By Rui Sun
This thesis introduces a brand new built-in set of rules for the detection of lane-level abnormal riding. up to now, there was little or no development within the skill to become aware of lane point abnormal using kinds, more often than not because of an absence of excessive functionality positioning recommendations and appropriate using trend acceptance algorithms. The set of rules combines info from the worldwide Positioning procedure (GPS), Inertial dimension Unit (IMU) and lane info utilizing complex filtering equipment. The car nation inside of a lane is predicted utilizing a Particle clear out (PF) and a longer Kalman filter out (EKF). The country info is then used inside of a unique Fuzzy Inference approach (FIS) dependent set of rules to realize sorts of abnormal using. Simulation and box trial effects are used to illustrate the accuracy and reliability of the proposed abnormal using detection method.
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Additional info for An Integrated Solution Based Irregular Driving Detection
The ﬁrst focuses on the detection and recognition of a vehicle’s real-time driving patterns. The second focuses on monitoring the driver’s physical behaviour in order to prevent irregular behaviour due to fatigue or inattention. 1 Detection of Real-time Driving Patterns This category includes the use of sensors for positioning, orientation, velocity and vision to detect vehicle motion data. The data is subsequently analysed to ﬁnd cues to identify irregular driving and then used for some safety related applications such as collision avoidance or lane departure warnings.
In terms of integrity, the requirement varies for different applications. The continuity parameter is not quantiﬁed for the safety related applications. Furthermore, availability is not quantiﬁed for some applications. The above requirements and applications are just examples of general information for the positioning system used for the ITS applications. From the table above, accuracy is an important requirement for the PNT system in many ITS applications. Currently, however, there are no speciﬁc requirements deﬁned for lane level irregular driving detection systems, despite the fact that this forms an important basis for many safety related ITS applications.
PPP requires a long convergence time during initialization and is not suitable for highly dynamic applications, while RTK, which exhibits stable positioning accuracy in both static and dynamic modes, is more suitable for lane level irregular driving detection. In the next chapter, the state-of-the-art studies in irregular driving detection will be reviewed. , & Rimmo, P. (1998). Dimensions of aberrant driver behaviour. Ergonomics, 41, 39–56. Alves, P. (2004). Development of two novel carrier phase-based methods for multiple reference station positioning.
An Integrated Solution Based Irregular Driving Detection by Rui Sun