Rihem Farkh¹, Ghislain Oudinet², Alaeddine Moussa³, Yasser Fouad^4,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086607 - 15 September 2026

Abstract Autonomous driving systems must reason not only about the current scene but also about how the environment may evolve under alternative actions. Although predictive world models can generate future latent rollouts, these rollouts are often consumed directly by planners or explanation modules without an explicit and auditable interpretation stage. This paper presents a predictive and explainable driving framework centered on a Future Interpretation Module (FIM), which transforms action-conditioned future rollouts into structured descriptors, including risk trend, peak risk, time-to-critical, minimum clearance, predicted collision, dominant predicted event, and confidence. An aligned latent interface, trained with feature-alignment… More >

Mohammed Alonazi¹, Muhammad Adeel Ahmed Tahir², Adnan Ahmed Rafique², Maha Abdelhaq³, Raed Alsaqour⁴, Ahmad Jalal^5,6, Jeongmin Park^7,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086550 - 15 September 2026

Abstract Accurate vehicle detection, tracking, and counting are fundamental components of Intelligent Transportation Systems (ITS) and urban traffic surveillance. However, real-world deployment remains challenging due to domain shifts, illumination variations, occlusions, dense traffic conditions, and heterogeneous data distributions. Existing studies often address detection, tracking, and counting as independent tasks, resulting in limited cross-domain generalization and inconsistent performance in complex traffic environments. To overcome these limitations, this paper proposes a unified cross-domain framework that jointly integrates vehicle detection, tracking, and lane-aware counting within a single intelligent traffic analytics pipeline. The proposed framework begins with image enhancement using… More >

Shengxuan Dong, Xiongwei Li^*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086535 - 15 September 2026

Abstract To address the conflict between navigation performance and safety constraints in safe reinforcement learning, this paper proposes Dual Stream-Analytic Hierarchy Process-Safe Soft Actor (DS-AHP-SAC), a safe soft actor-critic algorithm based on a dual-stream Q-network and dynamic Analytic Hierarchy Process (AHP) stratified experience replay. The algorithm achieves a balance between reward maximization and constraint satisfaction through three synergistic designs: (1) decoupling the Q-network into independent navigation and safety value streams to eliminate gradient interference at the Critic level and mitigate gradient competition at the Actor level; (2) constructing a three-criterion dynamic sampling strategy based on AHP, More >

Shigan Ding^1,2, Zihe Qin^1,3,*, Feng Zhang^1,3, Mao Zheng², Bowen Lin²

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086097 - 15 September 2026

Abstract To address the challenge of precise station-keeping for underactuated unmanned surface vehicles (USVs) in unknown current environments, our team previously proposed a solution based on a “virtual anchoring” method. However, field tests revealed that the inherent “virtual anchor line” constraint limits positioning accuracy. This work introduces a novel control strategy to overcome the aforementioned issue, which enables accurate unmanned surface vehicle (USV) station-keeping by significantly reducing the distance constraint inherent to traditional virtual anchoring. The core innovation lies in a Dynamic Virtual Guide-Point, whose position is updated based on a real-time estimate of the current… More >

Baoping Tian, Zhuxiao Wang^*, Jiahao Xue, Hong Wang, Ying Zhang, Yun Ju

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.085661 - 15 September 2026

Abstract Deep reinforcement learning (DRL) has gained significant attention as an essential technology for constructing intelligent agents capable of handling high-dimensional visual observations in complex control environments. With the rapid development of knowledge transfer paradigms, reincarnating reinforcement learning (RRL) has emerged as a promising approach to accelerate policy convergence and alleviate the inefficiency of traditional tabula rasa training by reusing pre-trained teacher policies. However, existing RRL approaches primarily focus on improving knowledge transfer efficiency, while how student networks adaptively regulate and selectively utilize inherited representations during the teacher–student transition remains underexplored. As a result, student agents… More >

