Commenced in January 2007
Paper Count: 30458
Cognition of Driving Context for Driving Assistance
Abstract:In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1315627Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 780
 Dice. (2017). Ontologies. Available: https://www.dice.com/skills/Ontologies.html
 R. Neches, R. Fikes, T. Finin, T. Gruber, R. Patil, T. Senator, et al. (1991) Enabling Technology for Knowledge Sharing. AI Magazine. 36-56.
 N. Guarino, "Formal ontology, conceptual analysis and knowledge representation," Human-Computer Studies, vol. 43, pp. 625-640, 1995.
 T. R. Gruber, "A Translation Approach to Portable Ontology Specifications," Knowledge Acquisition, vol. 5, pp. 199 - 220, 1993.
 A. Maalel, H. H. Mabrouk, L. Mejri, and H. H. B. Ghezela, "Development of an ontology to assist the modeling of accident scenario application on railroad transport," Journal of Computing, vol. 3, 2011.
 M. Charest and S. Delisle, "Ontology-Guided Intelligent Data Mining Assistance: Combining Declarative and Procedural Knowledge," presented at the IASTED International Conference, 2006.
 S. Kannan, A. Thangavelu, and R. Kalivaradhan, "An Intelligent Driver Assistance System (I-DAS) for Vehicle Safety Modeling Using Ontology Approach," International Journal of Ubiquitous Computing, vol. 1, pp. 15 – 29, 2010.
 Protégé. (2016). Protégé: Open-source ontology editor. Available: http://protege.stanford.edu
 VOWL. Visual Notation for OWL Ontologies. Available: http://vowl.visualdataweb.org/v2/
 H. Abraham, C. Lee, S. Brady, C. Fitzgerald, B. Mehler, B. Reimer, et al., "Autonomous Vehicles, Trust, and Driving Alternatives: A survey of consumer preferences," Massachussets Institute of Technology AgeLab, Cambridge, MA, USA, 2016.
 Foley & Lardner LLP, "2017 Connected Cars & Autonomous Vehicles Survey," 2017. Available: https://www.foley.com/files/uploads/2017-Connected-Cars-Survey-Report.pdf
 J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, "Internet of Things (IoT): A vision, architectural elements and future directions," Elsevier Future Generation Computer Systems, vol. 29, pp. 1645-1660, 2013.
 G. Brioschi, M. D. Hina, A. Soukane, A. Ramdane-Cherif, and M. Colombetti, "Computational intelligence on the cognition of driving context for a safe driving assistance system," International Journal of Software Science and Computational Intelligence, vol. 9, 2017.
 G. Brioschi, M. D. Hina, A. Soukane, A. Ramdane-Cherif, and M. Colombetti, "Techniques for Cognition of Driving Context for Safe Driving Application," presented at the ICCI*CC 2016, 15th IEEE International Conference on Cognitive Informatics and Cognitive Computing Stanford, CA, USA, 2016.
 P. Tchankue, J. Weeson, and D. Vogts, "Using machine learning to predict the driving context whist driving," in SAICSIT '13 South African Institute for Computer Scientists and Information Technologists Conference, East London, South Africa 2013.
 S. Ulbrich, T. Menzel, A. Reschka, F. Schuldt, and M. Maurer, "Defining and substantiating the terms scene, situation, and scenario for automated driving," presented at the ITSC 2015, IEEE International Conference on Intelligent Transportation Systems, Canary Islands, Spain, 2015.
 A. Armand, D. Filliat, and J. Ibañez-Guzman, "Ontology-Based Context Awareness for Driving Assistance Systems," presented at the IEEE Intelligent Vehicles Symposium, Dearborn, MI, USA, 2014.
 S. Fernandez, R. Hadfi, T. Ito, I. Marsa-Maestre, and J. R. Velasco, "Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network," Sensors, vol. 16, 2016.
 P. Morignot and F. Nashashibi, "An ontology-based approach to relax traffic regulation for autonomous vehicle assistance," presented at the AIA’13, 12th IASTED International Conference on Artificial Intelligence and Applications, Innsbruck, Austria.
