Channel Impulse Response (CIR)

This study presents a deep learning-based framework for detecting vehicle deceleration patterns using Ultra-Wideband (UWB) Channel Impulse Response (CIR) analysis. Unlike traditional GPS or IMU-based systems, which struggle in GPS-denied environments such as tunnels, the proposed method leverages UWB CIR signal variations to classify two key driving behaviors: rapid deceleration and gradual deceleration. All data were collected from real-world experiments using UWB devices installed on actual vehicles at a professional highway testing site.

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This dataset is made of the Channel Impulse Response (CIR) data collected in 9 different environments in Ghent city, Belgium. These environments include:

1.  Fourth floor at iGent Tower in the premises of Gent University

2. Zwijnaarde Open Area

3. Stadhuis Street and Nearby

4. Zuid Mall

5. Portus Ganda

6. Sint-Pieters Railway Station

7. Krook library

8. Citadel Park

9. Graffiti Straat

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