In response to the escalating transportation demand in urban areas due to population growth and urbanization, the development and efficient operation of urban rail transit systems have become crucial. This study propo...
详细信息
ISBN:
(纸本)9798350373301;9798350373295
In response to the escalating transportation demand in urban areas due to population growth and urbanization, the development and efficient operation of urban rail transit systems have become crucial. This study proposes an innovative approach for intelligent passenger coordination and management in urban rail transit systems by utilizing advanced network information analysis techniques. Through comprehensive evaluation and analysis of the urban rail transit network, this research aims to optimize operational efficiency and improve service quality. By integrating cutting-edge technologies and analytical methods, the proposed methodology addresses existing challenges and improves the overall performance of urban rail transit systems. The study includes a thorough review of related work in intelligent transportation systems, followed by a detailed description of the proposed methodology, focusing on the technical foundations of rail transit networks and intelligent passenger coordination strategies. In addition, the study presents simulation results that demonstrate the effectiveness of the proposed approach in optimizing passenger flow management and improving the travel experience for urban residents.
The highly sophisticated visual perception of experts provides inspection functionality for target objects such as engineering products, agricultural crops, affected areas in medical fields, constructions, and many ot...
详细信息
Recent advancements in artificial intelligence have led to significant results in various domains, including image classification, natural language processing, and mastering complex games. However, current deep neural...
详细信息
ISBN:
(纸本)9798350364309;9798350364293
Recent advancements in artificial intelligence have led to significant results in various domains, including image classification, natural language processing, and mastering complex games. However, current deep neural networks seem to process information differently from humans. Neuro-symbolic methods may offer a promising solution to address this concern. This paper proposes a preliminary cognitive architecture focused on neural cell assemblies, which can combine the adaptability of neural approaches with the explicit reasoning capabilities of symbolic systems. It presents a case study on learning to count, and highlights mechanisms for learning, generalization, and adaptation based on predictive errors.
Contemporarily, in light of the intelligent transportation systems (ITS) sector, the tendency can be observed that the solution of the multi-objective cyber-physical optimization problems with imperfect information ta...
详细信息
ISBN:
(纸本)9798350363074;9798350363081
Contemporarily, in light of the intelligent transportation systems (ITS) sector, the tendency can be observed that the solution of the multi-objective cyber-physical optimization problems with imperfect information takes an increasingly weighted role. In the present scientific work, the authors want to take these developments into account by introducing an innovative cyber-physical architectural design and corresponding the two-stage heuristic computing approach. It is utilized in synergy with the MCSA1 and DCEx architectural principles for the workflow scheduling of Monte-Carlo simulation, which is based on the intelligent and sustainable route-order dispatching process model. Factors such as emissions, transport costs, risks, and the individual weighting of orders are reflected in the model. In particular, the authors define a stochastic ILP-based2 monte-carlo workflow model. They further propose two-stage scheduling heuristic with d-HEFT DAG relaxation as first stage and apply state-of-the-art techniques as a part of SCIP framework to solve 2nd 1-0 ILP-based stage;evaluate the performance of the scheduling approach. The authors obtain preliminary results of the second stage behavior using a realistic heterogeneous computing scenario and corresponding constraint structures within MACS simulator engine3. The results from the experiments illustrate moderate complexity of the approach. Scalability of the model looks promising for the applicability in various industry-related scenarios and corresponding computing environments.
In the 6G era, addressing charging challenges for electric vehicles is paramount. This paper focuses on mitigating concerns for both Connected Autonomous Electric Vehicles (CAEVs) and Unmanned Aerial Vehicles (UAVs). ...
详细信息
ISBN:
(纸本)9798350361261;9798350361278
In the 6G era, addressing charging challenges for electric vehicles is paramount. This paper focuses on mitigating concerns for both Connected Autonomous Electric Vehicles (CAEVs) and Unmanned Aerial Vehicles (UAVs). CAEV users face range anxiety, while UAV operators contend with limited battery sizes. The paper introduces a dynamic wireless charging (DWC) reservation and trip planning system, powered by 6G, vital for future smart cities. It provides a literature review on CAEV and UAV charge scheduling, proposing a novel system design tailored for 6G-enabled intelligent Transportation systems (ITS), where UAVs serve CAEVs. Notably, for vehicle-to-vehicle DWC and communication, laser technology is utilized, ensuring reliability and efficiency. A dynamic arrival handling protocol addresses unpredictable vehicle arrivals. Simulation results showcase the system's efficiency, optimizing charging and reducing wait times. With the impending 6G era, the paper aims to advance charging infrastructure for intelligent, flexible, and harmonized electric vehicle charging operations.
Automatic facial expression recognition is one of the most important issues in computer vision and it has its use in areas such as HCI and emotion-based systems. For facial expression recognition, this paper presented...
详细信息
In this paper, we propose a novel federated learning (FL)-enhanced quality of service (QoS) multicast routing, called FLQMR protocol, in IoT-enabled mobile ad-hoc networks (MANETs) with cell-free massive multiple inpu...
详细信息
ISBN:
(纸本)9798350379068;9798350379051
In this paper, we propose a novel federated learning (FL)-enhanced quality of service (QoS) multicast routing, called FLQMR protocol, in IoT-enabled mobile ad-hoc networks (MANETs) with cell-free massive multiple input multiple output (CF-mMIMO). The main contributions of this paper can be summarized as follows. First, we consider the integration of cross-layer design, reconfigurable intelligent surfaces (RIS), FL, and edge computing to enhance network performance. Second, we design the FL framework to optimize routing decisions by selecting the best paths from the source node to multiple destinations. Third, we employ a cross-layer design that combines the physical layer information (i.e., mobility, position, SE) with the network layer information (i.e., route information) to establish a stable multicast tree from the source node to multiple destinations. The simulation results show that the proposed FLQMR protocol achieves a high packet delivery ratio, low routing delay, and low control overhead.
In this paper, we present an approach based on Attribute Based Access control (ABAC) and Risk Adaptive Access control (RAdAC) to improve the reliability of the risk assessment and authorization process. The model has ...
详细信息
This paper presents a stochastic/robust nonlinear model predictive control (NMPC) to enhance the robustness of model-based legged locomotion against contact uncertainties. We integrate the contact uncertainties into t...
详细信息
ISBN:
(纸本)9798350377712;9798350377705
This paper presents a stochastic/robust nonlinear model predictive control (NMPC) to enhance the robustness of model-based legged locomotion against contact uncertainties. We integrate the contact uncertainties into the covariance propagation of stochastic/robust NMPC framework by leveraging the guard saltation matrix and an extended Kalman filter-like covariance update. We achieve fast stochastic/robust NMPC computation by utilizing the zero-order algorithm with additional improvements in computational efficiency concerning the feedback gains. We conducted numerical experiments and demonstrate that the proposed method can accurately forecast future state covariance and generate trajectories that satisfies constraints even in the presence of the contact uncertainties. Hardware experiments on the perceptive locomotion of a wheeled-legged robot were also carried out, validating the feasibility of the proposed method in a real-world system with limited on-board computation.
Predicting traffic flow is important for improving safety and efficiency in IoV systems. Techniques such as traditional models, deep learning, hybrid approaches, graph-based methods, optimization, edge computing, and ...
详细信息
暂无评论