Search Results - "IEEE transactions on intelligent transportation systems"

Deep Reinforcement Learning for Autonomous Driving: A Survey by Kiran, B Ravi, Sobh, Ibrahim, Talpaert, Victor, Mannion, Patrick, Sallab, Ahmad A. Al, Yogamani, Senthil, Perez, Patrick

“…With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of…”
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T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction by Zhao, Ling, Song, Yujiao, Zhang, Chao, Liu, Yu, Wang, Pu, Lin, Tao, Deng, Min, Li, Haifeng

“…Accurate and real-time traffic forecasting plays an important role in the intelligent traffic system and is of great significance for urban traffic planning,…”
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Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges by Feng, Di, Haase-Schutz, Christian, Rosenbaum, Lars, Hertlein, Heinz, Glaser, Claudius, Timm, Fabian, Wiesbeck, Werner, Dietmayer, Klaus

“…Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous…”
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Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting by Cui, Zhiyong, Henrickson, Kristian, Ke, Ruimin, Wang, Yinhai

“…Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due to the time-varying traffic patterns and the complicated…”
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Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles by Aradi, Szilard

“…Academic research in the field of autonomous vehicles has reached high popularity in recent years related to several topics as sensor technologies, V2X…”
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Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control by Chu, Tianshu, Wang, Jie, Codeca, Lara, Li, Zhaojian

“…Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural…”
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Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions by Muhammad, Khan, Ullah, Amin, Lloret, Jaime, Ser, Javier Del, de Albuquerque, Victor Hugo C.

“…Advances in information and signal processing technologies have a significant impact on autonomous driving (AD), improving driving safety while minimizing the…”
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Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection by Yang, Fan, Zhang, Lei, Yu, Sijia, Prokhorov, Danil, Mei, Xue, Ling, Haibin

“…Pavement crack detection is a critical task for insuring road safety. Manual crack detection is extremely time-consuming. Therefore, an automatic road crack…”
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A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction by Zheng, Haifeng, Lin, Feng, Feng, Xinxin, Chen, Youjia

“…Accurate short-time traffic flow prediction has gained gradually increasing importance for traffic plan and management with the deployment of intelligent…”
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A Review of Motion Planning for Highway Autonomous Driving by Claussmann, Laurene, Revilloud, Marc, Gruyer, Dominique, Glaser, Sebastien

“…Self-driving vehicles will soon be a reality, as main automotive companies have announced that they will sell their driving automation modes in the 2020s. This…”
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Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications: A Review by Mozaffari, Sajjad, Al-Jarrah, Omar Y., Dianati, Mehrdad, Jennings, Paul, Mouzakitis, Alexandros

“…Behaviour prediction function of an autonomous vehicle predicts the future states of the nearby vehicles based on the current and past observations of the…”
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Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives by Chen, Hongtian, Jiang, Bin, Ding, Steven X., Huang, Biao

“…Recently, to ensure the reliability and safety of high-speed trains, detection and diagnosis of faults (FDD) in traction systems have become an active issue in…”
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Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review by Cui, Yaodong, Chen, Ren, Chu, Wenbo, Chen, Long, Tian, Daxin, Li, Ying, Cao, Dongpu

“…Autonomous vehicles were experiencing rapid development in the past few years. However, achieving full autonomy is not a trivial task, due to the nature of the…”
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A Survey on 3D Object Detection Methods for Autonomous Driving Applications by Arnold, Eduardo, Al-Jarrah, Omar Y., Dianati, Mehrdad, Fallah, Saber, Oxtoby, David, Mouzakitis, Alex

“…An autonomous vehicle (AV) requires an accurate perception of its surrounding environment to operate reliably. The perception system of an AV, which normally…”
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A Novel Gate Resource Allocation Method Using Improved PSO-Based QEA by Deng, Wu, Xu, Junjie, Zhao, Huimin, Song, Yingjie

“…With the continuous and rapid growth of air traffic demand, gate resource becomes a major bottleneck restricting airport development. Rational gate allocation…”
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Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey by Haydari, Ammar, Yilmaz, Yasin

“…Latest technological improvements increased the quality of transportation. New data-driven approaches bring out a new research direction for all control-based…”
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A Survey of Deep Learning Applications to Autonomous Vehicle Control by Kuutti, Sampo, Bowden, Richard, Jin, Yaochu, Barber, Phil, Fallah, Saber

“…Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex…”
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ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation by Romera, Eduardo, Alvarez, Jose M., Bergasa, Luis M., Arroyo, Roberto

“…Semantic segmentation is a challenging task that addresses most of the perception needs of intelligent vehicles (IVs) in an unified way. Deep neural networks…”
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Autonomous Vehicles That Interact With Pedestrians: A Survey of Theory and Practice by Rasouli, Amir, Tsotsos, John K.

“…One of the major challenges that autonomous cars are facing today is driving in urban environments. To make it a reality, autonomous vehicles require the…”
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Big Data Analytics in Intelligent Transportation Systems: A Survey by Zhu, Li, Yu, Fei Richard, Wang, Yige, Ning, Bin, Tang, Tao

“…Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent…”
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