Article
Energy & Fuels
Depeng Kong, Gongquan Wang, Ping Ping, Jennifer Wen
Summary: Thermal runaway is a safety concern for lithium-ion batteries. This study develops a numerical model to predict the temperature, pressure evolution, and jet fire of the battery, considering the effect of state of charge (SOC).
Article
Engineering, Civil
Honghao Gao, Can Liu, Yuyu Yin, Yueshen Xu, Yu Li
Summary: This paper focuses on trust node management in VANETs, aiming to quantify node credibility to avoid malicious nodes. It introduces an integrated trust calculation method, combining direct and recommended trust, and ensures the weight of the latest information through a time sliding window and time decay function. Experimental results demonstrate the method outperforms baseline methods in packet delivery ratio and security.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Md Noor-A-Rahim, Zilong Liu, Haeyoung Lee, G. G. Md Nawaz Ali, Dirk Pesch, Pei Xiao
Summary: This paper presents a comprehensive survey on resource allocation schemes for vehicular networks, discussing the challenges and opportunities for resource allocations in modern vehicular networks, and outlining some promising future research directions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Energy & Fuels
Nan Piao, Xuning Gao, Huicong Yang, Zhenqiang Guo, Guangjian Hu, Hui-Ming Cheng, Feng Li
Summary: In low-temperature environments, lithium-ion batteries face various challenges and limitations, which need to be addressed by increasing the inherent reactivity of the battery and improving the external reaction temperature to enhance reaction kinetics, as well as by implementing real-time temperature monitoring, optimizing charging protocols, and online lithium-plating monitoring for battery management. A systematic review of low-temperature LIBs is conducted to provide references for future research.
Article
Engineering, Civil
Ze Liu, Yingfeng Cai, Hai Wang, Long Chen, Hongbo Gao, Yunyi Jia, Yicheng Li
Summary: This study uses radar and camera information fusion sensing methods to improve the environmental perception of autonomous vehicles in severe weather, reducing the missed detection rate and providing accurate environmental perception information for the decision-making and control systems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Xiaoqiang Sun, F. Richard Yu, Peng Zhang
Summary: Connected and autonomous vehicles (CAVs) have the potential to enhance transportation safety, mobility choices, user cost reduction, and job creation, but they also face increasing cyber-security threats. This paper provides a comprehensive survey on cyber-security in the environment of CAVs, categorizing risks and vulnerabilities, proposing defense strategies, summarizing safety standards, and discussing future challenges and open problems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Zhenpo Wang, Xiaolin Ding, Lei Zhang
Summary: A full X-by-wire chassis coordinated control scheme is proposed in this paper by utilizing Direct Yaw-moment Control, Active Front Steering, Anti-Slip Regulation, and Active Roll Control. A vehicle state prediction module is established to generate reference vehicle states and a decentralized event-triggered discrete sliding mode control scheme is developed to track these references by coordinating the subsystems. The hardware-in-the-loop tests show that the proposed scheme can improve vehicle stability, handling performance, comfort, and rollover prevention.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Civil
Zhili Zhou, Xiaohua Dong, Zhetao Li, Keping Yu, Chun Ding, Yimin Yang
Summary: This study proposes a traffic accident detection method based on spatio-temporal feature encoding and a multilayer neural network. By encoding the temporal features of the video and clustering the video frames using a multilayer neural network, traffic accidents can be effectively detected from driving videos.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Zhihong Yao, Haoran Jiang, Yang Cheng, Yangsheng Jiang, Bin Ran
Summary: This paper proposes a two-level optimization method for the optimization and management of traffic conflict zones with connected automated vehicles (CAVs). It effectively improves traffic efficiency and reduces vehicle delays and fuel consumption.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Peter Arthurs, Lee Gillam, Paul Krause, Ning Wang, Kaushik Halder, Alexandros Mouzakitis
Summary: The advancements in smart connected vehicles and Intelligent Transportation Systems (ITS) rely on processing large amounts of sensor data. Cloud computing is effective for handling peak data periods, while edge cloud computing addresses latency and bandwidth constraints.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yingfeng Cai, Lei Dai, Hai Wang, Long Chen, Yicheng Li, Miguel Angel Sotelo, Zhixiong Li
Summary: The researchers proposed a deep learning model for predicting pedestrian motion trajectory from far shot first-person perspective video and achieved state-of-the-art results. The model includes four key innovations, such as a macroscopic prediction module, a relative motion transformation module, a circular training module, and a specific dataset, which enhanced prediction accuracy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Muhammad Zudhy Irawan, Prawira Fajarindra Belgiawan, Tri Basuki Joewono, Faza Fawzan Bastarianto, Muhamad Rizki, Anugrah Ilahi
Summary: The study found that descriptive norms, teleworking and e-learning, and attitudes toward COVID-19 have a positive impact on travel frequency and activity-travel behavior changes during the beginning of COVID-19 pandemic. Additionally, ICT experience influenced a decrease in travel frequency and ride-hailing use. While personal attributes did not significantly affect activity-travel behavior change, they directly influenced ICT use. People living outside of Java Island had a higher travel frequency during the beginning of COVID-19 pandemic.
