Article
Transportation
Anna-Maria Feneri, Soora Rasouli, Harry J. P. Timmermans
Summary: Mobility-as-a-Service (MaaS) is a new innovative technological solution to sustainable transportation that offers convenience by integrating planning, booking, and payment functions in a single app. Research shows that MaaS has the potential to alter daily travel patterns.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Xiaolin Tang, Jiaxin Chen, Huayan Pu, Teng Liu, Amir Khajepour
Summary: This article proposes an energy management strategy based on deep reinforcement learning to optimize the fuel economy of hybrid electric vehicles. By learning gear-shifting strategies and controlling engine throttle opening, the proposed strategy successfully reduces fuel consumption and improves computational efficiency.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Engineering, Electrical & Electronic
Libing Jing, Weizhao Tang, Tao Wang, Tong Ben, Ronghai Qu
Summary: The magnetic field modulated variable speed permanent magnet (PM) brushless motor (MFMVS-PMBM) is a new power shunting device for hybrid electric vehicles (HEVs) that shows promising electromagnetic characteristics. This study optimized the key parameters of the motor and analyzed their impact on its performance. Experimental results demonstrate that the MFMVS-PMBM exhibits good electromagnetic characteristics.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Engineering, Civil
Pandi Vijayakumar, Maria Azees, Sergei A. Kozlov, Joel J. P. C. Rodrigues
Summary: The 6G technology enhances VANETs with high availability, high reliability, and occasionally high throughput, along with proposing efficient batch authentication and key exchange schemes to improve security and preserve message integrity. The proposed scheme is computationally more efficient than existing schemes, as shown in the performance analysis.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yongjun Ren, Fujian Zhu, Jin Wang, Pradip Kumar Sharma, Uttam Ghosh
Summary: This paper proposes a blockchain-based proxy voting and revocation scheme for decision feedback in the Internet of Vehicles, allowing the intelligent system to ignore the unevenness and heterogeneity in 6G technology. Blockchain technology notarizes the vote data of vehicles and outsources microservices, enabling anonymous voting based on decision-related node attributes. Smart contracts automatically expand the scalability of outsourced microservices, and the security proof of the proposed scheme ensures the security and consistency of outsourced microservices, significantly improving the efficiency of voting feedback according to simulation results.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yi Xiao, Felipe Codevilla, Akhil Gurram, Onay Urfalioglu, Antonio M. Lopez
Summary: A crucial component of an autonomous vehicle is the AI driver, and today there are different paradigms for its development. This paper focuses on end-to-end autonomous driving and analyzes whether combining multiple modalities can produce better AI drivers. The study shows that early fusion multimodality outperforms single modality.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Run Liu, Zhenzhe Qu, Guosheng Huang, Mianxiong Dong, Tian Wang, Shaobo Zhang, Anfeng Liu
Summary: This paper proposes a UAV path planning scheme for IoT networks based on reinforcement learning. The scheme plans hover points for the UAV by learning the historical location of CHs and maximizes the probability of meeting CHs. It also plans the shortest path to visit all hover points using the simulated annealing method. Additionally, an algorithm named CHSA-AEP is proposed to search for the location of CHs, allowing the UAV to respond to changes in CH positions. Our proposed scheme outperforms other methods in energy efficiency and time utilization ratio, as demonstrated by comparison with area coverage algorithms and a random algorithm.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Engineering, Civil
Eduardo Arnold, Mehrdad Dianati, Robert de Temple, Saber Fallah
Summary: This article investigates two schemes for cooperative 3D object detection - early fusion and late fusion, and evaluates their performance in complex driving scenarios. The results show that early fusion outperforms late fusion, demonstrating the advantages of cooperative perception over single-point sensing.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Ying Chen, Fengjun Zhao, Xin Chen, Yuan Wu
Summary: This paper focuses on a hybrid energy-powered multi-server MEC system with Cybertwin. Vehicles enabled by Cybertwin and edge servers send the current network status and unprocessed tasks to the macro base station to achieve better resource allocation. The efficient multi-vehicle task offloading algorithm optimizes the cost and guarantees the system performance.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Civil
Xinqiang Chen, Zichuang Wang, Qiaozhi Hua, Wen-Long Shang, Qiang Luo, Keping Yu
