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Development of Smart Shift and Drive Control System Based on the Personal Driving Style Adaptation
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 5, 2016 by SAE International in United States
Annotation ability available
In general, driving performance is developed to meet preference of average customers. But there is no single standardized guideline which can satisfy various driving tastes of all drivers whose gender, cultural background, and age are different. To resolve this issue, automotive companies have introduced drive mode buttons which drivers can manually select from Normal, Eco, and Sport driving modes. Although this multi-mode manual systems is more efficient than single-mode system, it is in a transient state where drivers need to go through troubles of frequently selecting their preferred drive mode in volatile driving situations It is also doubtful whether the three-categorized driving mode can meet complex needs of drivers.. In order to settle these matters, it is necessary to analyze individual driving style automatically and to provide customized driving performance service in real time. In this paper, we adopted fuzzy algorithm to evaluate user’s short- and long-term driving tendency by analyzing various vehicle signals. We also came with a result of developing a smart shift and drive control system capable of changing power train and chassis control based on personal driving style and road condition to provide drivers with optimal driving performance and experiences.
CitationJeon, B., Kim, S., Jeong, D., and Chang, J., "Development of Smart Shift and Drive Control System Based on the Personal Driving Style Adaptation," SAE Technical Paper 2016-01-1112, 2016, https://doi.org/10.4271/2016-01-1112.
- MacAdam, C., Bareket, Z., Fancher, P., & Ervin R.., “Using Neural Networks to Identify Driving Style and Headway Control Behavior of Drivers,” Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility, 29:S1, pp. 143-160.
- Miller, G. A., “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information,” Psychological Review, 63, pp. 81-97.
- Jeon, B. and Kim, S., "Measurement and Modeling of Perceived Gear Shift Quality for Automatic Transmission Vehicles," SAE Int. J. Passeng. Cars - Mech. Syst. 7(1):423-433, 2014, doi:10.4271/2014-01-9125.
- Ulleberg, P. & Rundmo, T., “Personality, attitudes and risk perception as predictors of risky driving behavior among young drivers,” Safety Science, Vol. 41, pp 427-443.
- Lajunen, T. & Summala, H., “Driving experience, personality, and skill and safety-motive dimensions in driver’s self-assessments,” Person Individual Differences, Vol. 19 (3), 307-318.
- Reason, J., Manstead, A., Stradling, S., Baxter, J., & Campbell, K., “Errors and violations on the roads: A real distinction?” Ergonomics, Vol. 33 (10/11), pp. 1315-1332.
- Faber, V., “Clustering and the Continuous k-means Algorithm,” Los Alamo Science, Vol. 22, pp 138-144.