Abstract

This paper presents a real time traffic control system strategy by applying Wavelet Neural Networks (WNN) transform signal processing for wireless communication technologies of future high speed railways performance in Bangkok, Thailand with intelligent transportation systems. Innovations to address challenges emanating from railway transportation traffic system congestion. For Improving economies create more railways owners resulting in increased automobile manufacturing. Commuting time negatively impacts working hours. The economy will take a beating creating a vicious ecology cycle. But also a fast transportation alternative to air travel or regular passenger rail services. Providing these benefits would not be possible without the tremendous growth and prevalence for using wireless communication technologies. The wavelet transform has been successfully applied in many signal processing. The technique is based by using the absolute sum value of coefficients in multi resolution signal decomposition based on the discrete wavelet transform signal for data driven intelligent transportation systems. This survey provides an overview of the current state-of-the-art and future trends for wireless technologies aiming to realize the concept of High Speed Railway (HSR) communication services [1]. Our goal is to highlight the challenges for these technologies, including GSM-R, Wi-Fi, WIMAX, LTE-R, RoF, LCX & Cognitive Radio, the offered solutions, their performance, and other related issues. This paper studies these models to infer that with traffic railways signal control systems are supported. Simulation results of control system provided traffic information for course correction. It is proposed to integrate traffic system data with the traffic signal. However, with the advances in communication systems, such as LTE, 4G and cognitive radios, it is becoming possible for system designers to offer rich services to passengers while also providing support for enhanced train control operations such as positive train control.

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