Article
Engineering, Civil
Yuan Cao, Zixuan Zhang, Fanglin Cheng, Shuai Su
Summary: This paper proposes a trajectory optimization approach for high-speed trains aiming to reduce traction energy consumption and increase riding comfort. The approach can also achieve energy-saving effects by optimizing the operation time between stations. The optimization model considers factors such as discrete throttle settings, neutral zones, and sectionalized tunnel resistance. The model is then discretized and turned into a multi-step decision optimization problem. Simulation results with real-world data demonstrate the effectiveness of the proposed approach in saving energy and improving riding comfort.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Jianyu Chen, Shengbo Eben Li, Masayoshi Tomizuka
Summary: This article introduces an interpretable deep reinforcement learning method for end-to-end autonomous driving, which utilizes a sequential latent environment model for handling complex urban scenarios and significantly reducing the sample complexity of reinforcement learning. Comparative tests in a realistic driving simulator demonstrate that the method outperforms many baseline models including DQN, DDPG, TD3, and SAC in crowded urban environments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Wenting Wei, Ruying Yang, Huaxi Gu, Weike Zhao, Chen Chen, Shaohua Wan
Summary: Modern transportation faces challenges in safety, mobility, environment, and space limitations. Vehicular networks are seen as a promising solution to improve transportation satisfaction and convenience. This paper focuses on resource allocation in vehicular cloud computing, using an enhanced genetic algorithm to achieve better performance.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Chaolong Zhang, Shaishai Zhao, Yigang He
Summary: This paper proposes a hybrid approach to predict the future capacity and remaining useful life (RUL) of batteries by combining improved variational modal decomposition (VMD), particle filter (PF), and Gaussian process regression (GPR). Experimental results demonstrate that the proposed approach offers wide generality and reduced errors.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Civil
Xinyu Chen, Mengying Lei, Nicolas Saunier, Lijun Sun
Summary: This paper proposes a low-rank autoregressive tensor completion (LATC) framework by introducing temporal variation as a new regularization term, aiming to capture both global and local consistency in traffic data.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Lei Lin, Weizi Li, Huikun Bi, Lingqina Qin
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2022)
Article
Engineering, Civil
Kan Guo, Yongli Hu, Zhen Qian, Yanfeng Sun, Junbin Gao, Baocai Yin
Summary: Traffic forecasting is a challenging problem due to the complexity and non-stationary nature of traffic data. Graph Convolution Network (GCN) based methods have shown promising performance in this area. However, current methods lack the utilization of spatial and temporal properties in graph construction. This paper proposes a novel dynamic graph convolution network that adaptively constructs dynamic road network graphs for traffic forecasting, achieving better performance than state-of-the-art methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Review
Engineering, Civil
Sarang Thombre, Zheng Zhao, Henrik Ramm-Schmidt, Jose M. Vallet Garcia, Tuomo Malkamaki, Sergey Nikolskiy, Toni Hammarberg, Hiski Nuortie, M. Zahidul H. Bhuiyan, Simo Sarkka, Ville V. Lehtola
Summary: Autonomous ships, using perception systems and AI techniques, are expected to enhance safety and efficiency in maritime navigation. This article introduces the operational requirements for autonomous vessels and discusses suitable sensors and AI techniques for their perception systems. The integration of four sensor families and sources of auxiliary data are explained. The perception tasks involve problems that can be solved using AI techniques such as deep learning and Gaussian processes.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
