Title :
Reduction of computational cost in driving simulation subsystems using approximation techniques
Author :
Fouladinejad, Nariman ; Jalil, Mohamad Kasim Abdul ; Taib, Jamaludin Mohd
Author_Institution :
Fac. of Mech. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
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.
Keywords :
computational complexity; design of experiments; digital simulation; neural nets; traffic engineering computing; Kriging models; SADS framework; approximation techniques; computational cost reduction; design of experiments; driving simulation subsystems; highly integrated systems; neural networks; polynomial response surfaces; surrogate assisted driving simulator; surrogate model; Approximation methods; Computational modeling; Data models; Delays; Mathematical model; Vehicle dynamics; Vehicles; Design optimization; Driving simulation; Metamodeling; Surrogate modeling; Vehicle dynamic model; response surface approximation;
Conference_Titel :
Industrial Automation, Information and Communications Technology (IAICT), 2014 International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4799-4910-6
DOI :
10.1109/IAICT.2014.6922100