Sensing Vehicle Conditions for Detecting Driving Behaviors by Jiadi Yu Yingying Chen & Xiangyu Xu

Author:Jiadi Yu, Yingying Chen & Xiangyu Xu
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

3.5 Conclusion

In this chapter, we address the problem of performing abnormal driving behaviors detection (coarse-grained) and identification (fine-grained) to improve driving safety. In particular, we propose a system, D 3, to detect and identify specific types of abnormal driving behaviors by sensing the vehicle’s acceleration and orientation using smartphone sensors. Compared with existing abnormal driving detection systems, D 3 not only implements coarse-grained detections but also conducts fine-grained identifications. To identify specific abnormal driving behaviors, D 3 trains a multi-class classifier model through SVM based on the acceleration and orientation patterns of specific types of driving behaviors. To obtain effective training inputs, we extract 16 effective features from driving behavioral patterns collected from the 6-month driving traces in real driving environments. The extensive experiments driving in real driving environments in another 4 months show that D 3 achieves high accuracy when detecting and identifying abnormal driving behaviors.

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.