Detection of Driver Emergency Steering Intention Using EMG Signal

Aberham Genetu Feleke; Luzheng Bi; Weijie Fei

doi:10.1109/RCAR49640.2020.9303261

Detection of Driver Emergency Steering Intention Using EMG Signal

Aberham Genetu Feleke, Luzheng Bi^*, Weijie Fei

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

In this paper, a method to detect driver emergency-steering intention by using Electromyography (EMG) signals is presented. An emergency driving situation, where a driver tries to avoid collisions by steering alone, is anticipated. EMG signals are acquired from the upper limb, while the driver steers a vehicle under normal and emergency driving situations. A linear discriminant analysis (LDA) and multilayer perceptron (MLP) classifiers are constructed to detect the emergency steering from normal steering during driving. Our experimental results show that the emergency steering situation can be detected from EMG signal at about 607ms after the onset of visual stimuli and before a collision happens with an accuracy of greater than 86%.

Original language	English
Title of host publication	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	280-285
Number of pages	6
ISBN (Electronic)	9781728172927
DOIs	https://doi.org/10.1109/RCAR49640.2020.9303261
Publication status	Published - 28 Sept 2020
Event	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 - Virtual, Asahikawa, Hokkaido, Japan Duration: 28 Sept 2020 → 29 Sept 2020

Publication series

Name	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020

Conference

Conference	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
Country/Territory	Japan
City	Virtual, Asahikawa, Hokkaido
Period	28/09/20 → 29/09/20

Keywords

Driver intention
Driving Assistant
Electromyography (EMG)
Emergency steering

Access to Document

10.1109/RCAR49640.2020.9303261

Cite this

Feleke, A. G., Bi, L., & Fei, W. (2020). Detection of Driver Emergency Steering Intention Using EMG Signal. In 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 (pp. 280-285). Article 9303261 (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RCAR49640.2020.9303261

@inproceedings{8f85686745f54d31a209b8fffc5d7a81,

title = "Detection of Driver Emergency Steering Intention Using EMG Signal",

abstract = "In this paper, a method to detect driver emergency-steering intention by using Electromyography (EMG) signals is presented. An emergency driving situation, where a driver tries to avoid collisions by steering alone, is anticipated. EMG signals are acquired from the upper limb, while the driver steers a vehicle under normal and emergency driving situations. A linear discriminant analysis (LDA) and multilayer perceptron (MLP) classifiers are constructed to detect the emergency steering from normal steering during driving. Our experimental results show that the emergency steering situation can be detected from EMG signal at about 607ms after the onset of visual stimuli and before a collision happens with an accuracy of greater than 86%.",

keywords = "Driver intention, Driving Assistant, Electromyography (EMG), Emergency steering",

author = "Feleke, {Aberham Genetu} and Luzheng Bi and Weijie Fei",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 ; Conference date: 28-09-2020 Through 29-09-2020",

year = "2020",

month = sep,

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doi = "10.1109/RCAR49640.2020.9303261",

language = "English",

series = "2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020",

address = "United States",

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Feleke, AG, Bi, L & Fei, W 2020, Detection of Driver Emergency Steering Intention Using EMG Signal. in 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020., 9303261, 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020, Institute of Electrical and Electronics Engineers Inc., pp. 280-285, 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020, Virtual, Asahikawa, Hokkaido, Japan, 28/09/20. https://doi.org/10.1109/RCAR49640.2020.9303261

Detection of Driver Emergency Steering Intention Using EMG Signal. / Feleke, Aberham Genetu; Bi, Luzheng; Fei, Weijie.
2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 280-285 9303261 (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Detection of Driver Emergency Steering Intention Using EMG Signal

AU - Feleke, Aberham Genetu

AU - Bi, Luzheng

AU - Fei, Weijie

PY - 2020/9/28

Y1 - 2020/9/28

N2 - In this paper, a method to detect driver emergency-steering intention by using Electromyography (EMG) signals is presented. An emergency driving situation, where a driver tries to avoid collisions by steering alone, is anticipated. EMG signals are acquired from the upper limb, while the driver steers a vehicle under normal and emergency driving situations. A linear discriminant analysis (LDA) and multilayer perceptron (MLP) classifiers are constructed to detect the emergency steering from normal steering during driving. Our experimental results show that the emergency steering situation can be detected from EMG signal at about 607ms after the onset of visual stimuli and before a collision happens with an accuracy of greater than 86%.

AB - In this paper, a method to detect driver emergency-steering intention by using Electromyography (EMG) signals is presented. An emergency driving situation, where a driver tries to avoid collisions by steering alone, is anticipated. EMG signals are acquired from the upper limb, while the driver steers a vehicle under normal and emergency driving situations. A linear discriminant analysis (LDA) and multilayer perceptron (MLP) classifiers are constructed to detect the emergency steering from normal steering during driving. Our experimental results show that the emergency steering situation can be detected from EMG signal at about 607ms after the onset of visual stimuli and before a collision happens with an accuracy of greater than 86%.

KW - Driver intention

KW - Driving Assistant

KW - Electromyography (EMG)

KW - Emergency steering

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DO - 10.1109/RCAR49640.2020.9303261

M3 - Conference contribution

AN - SCOPUS:85099367071

T3 - 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020

SP - 280

EP - 285

BT - 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020

Y2 - 28 September 2020 through 29 September 2020

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Feleke AG, Bi L, Fei W. Detection of Driver Emergency Steering Intention Using EMG Signal. In 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 280-285. 9303261. (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020). doi: 10.1109/RCAR49640.2020.9303261

Detection of Driver Emergency Steering Intention Using EMG Signal

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