Using Dictionary Learning and Sparse Coding on Driving Behavior Analysis
| Autor: | Hsi-Chih Hu, 胡曦之 |
|---|---|
| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 Traffic safety has been an important issue for a long time. Most of the traffic accident are happened because of the aggressive driving behavior. For insurance company, understanding the driver's behavior is more appropriate to define the insurance instead of making decisions based on vehicle and driver characteristics. To define the behavior for drivers, we need to classify the trip data for different driver. In this research, we focus on two things. First one is learning the sequential data and generate appropriate features by dictionary learning and sparse coding. Second one is using the sparse code features with binary classification to identify the trips between drivers. We also analyze three models for driving behaviors: full-data model, time model and location model. We get the best model which affect the drivers' behavior more to identify the trip for drivers. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|