Reduction of computational cost in driving simulation subsystems using approximation techniques

Driving simulators are practical simulation tools in studying vehicle behavior and driver reaction in a safe and controllable condition. The development of a real time driving simulator evolves into complex highly integrated and interdependent systems that require vast amount of computer memory and...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Mohd. Taib, Jamaludin, Abdul Jalil, Mohamad Kasim, Fouladinejad, Nariman
التنسيق: مقال
منشور في: Institute of Electrical and Electronics Engineers Inc. 2014
الموضوعات:
الوصول للمادة أونلاين:http://eprints.utm.my/id/eprint/62420/
http://dx.doi.org/10.1109/IAICT.2014.6922100
الوسوم: إضافة وسم
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المؤسسة: Universiti Teknologi Malaysia
الوصف
الملخص:Driving simulators are practical simulation tools in studying vehicle behavior and driver reaction in a safe and controllable condition. The development of a real time driving simulator evolves into complex highly integrated and interdependent systems that require vast amount of computer memory and computational time. This paper provides a study of employing approximation techniques in optimizing the computationally expensive simulation systems. Using the approximation techniques, a surrogate model can be constructed and used in the lieu of original codes. It can obviate the computational cost of highly integrated systems. A variety of approximation techniques can be used to simplify multidisciplinary simulations. In this paper, some well-known approximation techniques were reviewed including design of experiments, polynomial response surfaces, Kriging models and neural networks. A thorough review and study of various types of approximation techniques were made to construct efficient surrogate models for simulation subsystems. A surrogate assisted driving simulator (SADS) framework is then proposed that can significantly reduce the computational burden and achieve reasonable accuracy.