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INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING

Abstract: 

Performing driving behaviors based on causal reasoning is essential to ensure driving safety. In this work, we investigated how state-of-the-art 3D Convolutional Neural Networks (CNNs) perform on classifying driving behaviors based on causal reasoning. We proposed a perturbation-based visual explanation method to inspect the models' performance visually. By examining the video attention saliency, we found that existing models could not precisely capture the causes (e.g., traffic light) of the specific action (e.g., stopping). Therefore, the Temporal Reasoning Block (TRB) was proposed and introduced to the models. With the TRB models, we achieved the accuracy of 86.3%, which outperform the state-of-the-art 3D CNNs from previous works. The attention saliency also demonstrated that TRB helped models focus on the causes more precisely. With both numerical and visual evaluations, we concluded that our proposed TRB models were able to provide accurate driving behavior prediction by learning the causal reasoning of the behaviors.

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Paper Details

Authors:
Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, C.-H. Huck Yang, J. Tegner, Y.-C. James Tsai
Submitted On:
14 May 2020 - 11:12am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Yi-Chieh Liu, Yung-An Hsieh
Paper Code:
4790
Document Year:
2020
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INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING.pdf

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[1] Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, C.-H. Huck Yang, J. Tegner, Y.-C. James Tsai, "INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5305. Accessed: Sep. 26, 2020.
@article{5305-20,
url = {http://sigport.org/5305},
author = {Yi-Chieh Liu; Yung-An Hsieh; Min-Hung Chen; C.-H. Huck Yang; J. Tegner; Y.-C. James Tsai },
publisher = {IEEE SigPort},
title = {INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING},
year = {2020} }
TY - EJOUR
T1 - INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING
AU - Yi-Chieh Liu; Yung-An Hsieh; Min-Hung Chen; C.-H. Huck Yang; J. Tegner; Y.-C. James Tsai
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5305
ER -
Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, C.-H. Huck Yang, J. Tegner, Y.-C. James Tsai. (2020). INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING. IEEE SigPort. http://sigport.org/5305
Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, C.-H. Huck Yang, J. Tegner, Y.-C. James Tsai, 2020. INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING. Available at: http://sigport.org/5305.
Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, C.-H. Huck Yang, J. Tegner, Y.-C. James Tsai. (2020). "INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING." Web.
1. Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, C.-H. Huck Yang, J. Tegner, Y.-C. James Tsai. INTERPRETABLE SELF-ATTENTION TEMPORAL REASONING FOR DRIVING BEHAVIOR UNDERSTANDING [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5305