Scipediacontent: Scipediacontent moved page Draft Content 438764141 to Lefevre et al 2013a

2021-02-03T19:43:33Z

Scipediacontent moved page Draft Content 438764141 to Lefevre et al 2013a

Scipediacontent: Created page with " == Abstract == International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on..."

2021-02-03T19:43:31Z

Created page with " == Abstract == International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on..."

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== Abstract ==

International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on Support Vector Machine and Bayesian ﬁltering is proposed for online lane change intention prediction. The approach uses the multiclass probabilistic outputs of the Support Vector Machine as an input to the Bayesian ﬁlter, and the output of the Bayesian ﬁlter is used for the ﬁnal prediction of lane changes. A lane tracker integrated in a passenger vehicle is used for real-world data collection for the purpose of training and testing. Data from different drivers on different highways were used to evaluate the robustness of the approach. The results demonstrate that the proposed approach is able to predict driver intention to change lanes on average 1.3 seconds in advance, with a maximum prediction horizon of 3.29 seconds.

== Original document ==

The different versions of the original document can be found in:

* [https://hal.inria.fr/hal-00821309/file/Kumar_IV_13.pdf https://hal.inria.fr/hal-00821309/file/Kumar_IV_13.pdf]

* [http://xplorestaging.ieee.org/ielx7/6601112/6629437/06629564.pdf?arnumber=6629564 http://xplorestaging.ieee.org/ielx7/6601112/6629437/06629564.pdf?arnumber=6629564],
: [http://dx.doi.org/10.1109/ivs.2013.6629564 http://dx.doi.org/10.1109/ivs.2013.6629564]

* [https://hal.inria.fr/hal-00821309 https://hal.inria.fr/hal-00821309],
: [https://hal.inria.fr/hal-00821309/document https://hal.inria.fr/hal-00821309/document],
: [https://hal.inria.fr/hal-00821309/file/Kumar_IV_13.pdf https://hal.inria.fr/hal-00821309/file/Kumar_IV_13.pdf]

* [https://ieeexplore.ieee.org/document/6629564 https://ieeexplore.ieee.org/document/6629564],
: [https://hal.inria.fr/hal-00821309/document https://hal.inria.fr/hal-00821309/document],
: [https://dblp.uni-trier.de/db/conf/ivs/ivs2013.html#KumarPLL13 https://dblp.uni-trier.de/db/conf/ivs/ivs2013.html#KumarPLL13],
: [https://hal.inria.fr/hal-00821309 https://hal.inria.fr/hal-00821309],
: [https://doi.org/10.1109/IVS.2013.6629564 https://doi.org/10.1109/IVS.2013.6629564],
: [http://ieeexplore.ieee.org/iel7/6601112/6629437/06629564.pdf http://ieeexplore.ieee.org/iel7/6601112/6629437/06629564.pdf],
: [https://academic.microsoft.com/#/detail/2012849708 https://academic.microsoft.com/#/detail/2012849708]

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Lefevre et al 2013a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 438764141 to Lefevre et al 2013a

Scipediacontent: Created page with " == Abstract == International audience; Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on..."