
doi: 10.1007/11949534_50
This paper describes a novel driving pattern recognition and status monitoring system based on the orientation information. Two fixed cameras are used to capture the driver's image and the front-road image. The driver's sight line and the driving lane path are found from these 2 captured images and are mapped into a global coordinate. Two correlation coefficients among the driver's sight line, the driving lane path and the car heading direction are calculated in the global coordinate to monitor the driving status such as a safe driving status, a risky driving status and a dangerous driving status. The correlation coefficients between the lane path and car heading direction in a fixed period are analyzed and recognized as one of 4 driving patterns by HMM. Four driving patterns including the driving in a straight lane, the driving in a curve lane, the driving of changing lanes, and the driving of making a turn are able to be recognized so far.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
