Jamaludin Mohd Taib

Development of a surrogate-based vehicle dynamic model to reduce computational delays in a driving simulator

The development of a real-time driving simulator involves highly complex integrated and interdependent subsystems that require a large amount of computational time. When advanced hardware is unavailable for economic reasons, achieving real-time simulation is challenging, and thus delays are inevitable. Moreover, computational delays in the response of driving simulator subsystems reduce the fidelity of the simulation. In this paper, we propose a technique to decrease computational delays in a driving simulator. We used approximation techniques, sensitivity analysis, decomposition, and sampling techniques to develop a surrogate-based vehicle dynamic model (SBVDM). This global surrogate model can be used in place of the conventional vehicle dynamic model to reduce the computational burden while maintaining an acceptable accuracy. Our results showed that the surrogate model can significantly reduce computing costs compared to the computationally expensive conventional model. In addition, the response time of the SBVDM is nearly five times faster than the original simulation codes. Also, as a method to reduce hardware cost, the SBVDM was used and the results showed that most of the responses were accurate and acceptable in relation to longitudinal and lateral dynamics. Based on the results, the authors suggested that the proposed framework could be useful for developing low-cost vehicle simulation systems that require fast computational output.

Modeling virtual driving environment for a driving simulator

This paper focuses on the development of a virtual driving environment for a real-time driving simulation (DS) to be integrated with other simulator components. The integration between database of driving environment and other driving simulation elements is useful for wide ranges of experiments and investigations related to vehicle simulation. To have a realistic driving simulator, virtual environment (VE) shall be constructed similar to the real world in a relevant framework using the applications of virtual reality (VR). In this research, the graphic quality and speed were optimized using different techniques in order to produce efficient realism and fidelity. The driving scenes were developed in a customized framework, which allow interaction of different computers in a distributed environment. A collaborative network system is required for high-speed connection between different parts of driving simulation in order to have real-time simulation.

Decomposition-Assisted Computational Technique Based on Surrogate Modeling for Real-Time Simulations

The development of complex simulation systems is extremely costly as it requires high computational capability and expensive hardware. As cost is one of the main issues in developing simulation components, achieving real-time simulation is challenging and it often leads to intensive computational burdens. Overcoming the computational burden in a multidisciplinary simulation system that has several subsystems is essential in producing inexpensive real-time simulation. In this paper, a surrogate-based computational framework was proposed to reduce the computational cost in a high-dimensional model while maintaining accurate simulation results. Several well-known metamodeling techniques were used in creating a global surrogate model. Decomposition approaches were also used to simplify the complexities of the system and to guide the surrogate modeling processes. In addition, a case study was provided to validate the proposed approach. A surrogate-based vehicle dynamic model (SBVDM) was developed to reduce computational delay in a real-time driving simulator. The results showed that the developed surrogate-based model was able to significantly reduce the computing costs, unlike the expensive computational model. The response time in surrogate-based simulation was considerably faster than the conventional model. Therefore, the proposed framework can be used in developing low-cost simulation systems while yielding high fidelity and fast computational output.

Applications of Cubic Motion Curve

Cubic motion is a curve that is generated by the integration of Cubic Spline and dynamic of motion. Cubic spline will draw the curve, whilst the dynamic of motion will position the vertices. This embedded motion attribute to the curve will have an advantage to study related to motion of vehicle. The objective of the paper is to demonstrate the advantage of motion attribute in the curve. It is demonstrated by two case studies. The case studies are simulation of traffic flow system and study of vehicle dynamic response.

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 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.