Summary: Automated container terminals are the future of the port industry, and accurate kinematic data is crucial for improving efficiency and safety. Analyzing vehicle trajectories and speeds from port surveillance videos can provide valuable information. This study proposes an ensemble framework that uses computer vision and AI techniques to extract vehicle speeds from port videos, helping participants in port traffic make more informed decisions. Experimental results show that the framework achieves accurate vehicle kinematic data in typical port traffic scenarios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang
Summary: Recent trend focuses on applying deep reinforcement learning to solve vehicle routing problem and address challenges in pairing and precedence relationships in pickup and delivery problem. Research utilizes novel neural network with heterogeneous attention mechanism to empower policy and automate node selection.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Jiwei Huang, Bofeng Lv, Yuan Wu, Ying Chen, Xuemin Shen
Summary: In this paper, a joint admission control and computation resource allocation scheme is proposed for MEC enabled SCN. The ACCRA algorithm is designed to achieve close-to-optimal system utility and strike a balance between utility and queue length.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Environmental Studies
Daniel J. Reck, Henry Martin, Kay W. Axhausen
Summary: The study found that trip distance, precipitation, and access distance are fundamental factors in micro-mobility mode choice. Additionally, personal e-scooters and e-bikes emit less CO2 than the transport modes they replace, while shared e-scooters and e-bikes emit more CO2 than the transport modes they replace.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Engineering, Civil
Honghao Gao, Wanqiu Huang, Tong Liu, Yuyu Yin, Youhuizi Li
Summary: In this study, a privacy-oriented task offloading method is proposed, which defines evaluation indicators and utilizes deep reinforcement learning to solve the optimal task offloading problem. The method achieves good results in reducing privacy loss, energy consumption, and time delays.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Shunpu Tang, Junjuan Xia, Lisheng Fan, Xianfu Lei, Wei Xu, Arumugam Nallanathan
Summary: This study proposes a novel dilated convolution based CSI feedback network, which effectively compresses feedback CSI dimension and achieves superior performance and reduced computational complexity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Civil
Zhiyu Huang, Jingda Wu, Chen Lv
Summary: This paper presents a driving model based on internal reward functions that mimics human decision-making mechanisms. The use of maximum entropy inverse reinforcement learning allows for the inference of reward function parameters from naturalistic human driving data. The results demonstrate that the learned reward functions effectively capture the preferences of different drivers and improve the accuracy of the modeling process.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Wanneng Shu, Ken Cai, Neal Naixue Xiong
Summary: This paper explores the use of GRU neural network for traffic flow prediction, introducing an improved Bi-GRU prediction model to demonstrate its effectiveness.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Guiyang Luo, Hui Zhang, Quan Yuan, Jinglin Li, Fei-Yue Wang
Summary: This paper proposes an embedded spatial-temporal network (ESTNet) for accurate spatial-temporal prediction. The ESTNet extracts static features from fine-grained road networks using multi-scale graph convolution networks, and dynamic features from real-time traffic using gated recurrent unit networks. It simultaneously models the spatial-temporal dependencies using a three-dimension convolution unit. Experimental results demonstrate the effectiveness and superiority of the ESTNet over existing techniques.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Qu Zhaowei, Li Haitao, Li Zhihui, Zhong Tao
Summary: This paper proposes a new hybrid deep learning network model, M-B-LSTM, for short-term traffic flow forecasting. The model learns and equalizes the distribution of traffic flow through an online self-learning network and employs deep bidirectional long short-term memory network and long short-term memory network to address uncertainty and overfitting problems. Experimental results demonstrate that the proposed model outperforms existing methods in solving uncertainty and overfitting problems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yi Han, Biyao Wang, Tian Guan, Di Tian, Guangfeng Yang, Wei Wei, Hongbo Tang, Joon Huang Chuah
Summary: This paper introduces an optimized lidar and camera sensor fusion method for road environment sensing of intelligent vehicles. The method achieves superior results in road boundary detection and lane line classification.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
