Scipediacontent: Scipediacontent moved page Draft Content 281811726 to Koch et al 2019a

2021-02-03T16:14:43Z

Scipediacontent moved page Draft Content 281811726 to Koch et al 2019a

Scipediacontent: Created page with " == Abstract == In recent years, driver behavior analysis has led to countless driver assistance systems. In these systems, earlier detection of a driver’s maneuver intenti..."

2021-02-03T16:14:39Z

Created page with " == Abstract == In recent years, driver behavior analysis has led to countless driver assistance systems. In these systems, earlier detection of a driver’s maneuver intenti..."

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== Abstract ==

In recent years, driver behavior analysis has led to countless driver assistance systems. In these systems, earlier detection of a driver’s maneuver intentions offers opportunities to improve driving experience and safety. Especially brake maneuvers are of fundamental importance because they are directly related to the avoidance of potential hazards.Current state-of-the-art brake assistance systems rely on the release speed of accelerator pedal as an indicator whether a brake event is planned. However, this simple and practical algorithm, fails to capture the overall movement pattern of accelerator pedal behaviors and cannot utilize rich information from different vehicle sensors.To address this issue, we propose a novel recurrent neural network architecture for the purpose of brake maneuver prediction. The proposed method exploits the advantages of multiple sensors. Unlike conventional practices where all signals are aggregated to a single neural network, we leverage the confidence of each sensor. We evaluate our approach based on a dataset of 44 drivers, comprising around 500 hours of naturalistic driving data. The evaluation results show that the proposed algorithm outperforms baseline method by large margin.

== Original document ==

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

* [https://www.alexandria.unisg.ch/259256/2/Brake%20Maneuver%20Prediction%E2%80%93An%20Inference%20Leveraging%20RNN%20Focus%20on%20Sensor%20Confidence.pdf https://www.alexandria.unisg.ch/259256/2/Brake%20Maneuver%20Prediction%E2%80%93An%20Inference%20Leveraging%20RNN%20Focus%20on%20Sensor%20Confidence.pdf]

* [http://xplorestaging.ieee.org/ielx7/8907344/8916833/08917405.pdf?arnumber=8917405 http://xplorestaging.ieee.org/ielx7/8907344/8916833/08917405.pdf?arnumber=8917405],
: [http://dx.doi.org/10.1109/itsc.2019.8917405 http://dx.doi.org/10.1109/itsc.2019.8917405]

* [https://dblp.uni-trier.de/db/conf/itsc/itsc2019.html#LiuKGW19 https://dblp.uni-trier.de/db/conf/itsc/itsc2019.html#LiuKGW19],
: [https://www.alexandria.unisg.ch/259256 https://www.alexandria.unisg.ch/259256],
: [https://www.research-collection.ethz.ch/handle/20.500.11850/387253 https://www.research-collection.ethz.ch/handle/20.500.11850/387253],
: [https://academic.microsoft.com/#/detail/2989770297 https://academic.microsoft.com/#/detail/2989770297]

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Koch et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 281811726 to Koch et al 2019a

Scipediacontent: Created page with " == Abstract == In recent years, driver behavior analysis has led to countless driver assistance systems. In these systems, earlier detection of a driver’s maneuver intenti..."