Prediction of Driving Actions from Driving Signals
Prediction of Driving Actions from Driving Signals
- New search for: Itoh, Toshihiko
- New search for: Yamada, Shinya
- New search for: Yamamoto, Kazumasa
- New search for: Araki, Kenji
- New search for: Itoh, Toshihiko
- New search for: Yamada, Shinya
- New search for: Yamamoto, Kazumasa
- New search for: Araki, Kenji
Abstract A spoken dialogue system for car-navigation systems may be able to provide more natural and smoother communications but it must also cause safety problems. One of these problems is distraction whereby machine operation and voice conversations influence the driver. Even the use of a simple speech interface may affect the driving operation. We consider that a spoken dialogue system which can understand the driver's situation and change its dialogue rhythm according to that situation would be safe as part of a car-navigation system. For this to be possible, the system needs to predict and recognize driver's actions from environmental information such as driving signals. In this chapter, we report the results of an experiment on predicting driver actions. The action prediction system uses HMM-based pattern recognition only on driving signals and does not use position information. Its best driving action prediction accuracy was 0.632.
Document information
Prediction of Driving Actions from Driving Signals
2008-10-06
14 pages
Article/Chapter (Book)
Electronic Resource
English
Car-navigation systems , Distraction , Hidden Markov model , HMM-based pattern recognition , Dialogue rhythm , Driving action , Driving prediction , Driving recognition , Driving signal , Safety , Spoken dialogue , Spoken dialogue interface Engineering , Automotive Engineering , Signal, Image and Speech Processing , User Interfaces and Human Computer Interaction , Communications Engineering, Networks
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