WiP Abstract: Edge-Based Privacy of Naturalistic Driving Data Collection

Jan 1, 2023·
Matt Bunting
Matt Bunting
,
Matthew Nice
Dan Work
Dan Work
Jonathan Sprinkle
Jonathan Sprinkle
,
Roman Golota
· 1 min read
DOI
Type
Publication
Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023)
publications

Collecting large driving datasets is important for data-driven transportation research and studied in naturalistic driving [3]. Due to the standard implementation of a Controller Area Network (CAN) bus for a vehicle’s inter-module communication, many off-the-shelf devices can easily transform a vehicle into a rich data collection utility [2]. Vehicles with Adaptive Cruise Control (ACC) are an example of a feature resulting in emergent traffic behavior when scaled [4]. While these utilities were designed with particular data use cases, data may be publicly shared to benefit other researchers through online tools like CyVerse [1]. However, such data should only be shared when any private information is removed. This private information may exist as a set of GPS coordinates, since the start and end points of a trip may designate a driver’s place of residence or work.

Matt Bunting
Authors
Research Scientist
Dr. Matthew Bunting is a Research Scientist at the Institute for Software Integrated Systems at Vanderbilt University. He joined Vanderbilt in 2022 having previously been a postdoctoral scholar at the University of Arizona from 2020-2022. His research is in embedded control software and visualization for cyber-physical systems.
Authors
Former PhD Student
Dan Work
Authors
Professor
Dan Work is a Chancellor Faculty Fellow and professor in civil and environmental engineering, computer science, and the Institute for Software Integrated Systems at Vanderbilt University.
Jonathan Sprinkle
Authors
Professor and Chair of Computer Science
Professor of Computer Science at Vanderbilt University. Research in cyber-physical systems, autonomous vehicles, and domain-specific modeling.