Ocena sloga vožnje na podlagi kontekstualnih podatkov

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Language:	English
Year of publishing:	2017
Typology:	2.08 - Doctoral Dissertation
Organization:	UL FE - Faculty of Electrical Engineering
Publisher:	[M. Sysoev]
UDC:	004.6:629.03.072(043.3)
COBISS:	11768148
Views:	1358
Downloads:	477
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Secondary language:	Slovenian
Secondary title:	Estimation of driving style based on contextual data
Secondary abstract:	New models and methods have been designed to estimate the influence of the context, the drivers' activity and behavioural information to the driving style in usual automotive environment in natural driving and to investigate stress based on smartphone sensors data considering the current activity. For these purposes, an experiment was conducted using three types of validation metrics: (i) the stress recognition metric, considering the current activity based on data collected before driving; (ii) the metric based on a self-assessment of driving style; (iii) and the metric based on an objective driving data. 67 hours of driving were collected for further analysis in pilot study. Ten drivers were involved in the experiment. Algorithms for detecting stress right before driving (based on analysis contextual and behavioural data) achieved 71.4% of accuracy for the true positive rate using questionnaire analysis for validation, established by psychologists. The possibility of applying driving style self-assessments as second validation metric was evaluated as not precise enough. In the last third metric a new approach was suggested to estimate the driving style based on data collected before and during the driving tasks including new parameters for data analysis as a car door opening and closing manner and application for a type activity recognition based on Google activity recognition API. Further analysis, in which metric of driving style from objective driving data was correlated with the data collected before driving and with the data collected before and during the first 1 min of driving, showed significant correlation results, from 72.7% to 90.9% of true positive rate. Results of the pilot study for the driving style estimation system showed a success in recognizing driving style based on the data collected before and during the driving. In cases when maximal non-invasiveness should be reached, only smartphone and car door as data sources can be used to estimate the driving style. Considering these demands we were able to achieve 72.7% of true positive rate of driving style recognition. It is less compared to the analysis with using the first 1 min of the driving data, but the results are obtained completely before the driving, so they could be used in advance as feedbacks to the drivers about the potentially aggressive driving style. The obtained recognition rates lend support to the hypothesis that contextual, behavioural and activity data could be used for the driving style estimation.
Secondary keywords:	slog vožnje;kontekstualni podatki;stres;disertacije;Vožnja;Disertacije;Slog;Podatki;
Type (COBISS):	Doctoral dissertation
Study programme:	1000319
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za elektrotehniko
Pages:	XXVII, 97 str.
ID:	10843838