Howdrive 3D : Driver Distraction Dataset

Citation Author(s):
Amal
Ezzouhri
Zakaria
Charouh
Mounir
Ghogho
Zouhair
Guennoun
Submitted by:
Amal Ezzouhri
Last updated:
Mon, 07/25/2022 - 15:44
DOI:
10.21227/f9z3-0438
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Abstract 

To study the driver's behavior in real traffic situations, we conducted experiments using an instrumented vehicle, which comprises:

(i) a camera, installed above the vehicle's side window and oriented toward the driver, and (ii) a Mobile Digital Video Recorder (MDVR).

One part of the data was collected in real-world driving conditions. The other part was collected by asking drivers to simulate different types of driving behaviors in the instrumented vehicle, but without moving the vehicle for safety reasons. Nine drivers were involved in the experiment. Each of them was asked to perform the ten activities separately (i.e., one activity for each video sequence) while driving or pretending to drive, which took about 15 minutes for each driver resulting in about 450 images per class per driver. After the manual examination, a total of about 38 thousand images were preserved.

Acknowledgment

This work is partly funded by the National Agency for Road Safety (NARSA) of the Moroccan Ministry of Equipment, Transport, Logistics and Water, via the National Center for Scientific and Technical Research (CNRST).

Instructions: 

 

 You must cite the Scientific Data journal paper: A. Ezzouhri, Z. Charouh, M. Ghogho and Z. Guennoun, "Robust Deep Learning-based Driver Distraction Detection and Classification," in IEEE Access, doi: 10.1109/ACCESS.2021.3133797.

 

Comments

good job

Submitted by li zheng on Tue, 05/17/2022 - 23:34

thanks

Submitted by yijia deng on Mon, 03/18/2024 - 22:07