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2023-01-16T04:32:36Z
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Prediction model of driving behavior based on traffic conditions and driver types
Amata, Hideomi
38117
Miyajima, Chiyomi
38118
Nishino, Takanori
38119
Kitaoka, Norihide
38120
Takeda, Kazuya
38121
We investigate the driving behavior differences at unsignalized intersections between expert and nonexpert drivers. By analyzing real-world driving data, significant differences were seen in pedal operations but not in steering operations. Easing accelerator behaviors before entering unsignalized intersections were especially seen more often in expert driving. We propose two prediction models for driving behaviors in terms of traffic conditions and driver types: one is based on multiple linear regression analysis, which predicts whether the driver will steer, ease up on the accelerator, or brake. The second predicts driver decelerating intentions using a Bayesian network. The proposed models could predict the three driving actions with over 70% accuracy, and about 50% of decelerating intentions were predicted before entering unsignalized intersections.
journal article
IEEE
2009-10-04
application/pdf
12th International IEEE Conference on Intelligent Transportation Systems (ITSC '09)
1
6
http://hdl.handle.net/2237/13899
https://nagoya.repo.nii.ac.jp/record/12023/files/Amata_ITSC2009-10.pdf
eng
978-1-4244-5519-5
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