Scipediacontent: Scipediacontent moved page Draft Content 719972867 to LeBlanc et al 2017a

2021-01-28T18:12:36Z

Scipediacontent moved page Draft Content 719972867 to LeBlanc et al 2017a

Scipediacontent: Created page with " == Abstract == Evaluating the effectiveness and benefits of driver assistance systems is essential for improving the system performance. In this paper, we propose an efficie..."

2021-01-28T18:12:32Z

Created page with " == Abstract == Evaluating the effectiveness and benefits of driver assistance systems is essential for improving the system performance. In this paper, we propose an efficie..."

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== Abstract ==

Evaluating the effectiveness and benefits of driver assistance systems is essential for improving the system performance. In this paper, we propose an efficient evaluation method for a semi-autonomous lane departure correction system. To achieve this, we apply a bounded Gaussian mixture model to describe drivers' stochastic lane departure behavior learned from naturalistic driving data, which can regenerate departure behaviors to evaluate the lane departure correction system. In the stochastic lane departure model, we conduct a dimension reduction to reduce the computation cost. Finally, to show the advantages of our proposed evaluation approach, we compare steering systems with and without lane departure assistance based on the stochastic lane departure model. The simulation results show that the proposed method can effectively evaluate the lane departure correction system.

Comment: arXiv admin note: text overlap with arXiv:1702.05779

== Original document ==

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

* [http://arxiv.org/abs/1702.06557 http://arxiv.org/abs/1702.06557]

* [http://arxiv.org/pdf/1702.06557 http://arxiv.org/pdf/1702.06557]

* [http://xplorestaging.ieee.org/ielx7/7987634/7995688/07995834.pdf?arnumber=7995834 http://xplorestaging.ieee.org/ielx7/7987634/7995688/07995834.pdf?arnumber=7995834],
: [http://dx.doi.org/10.1109/ivs.2017.7995834 http://dx.doi.org/10.1109/ivs.2017.7995834]

* [https://dblp.uni-trier.de/db/journals/corr/corr1702.html#ZhaoWL17 https://dblp.uni-trier.de/db/journals/corr/corr1702.html#ZhaoWL17],
: [http://ui.adsabs.harvard.edu/abs/2017arXiv170206557Z/abstract http://ui.adsabs.harvard.edu/abs/2017arXiv170206557Z/abstract],
: [https://arxiv.org/abs/1702.06557 https://arxiv.org/abs/1702.06557],
: [http://dblp.uni-trier.de/db/journals/corr/corr1702.html#ZhaoWL17 http://dblp.uni-trier.de/db/journals/corr/corr1702.html#ZhaoWL17],
: [https://academic.microsoft.com/#/detail/2589300346 https://academic.microsoft.com/#/detail/2589300346]

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LeBlanc et al 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 719972867 to LeBlanc et al 2017a

Scipediacontent: Created page with " == Abstract == Evaluating the effectiveness and benefits of driver assistance systems is essential for improving the system performance. In this paper, we propose an efficie..."