Jixiang Wang¹, Jing Wei², Siqi Chen¹, Haiyang Yu^1,3,4, Yilong Ren^1,3,4,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4167-4192, 2025, DOI:10.32604/cmc.2025.062503 - 19 May 2025

Abstract The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation. While existing vehicle-to-infrastructure coordination frameworks partially address congestion mitigation, they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles. To bridge this gap, this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol, explicitly balancing system-wide efficiency (measured by network throughput) with priority vehicle rights protection (quantified via time-sensitive utility functions). The approach innovatively combines (1) a multi-vehicle… More >

Zulqar Nain¹, B. Shahana², Shehzad Ashraf Chaudhry³, P. Viswanathan⁴, M.S. Mekala¹, Sung Won Kim^1,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5705-5721, 2023, DOI:10.32604/cmc.2023.033194 - 28 December 2022

Abstract Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System (CPS) applications. Edge devices enable limited computational capacity and energy availability that hamper end user performance. We designed a novel performance measurement index to gauge a device’s resource capacity. This examination addresses the offloading mechanism issues, where the end user (EU) offloads a part of its workload to a nearby edge server (ES). Sometimes, the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources (such as storage and… More >

Manar Ahmed Hamza^1,*, Masoud Alajmi², Jaber S. Alzahrani³, Siwar Ben Haj Hassine⁴, Abdelwahed Motwakel¹, Ishfaq Yaseen¹

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3465-3479, 2022, DOI:10.32604/cmc.2022.026066 - 29 March 2022

Abstract Recent advancements of the intelligent transportation system (ITS) provide an effective way of improving the overall efficiency of the energy management strategy (EMSs) for autonomous vehicles (AVs). The use of AVs possesses many advantages such as congestion control, accident prevention, and etc. However, energy management and traffic flow prediction (TFP) still remains a challenging problem in AVs. The complexity and uncertainties of driving situations adequately affect the outcome of the designed EMSs. In this view, this paper presents novel sustainable energy management with traffic flow prediction strategy (SEM-TPS) for AVs. The SEM-TPS technique applies type More >

Antonio Peña-García^1,*, Huchang Liao²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2373-2383, 2021, DOI:10.32604/cmc.2021.013151 - 28 December 2020

Abstract The requirements for automotive lighting systems, especially the light patterns ensuring driver perception, are based on criteria related to the headlamps, rather than the light perceived by drivers and road users. Consequently, important factors such as pavement reflectance, driver age, or time of night, are largely ignored. Other factors such as presence of other vehicles, vehicle speed and weather conditions are considered by the Adaptive Driving Beam (ADB) and Adaptive Front-lighting System (AFS) respectively, though with no information regarding the visual perception of drivers and other road users. Evidently, it is simpler to simulate and… More >