Driving behavior is determined by individual driving capability features to control particular type of vehicle. These features form particular driving style, which depending on application may be categorized as: aggressive and safe driving, eco and fuel-demanding driving, sober and drowsy driving etc. Nowadays it is useful for transport companies to analyze driving behavior of their employees (or clients), because driving behavior affects vehicle life time, vehicle failure intensity, quality of transport services. Aggressive driving are considered all negative driving features that damage vehicle, increase risk of traffic accident, worsen transport services. In this work a detail driving behavior analysis is performed using inertial measurement sensor – 3- axis G-sensor (accelerometer) signal information, which is attached to vehicle. There are to objectives of this research: recognition of aggressive and safe driving behavior when signal information is obtained from vehicle that is driven in aggressive and safe driving styles; driving behavior identification (driver classification) when signals are obtained from public transport bus that is driven by two drivers (one at a time). Signal processing analysis is performed and algorithms formed that reduce noise level and detect outliers in signal by combining moving median and average filters. Also a special signal processing is done on public transport bus signals when stopping time must be extracted and deleted from raw signal. This is performed by applying Gaussian mixture models. Algorithms of feature extraction from accelerometer signal are formed using both time and frequency domain information. From time domain the following features are extracted: quantiles of signal; difference between quantiles; correlation between signals; data threshold violation intensity; standard deviation of jerk signal (first order differences of original signal). In the frequency domain relative power spectral density in particular frequency band are extracted as features for ...


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    Title :

    Intelektualios vairavimo elgsenos įvertinimo sistemos kūrimas ir tyrimas ; Development and research on intelligent driving style evaluation system



    Publication date :

    2015-06-09


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    Lithuanian , English



    Classification :

    DDC:    380 / 629