Arshiya S. Ansari^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2865-2892, 2024, DOI:10.32604/cmc.2024.045908 - 26 March 2024

Abstract Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look. Whereas vehicular ad hoc networks (VANETs), which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services, as they are an essential component of modern smart transportation systems. VANETs steganography has been suggested by many authors for secure, reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection. This paper aims to determine whether using steganography is… More >

Liang Liu, Guangda Xu^*, Yuan Zhao, Yi Lu, Yu Li, Jing Gao

Energy Engineering, Vol.121, No.2, pp. 377-404, 2024, DOI:10.32604/ee.2023.041311 - 25 January 2024

Abstract The couple between the power network and the transportation network (TN) is deepening gradually with the increasing penetration rate of electric vehicles (EV), which also poses a great challenge to the traditional voltage control scheme. In this paper, we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV. In the first stage, the action of on-load tap changer and capacitor banks, etc., are determined by optimal power flow calculation, and the node electricity price is also determined based on dynamic time-of-use tariff mechanism. In the second stage, multiple… More >

A. Vikram¹, J. Akshya², Sultan Ahmad^3,4, L. Jerlin Rubini⁵, Seifedine Kadry^6,7,8, Jungeun Kim^9,*

Computer Systems Science and Engineering, Vol.48, No.1, pp. 115-130, 2024, DOI:10.32604/csse.2023.037928 - 26 January 2024

Abstract Traffic monitoring through remote sensing images (RSI) is considered an important research area in Intelligent Transportation Systems (ITSs). Vehicle counting systems must be simple enough to be implemented in real-time. With the fast expansion of road traffic, real-time vehicle counting becomes essential in constructing ITS. Compared with conventional technologies, the remote sensing-related technique for vehicle counting exhibits greater significance and considerable advantages in its flexibility, low cost, and high efficiency. But several techniques need help in balancing complexity and accuracy technique. Therefore, this article presents a deep learning-based vehicle detection and counting system for ITS More >

Othman S. Al-Heety^1,*, Zahriladha Zakaria^1,*, Ahmed Abu-Khadrah², Mahamod Ismail³, Sarmad Nozad Mahmood⁴, Mohammed Mudhafar Shakir⁵, Sameer Alani⁶, Hussein Alsariera¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2103-2127, 2024, DOI:10.32604/cmes.2023.029509 - 15 December 2023

Abstract Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision. In this article, these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data. The framework integrates Kalman filtering and Q-learning. Unlike smoothing Kalman filtering, our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error. Unlike traditional Q-learning, our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from… More >

Mohammed S. Alsaqer¹, Majid H. Alsulami^2,*, Rami N. Alkhawaji³, Abdulellah A. Alaboudi²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3943-3968, 2023, DOI:10.32604/cmc.2023.042379 - 26 December 2023

Abstract Blockchain technology has revolutionized conventional trade. The success of blockchain can be attributed to its distributed ledger characteristic, which secures every record inside the ledger using cryptography rules, making it more reliable, secure, and tamper-proof. This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context. Furthermore, it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure. To realize the full potential of the accurate and… More >

Fares Alharbi¹, Reem Alshahrani², Mohammed Zakariah^3,*, Amjad Aldweesh¹, Abdulrahman Abdullah Alghamdi¹

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3697-3722, 2023, DOI:10.32604/cmc.2023.040086 - 26 December 2023

Abstract Privacy and trust are significant issues in intelligent transportation systems (ITS). Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels, optical fiber, and blockchain technology. The Internet of Things (IoT) is a network of connected, interconnected gadgets. Privacy issues occasionally arise due to the amount of data generated. However, they have been primarily addressed by blockchain and smart contract technology. While there are still security issues with smart contracts, primarily due to the complexity of writing… More >

Dehai Zhang^*, Yu Ma, Qing Liu, Haoxing Wang, Anquan Ren, Jiashu Liang

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2901-2920, 2023, DOI:10.32604/cmc.2023.038264 - 08 October 2023

Abstract Traffic scene captioning technology automatically generates one or more sentences to describe the content of traffic scenes by analyzing the content of the input traffic scene images, ensuring road safety while providing an important decision-making function for sustainable transportation. In order to provide a comprehensive and reasonable description of complex traffic scenes, a traffic scene semantic captioning model with multi-stage feature enhancement is proposed in this paper. In general, the model follows an encoder-decoder structure. First, multi-level granularity visual features are used for feature enhancement during the encoding process, which enables the model to learn… More >

Difeng Zhu¹, Zhimou Zhu², Xuan Gong¹, Demao Ye¹, Chao Li^3,*, Jingjing Chen^4,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3083-3100, 2023, DOI:10.32604/iasc.2023.040517 - 11 September 2023

Abstract Traffic prediction is a necessary function in intelligent transportation systems to alleviate traffic congestion. Graph learning methods mainly focus on the spatiotemporal dimension, but ignore the nonlinear movement of traffic prediction and the high-order relationships among various kinds of road segments. There exist two issues: 1) deep integration of the spatiotemporal information and 2) global spatial dependencies for structural properties. To address these issues, we propose a nonlinear spatiotemporal optimization method, which introduces hypergraph convolution networks (HGCN). The method utilizes the higher-order spatial features of the road network captured by HGCN, and dynamically integrates them More >

Ayman Khallel Al-Ani^1,*, Shams Ul Arfeen Laghari², Hariprasath Manoharan³, Shitharth Selvarajan⁴, Mueen Uddin⁵

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2261-2279, 2023, DOI:10.32604/cmc.2023.038534 - 30 August 2023

Abstract In this paper, the application of transportation systems in real-time traffic conditions is evaluated with data handling representations. The proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the system. Compared to the existing approach, the design model in the proposed method is made by dividing the computing areas into several cluster regions, thereby reducing the complex monitoring system where control errors are minimized. Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to More >

Weixin Jiang^1,*, Qing Yuan², Zongze Li³, Junhua Gong³, Bo Yu⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.08861

Abstract The hydraulic and thermal simulation of crude oil pipeline transportation is greatly significant for the safe transportation and accurate regulation of pipelines. With reasonable basic parameters, the solution of the traditional partial differential equation (PDE) for the axial soil temperature field on the pipeline can obtain accurate simulation results, yet it brings about a low calculation efficiency problem. In order to overcome the low-efficiency problem, an efficient and robust hybrid solution model for soil temperature field coupling with Bayesian neural network and PDE is proposed, which considers the dynamic changes of boundary conditions. Four models,… More >