 M. Boudra, M. D. Hina, A. Ramdane-Cherif, and C. Tadj, "Architecture and Ontological Modelling for Assisted Driving and Interaction," International Journal of Advanced Computer Research, vol. 5, 2015.
 Fraunhofer IAO. (2016). Human-Vehicle Interaction: From driver assistance system to automated driving. Available: http://www.iao.fraunhofer.de/lang-en/range-of-services/people-and-mobility/human-vehicle-interaction.html
 Z. Xiong, V. Dixit, and T. Waller, "The Developement of an Ontology for Driving Context Modelling and Reasoning," presented at the 19th IEEE International Conference on Intelligent Transportation Systems, Rio de Janiero, Brazil, 2016.
 S. Dourlens and A. Ramdane-Cherif, "Modeling and understanding environment using semantic agents," International Journal of Artificial Intelligence and Soft Computing, vol. 2, 2012.
 P. P. Daghan Lemi Acay, Liz Sonenberg, "Extrospection: Agents Reasoning about the Environment," presented at the 3rd International Conference on Intelligent Environments (IE'07), Germany, 2007.
 S. Dourlens and A. Ramdane-Cherif, "Semantic Modeling and Understanding of Environment Behaviors," presented at the IEEE Symposium Series on Computational Intelligence, Symposium on Intelligent Agents, Paris, France, 2011.
 C. Thierry. (2017). Project ASSIA Simulation. Available: https://www.youtube.com/watch?v=pH71u6a6HYc&feature=youtu.be
 Game Engine. (2016). Unity 3D. Available: https://unity3d.com/
 I. Horrocks, P. F. Patel-Schneider, H. Boley, S. Tabet, B. Grosof, and M. Dean. (2016). SWRL: A Semantic Web Rule Language Combining OWL and RuleML. Available: https://www.w3.org/Submission/SWRL/
 S. Julien and P. Maret, "Semantic Agent Model for SWRL Rule-based Agents," in International Conference on Agents and Artificial Intelligence (ICAART 2010), Valencia, Spain, pp. 244-248.
 E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur, and Y. Katz, "Pellet: A Practical OWL-DL Reasoner," Journal of Web Semantics, vol. 5, pp. 51 - 53, 2007.
 B. Motik, I. Horrocks, Z. Wu, A. Fokoue, C. Lutz, OWL 2 Web Ontology Language Profiles, 2nd edition, 2012.
 I. Witten, E. Frank, and M. Hall, Data Mining: Practical Machine Learning Tools and Techniques. Burlington, MA: Morgan Kaufmann, 2011.
 A. A. Ithape, "Artificial Intelligence and Machine Learning in ADAS," presented at the Vector India Conference 2017, Pune, India, 2017.
 P. Louridas and C. Ebert, "Machine Learning," IEEE Software, vol. 33, pp. 110-115, Sept.-Oct. 2016 2016.
 RapidMiner Inc., "How to Correctly Validate Machine Learning Models," 2017.
 A. Saxena. (2017, 27 September 2017). Machine Learning Algorithms in Autonomous Cars. Available: http://visteon.bg/2017/03/02/machine-learning-algorithms-autonomous-cars/
 Y. Hou, P. Edara, and C. Sun, "Modeling Mandatory Lane Changing Using Bayes Classifier and Decision Trees," IEEE Transactions on Intelligent Transportation Systems, vol. 15, pp. 647 - 655, 2014.
 M. F. Peschl and C. Stary, "The Role of Cognitive Modeling for User Interface Design Representations," Mind and Machines, vol. 8, pp. 203 - 236, 1998.
 T. Harada, K. Mori, A. Yoshizawa, and H. Iwasaki, "Designing a Car-Driver's Cognitive Process Model for Considering Degree of Distraction," International Journal of Software Science and Computational Intelligence, vol. 7, pp. 1-16, July-September 2015 2015.
 John. E. Kelly III, "Computing, cognition and the future of knowing: How humans and machines are forging a new age of understanding," 2015.
 L. Li, D. Wen, N.-N. Zheng, and L.-C. Shen, "Cognitive Cars: A New Frontier for ADAS Research," IEEE Transactions on Intelligent Transportation Systems, vol. 13, pp. 395 - 407, 2012.