Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision
This paper studies and identifies driver's steering manoeuvre behaviour in near rear-end collision. Time-To-Collision (TTC) is utilized in defining driver's emergency threat assessment. The target scenario is set up under real experimental environment and the naturalistic data from the exp...
Published in: | Telkomnika (Telecommunication Computing Electronics and Control) |
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Language: | English |
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Universitas Ahmad Dahlan
2017
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2-s2.0-85111741464 Hassan N.; Zamzuri H.; Wahid N.; Zulkepli K.A.; Azmi M.Z. Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision 2017 Telkomnika (Telecommunication Computing Electronics and Control) 15 2 10.12928/TELKOMNIKA.V15I1.6133 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111741464&doi=10.12928%2fTELKOMNIKA.V15I1.6133&partnerID=40&md5=0530deeffaa64dfe155ab260cc8ac5c0 This paper studies and identifies driver's steering manoeuvre behaviour in near rear-end collision. Time-To-Collision (TTC) is utilized in defining driver's emergency threat assessment. The target scenario is set up under real experimental environment and the naturalistic data from the experiment are collected. Four normal drivers are employed for the experiment to perform the manoeuvre. Artificial Neural Network (ANN) is proposed to model the behaviour of the driver's steering manoeuvre. The results show that all drivers manage to perform steering manoeuvre within the safe TTC region and the modelling results from ANN are reasonably positive. With further studies and improvements, this model would benefit to evaluate the driving reliability to enhance traffic safety and Intelligent Transportation System. © 2017 Universitas Ahmad Dahlan. All Rights Reserved. Universitas Ahmad Dahlan 16936930 English Article All Open Access; Green Open Access; Hybrid Gold Open Access |
author |
Hassan N.; Zamzuri H.; Wahid N.; Zulkepli K.A.; Azmi M.Z. |
spellingShingle |
Hassan N.; Zamzuri H.; Wahid N.; Zulkepli K.A.; Azmi M.Z. Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
author_facet |
Hassan N.; Zamzuri H.; Wahid N.; Zulkepli K.A.; Azmi M.Z. |
author_sort |
Hassan N.; Zamzuri H.; Wahid N.; Zulkepli K.A.; Azmi M.Z. |
title |
Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
title_short |
Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
title_full |
Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
title_fullStr |
Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
title_full_unstemmed |
Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
title_sort |
Driver's Steering Behaviour Identification and Modelling in Near Rear-End collision |
publishDate |
2017 |
container_title |
Telkomnika (Telecommunication Computing Electronics and Control) |
container_volume |
15 |
container_issue |
2 |
doi_str_mv |
10.12928/TELKOMNIKA.V15I1.6133 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111741464&doi=10.12928%2fTELKOMNIKA.V15I1.6133&partnerID=40&md5=0530deeffaa64dfe155ab260cc8ac5c0 |
description |
This paper studies and identifies driver's steering manoeuvre behaviour in near rear-end collision. Time-To-Collision (TTC) is utilized in defining driver's emergency threat assessment. The target scenario is set up under real experimental environment and the naturalistic data from the experiment are collected. Four normal drivers are employed for the experiment to perform the manoeuvre. Artificial Neural Network (ANN) is proposed to model the behaviour of the driver's steering manoeuvre. The results show that all drivers manage to perform steering manoeuvre within the safe TTC region and the modelling results from ANN are reasonably positive. With further studies and improvements, this model would benefit to evaluate the driving reliability to enhance traffic safety and Intelligent Transportation System. © 2017 Universitas Ahmad Dahlan. All Rights Reserved. |
publisher |
Universitas Ahmad Dahlan |
issn |
16936930 |
language |
English |
format |
Article |
accesstype |
All Open Access; Green Open Access; Hybrid Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809677606546571264 |