A Method for Detecting Driver's Risk Level Based on Hidden Markov Model
A hidden Markov and risk level technology, applied in the level field, can solve the problems of less research on driver risk level identification and cannot meet traffic safety management, so as to reduce casualties and property losses, improve overall safety, and improve safety effect
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[0034] The present invention will be further described below with reference to the accompanying drawings.
[0035] The invention firstly designs the acceleration index by analyzing the speed data of each driver, and uses the characteristic index to identify the driving behavior sequence of the driver. Then, using the obtained alarm type of each driver, the K-Means clustering method is used to classify the drivers into low-risk drivers, medium-risk drivers and high-risk drivers. The classification of the driver's risk level is the basis for the identification of the driver's risk level, and whether the classification is reasonable or not directly determines the success or failure of the recognition algorithm. After training the hidden Markov model with some data, the driving behavior sequence is recognized.
[0036] Among them, there are five driving behaviors: fast deceleration, slow deceleration, normal driving, slow acceleration, and fast acceleration.
[0037] 1. Calculat...
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