Presentation
Using an improved rule match algorithm in an expert system to detect broken driving rules for an energy-efficiency and safety relevant driving system
Author/s | Yay, Emre
Martínez Madrid, Natividad |
Department | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Publication Date | 2014 |
Deposit Date | 2017-10-03 |
Published in |
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ISBN/ISSN | 1877-0509 |
Abstract | Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power
train. However, there are opportunities to increase energy-efficiency and safety by adapting the ... Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power train. However, there are opportunities to increase energy-efficiency and safety by adapting the individual driving behaviour in the given driving situation. In this paper, an improved rule match algorithm is introduced, which is used in the expert system of a human-centred driving system. The goal of the driving system is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. The improved rule match algorithm checks the incoming information against the driving rules to recognise any breakings of a driving rule. The needed information is obtained by monitoring the driver, the current driving situation as well as the car, using in-vehicle sensors and serial-bus systems. On the basis of the detected broken driving rules, the expert system will create individual recommendations in terms of energy-efficiency and safety, which will allow eliminating bad driving habits, while considering the driver needs. |
Citation | Yay, E. y Martínez Madrid, N. (2014). Using an improved rule match algorithm in an expert system to detect broken driving rules for an energy-efficiency and safety relevant driving system. En KES 2014: 18th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (127-136), Gdynia, Poland: Elsevier. |
Files | Size | Format | View | Description |
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Using an Improved.pdf | 522.8Kb | [PDF] | View/ | |
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