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https://doi.org/10.1109/itsc.2...
Conference object . 2009 . Peer-reviewed
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Article . 2009
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Prediction model of driving behavior based on traffic conditions and driver types

Authors: Takanori Nishino; Hideomi Amata; Norihide Kitaoka; Chiyomi Miyajima; Kazuya Takeda;

Prediction model of driving behavior based on traffic conditions and driver types

Abstract

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.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Average