Human Behavior Based Predictive Brake Assistance

Driver assistance systems have both the potential to alert the driver to critical situations and distract or annoy the driver if the driver is already aware of the situation. As systems attempt to preemptively warn drivers more and more in advance, this problem becomes exacerbated. We present a pred...

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Bibliographic Details
Published in2006 IEEE Intelligent Vehicles Symposium pp. 8 - 12
Main Authors Mccall, J.C., Trivedi, M.M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2006
Subjects
Adaptive control
Bayesian methods
Control systems
Hidden Markov models
Humans
Programmable control
Remotely operated vehicles
Road accidents
Sensor systems
Vehicle driving
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ISBN490112286X
9784901122863
ISSN1931-0587
DOI10.1109/IVS.2006.1689597

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Summary:Driver assistance systems have both the potential to alert the driver to critical situations and distract or annoy the driver if the driver is already aware of the situation. As systems attempt to preemptively warn drivers more and more in advance, this problem becomes exacerbated. We present a predictive braking assistance system that identifies not only the need for braking action, but also whether or not a braking action is being planned by the driver. Our system uses a Bayesian framework to determine the criticality of the situation by assessing (1) the probability that braking should be performed given observations of the vehicle and surround and (2) the probability that the driver intends to perform a braking action. We train and evaluate our system using over 22 hours of data collected from real driving scenarios with 28 different drivers
ISBN:490112286X
9784901122863
ISSN:1931-0587
DOI:10.1109/IVS.2006.1689597