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Driving Activity Recognition Using UWB Radar and Deep Neural Networks.

Iuliia Brishtel^1,2, Stephan Krauss¹, Mahdi Chamseddine¹

¹Department of Augmented Vision, German Research Center for Artificial Intelligence, Trippstadter Str. 122, 67663 Kaiserslautern, Germany.

Sensors (Basel, Switzerland)

|January 21, 2023

Summary

This study introduces a novel radar-based system for in-car activity monitoring, offering a privacy-preserving alternative to vision systems. The research focuses on classifying driving activities using deep neural networks and a new dataset for improved generalization.

Keywords:

artificial intelligence and machine learning for radar modern radar applications radar sensors for driver monitoring radar signal processing techniques

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Area of Science:

Automotive Engineering
Signal Processing
Machine Learning

Background:

In-car activity monitoring is crucial for automotive safety functions.
Current methods predominantly rely on vision systems, which raise privacy concerns.
Radar technology presents a low-cost, privacy-preserving alternative for activity monitoring.

Purpose of the Study:

To introduce a novel approach for in-car activity monitoring using ultra-wideband (UWB) radar.
To classify driving activities by leveraging the Doppler signal processed by deep neural networks.
To enhance generalization to unseen individuals and provide a benchmark dataset for future research.

Main Methods:

Utilizing the Doppler signal from an ultra-wideband (UWB) radar as input.
Employing deep neural networks for the classification of driving activities.
Developing and releasing a new radar driving activity dataset (RaDA) for public use.

Main Results:

Demonstrated a novel method for in-car activity classification using UWB radar Doppler signals.
Achieved classification of driving activities through deep neural network analysis.
Established a new dataset (RaDA) to facilitate research and benchmarking in radar-based activity monitoring.

Conclusions:

Radar-based systems offer a viable, privacy-preserving solution for in-car activity monitoring.
Deep neural networks effectively classify driving activities using UWB radar Doppler signals.
The RaDA dataset will spur further development and comparison of radar-based automotive safety technologies.