vehicles.

big data

Internet of things

reference architecture


data toolchain

automated vehicles

field operational tests

edge-to-cloud architectures


Johannes Hiller

RWTH Aachen University

Sami Koskinen

Technical Research Centre of Finland (VTT)

Riccardo Berta

University of Genoa

Nisrine Osman

University of Genoa

Ben Nagy

Jaguar Land Rover

Francesco Bellotti

University of Genoa

Ashfaqur Rahman

Jaguar Land Rover

Erik Svanberg

Chalmers, Mechanics and Maritime Sciences, Vehicle Safety, Accident Prevention

SAFER, The Vehicle and Traffic Safety Centre

Hendrik Weber

RWTH Aachen University

Eduardo H. Arnold

The University of Warwick

Mehrdad Dianati

The University of Warwick

Alessandro De Gloria

University of Genoa


2079-9292 (eISSN)

Vol. 9 5 809

L3Pilot - Piloting Automated Driving on European Roads

European Commission (EC) (723051), 2017-09-13 -- 2020-09-13.

Areas of Advance


Subject Categories

Software Engineering

Vehicle Engineering




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Latest update

9/7/2021 1