Chao He^1,*, Dongfeng Fu¹, Xin Xie², Jinkui Zhang³, Sirui Zhang⁴, Zheng Zhang⁵

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.085383 - 15 September 2026

Abstract With the rapid development of fifth generation (5G), 5G-Advanced, edge computing, and early sixth generation (6G) technologies, the Internet of Vehicles (IoV) is evolving toward highly connected, intelligent, and delay-sensitive transportation services. Nevertheless, ground infrastructure still faces coverage holes, blockage, overloaded roadside units (RSUs), limited backhaul, and weak service continuity in urban canyons, crowded intersections, long highway segments, rural roads, and emergency areas. Unmanned aerial vehicles (UAVs) can provide flexible aerial relay, mobile sensing, temporary coverage, and lightweight edge computing support for these scenarios. This survey reviews UAV-assisted IoV from an integrated sensing, communication, and… More >

Ao Nie¹, Wei Zhou¹, Yi Yu¹, Wan Xu^1,2,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.083871 - 15 September 2026

Abstract Currently, mobile robot path planning in unstructured forest environments remains a hot research topic in the robotics field. Studies applying the Greylag Goose Optimization (GGO) algorithm to multi-robot path planning under such scenarios are limited, and these approaches still face significant challenges, such as insufficient trajectory smoothness, frequent coordination conflicts, and relatively slow convergence to optimal solutions. To address these issues, this paper proposes an Evolutionary Game-Theoretic Improved GGO algorithm (EG-IGGO), designed to optimize path quality while ensuring robust obstacle avoidance capabilities. Specifically, two novel strategies—the population alignment strategy and the dual-source adaptive guidance strategy—are… More >

Lingtao Zhan¹, Jiale Zhu¹, Tingting Wang¹, Xiongbai Cao¹, Xiaoyu Hao^1,2, Cesare Grazioli³, Quanzheng Zhang¹, Huixia Yang¹, Teng Zhang^1,*, Yeliang Wang¹

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.083413 - 15 September 2026

Abstract Scanning tunneling microscopy (STM) images are frequently affected by low-frequency vibrations, substrate-induced background variations, and bias-dependent contrast changes, which degrade molecular feature responses and hinder reliable segmentation. To address this challenge, we develop an STM-oriented Feature Pyramid Network (FPN) + Dual-Path Intensity Calibration (DPIC) framework by adapting a DPIC module, originally derived from a cloud-noise calibration mechanism, to the specific characteristics of STM molecular images. In this framework, DPIC is reformulated as a noise-aware feature calibration module that suppresses low-response background interference while preserving foreground molecular contours. We integrated DPIC into the FPN architecture and… More >

Yuzhang Wang^1,2,*, Zhuning Liu¹, Haozhe Sun¹, Zhuo Li³, Kanru Cheng¹, Chaoran Yang¹

Frontiers in Heat and Mass Transfer, Vol.24, No.4, 2026, DOI:10.32604/fhmt.2026.084530 - 31 August 2026

Abstract During the operation of a gas turbine, the surface morphology of thermal barrier coatings (TBCs) of the high temperature blades inevitably evolves due to sintering, particle deposition or other factors, leading to an increase in surface roughness. This altered roughness can significantly influence the flow behavior of cooling films and the heat transfer performance of the coupled cooling film-TBC system. In this work, the flow behavior and conjugate heat transfer between cooling film and TBC under varying surface roughness conditions were investigated using the double distribution function lattice Boltzmann method (DDF-LBM) coupled with large eddy… More >

Guang Wen¹, Wenling Liao^1,2,*, Shuaimei Lian¹, Pingping Liu^1,*

Frontiers in Heat and Mass Transfer, Vol.24, No.4, 2026, DOI:10.32604/fhmt.2026.081270 - 31 August 2026

Abstract In this work, FLUENT is used to systematically investigate the effects of two key factors on the hydrothermal performance and entropy generation within a mass flow rate range of 0.3–1.1 g/s: (1) the coupling modes between grooves (simple and composite) and microchannels (straight, convergent, and divergent), and (2) the cross-sectional shape of composite grooves. Results show that, compared with simple grooves, composite grooves induce stronger spiral fluid disturbances between the mainstream and near-wall zones, enhancing direct fluid impingement on groove walls and thus improving the cooling effect on the microchannel. Among the configurations, the coupling More >