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22 December 2021 Driving behavior classification and prediction method based on multiple logistic regression model
Chang Liu, Xing Kai Meng, Chu na Wu, Xue ran Wang, Wen hui Luo, Hong wen Xia
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Proceedings Volume 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021); 120585R (2021) https://doi.org/10.1117/12.2619757
Event: 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 2021, Chongqing, China
Abstract
Traffic safety and pollution are key challenges for the sustainable development of urban transportation. Researches show that driving behavior accounts for a significant proportion of many factors affecting traffic safety and ecology. Therefore, reasonable research on safe and ecological driving behaviour can effectively interfere with the driver’s behaviour and is conducive to the improvement of drivers’ self-management in behavior and awareness, facilitating urban traffic problems solving. This study uses driving behavior data constructing and predicting a general classification system to divide “safetyecological” (The abbreviation below is “SAF-ECO”) levels. It divides “SAF-ECO” levels in terms of ecology and security. The study provides scientific support for changes of the “SAF-ECO” level in the teaching process of driving school. Besides, it ensures traffic safety and improves the ecological environment.
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Chang Liu, Xing Kai Meng, Chu na Wu, Xue ran Wang, Wen hui Luo, and Hong wen Xia "Driving behavior classification and prediction method based on multiple logistic regression model", Proc. SPIE 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 120585R (22 December 2021); https://doi.org/10.1117/12.2619757
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KEYWORDS
Safety
Ecology
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