A New Vehicular Fog Computing Architecture for Cooperative Sensing of Autonomous Driving
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Fan Wu | Sun Mao | Supeng Leng | Xiaosha Chen | Hao Du | S. Leng | Fan Wu | Sun Mao | Hao Du | Xiaosha Chen
[1] Qiuping Li,et al. Enhancing the User Experience in Vehicular Edge Computing Networks: An Adaptive Resource Allocation Approach , 2019, IEEE Access.
[2] Shahid Mumtaz,et al. Social Big-Data-Based Content Dissemination in Internet of Vehicles , 2018, IEEE Transactions on Industrial Informatics.
[3] Yusheng Ji,et al. AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling , 2017, IEEE Transactions on Vehicular Technology.
[4] Blaise Agüera y Arcas,et al. Communication-Efficient Learning of Deep Networks from Decentralized Data , 2016, AISTATS.
[5] Yang Tao,et al. Power control algorithm of cognitive radio based on non-cooperative game theory , 2013, China Communications.
[6] Rajkumar Buyya,et al. Fog Computing: Helping the Internet of Things Realize Its Potential , 2016, Computer.
[7] Yan Zhang,et al. Deep Reinforcement Learning for Cooperative Content Caching in Vehicular Edge Computing and Networks , 2020, IEEE Internet of Things Journal.
[8] Depeng Jin,et al. Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures , 2016, IEEE Transactions on Vehicular Technology.
[9] Jing Ye,et al. RT3D: Real-Time 3-D Vehicle Detection in LiDAR Point Cloud for Autonomous Driving , 2018, IEEE Robotics and Automation Letters.
[10] Jianping Wu,et al. Correction to "Capturing Drivers' Lane Changing Behaviors on Operational Level by Data Driven Methods" , 2019, IEEE Access.
[11] Supeng Leng,et al. A Millimeter Wave-Based Sensor Data Broadcasting Scheme for Vehicular Communications , 2019, IEEE Access.
[12] Qiuping Li,et al. Computation offloading and resource allocation for mobile edge computing with multiple access points , 2019, IET Commun..
[13] Lei Liu,et al. Vehicular Edge Computing and Networking: A Survey , 2019, Mobile Networks and Applications.
[14] Ricardo Omar Chávez García,et al. Multiple Sensor Fusion and Classification for Moving Object Detection and Tracking , 2016, IEEE Transactions on Intelligent Transportation Systems.
[15] Lihua Yang,et al. Multiband Cooperation for 5G HetNets: A Promising Network Paradigm , 2019, IEEE Vehicular Technology Magazine.
[16] Jun Liang,et al. A Deep Learning Method for Lane Changing Situation Assessment and Decision Making , 2019, IEEE Access.
[17] Yu Xiao,et al. Fog Following Me: Latency and Quality Balanced Task Allocation in Vehicular Fog Computing , 2018, 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).
[18] Dong Seog Han,et al. Radar and Vision Sensor Fusion for Object Detection in Autonomous Vehicle Surroundings , 2018, 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN).
[19] Hani S. Mahmassani,et al. Modeling Lane-Changing Behavior in a Connected Environment: A Game Theory Approach , 2015 .
[20] Ke Zhang,et al. Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks , 2019, IEEE Transactions on Vehicular Technology.
[21] Joseph Walsh,et al. Sensor Technology in Autonomous Vehicles : A review , 2018, 2018 29th Irish Signals and Systems Conference (ISSC).
[22] Xing Xie,et al. FlierMeet: A Mobile Crowdsensing System for Cross-Space Public Information Reposting, Tagging, and Sharing , 2015, IEEE Transactions on Mobile Computing.
[23] Jonathan Rodriguez,et al. Robust Mobile Crowd Sensing: When Deep Learning Meets Edge Computing , 2018, IEEE Network.
[24] Avinash C. Kak,et al. A novel evidence accumulation framework for robust multi-camera person detection , 2008, 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras.
[25] Yang Yang,et al. Incentive Propagation Mechanism of Computation Offloading in Fog-enabled D2D Networks , 2018, 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP).
[26] Song Guo,et al. A Game Theoretic Approach to Parked Vehicle Assisted Content Delivery in Vehicular Ad Hoc Networks , 2017, IEEE Transactions on Vehicular Technology.
[27] Yu Xiao,et al. Vehicular fog computing: Vision and challenges , 2017, 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops).
[28] Pascal Fua,et al. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] Jie Zhang,et al. Computation Offloading for Multi-Access Mobile Edge Computing in Ultra-Dense Networks , 2018, IEEE Communications Magazine.
[30] Xiang Cheng,et al. Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper) , 2018, 2018 IEEE International Conference on Communication Systems (ICCS).
[31] Xuemin Shen,et al. Connected Vehicles: Solutions and Challenges , 2014, IEEE Internet of Things Journal.
[32] Supeng Leng,et al. Smart Network Slicing for Vehicular Fog-RANs , 2019, IEEE Transactions on Vehicular Technology.
[33] Hang-Bong Kang,et al. Fast Occupancy Grid Filtering Using Grid Cell Clusters From LIDAR and Stereo Vision Sensor Data , 2016, IEEE Sensors Journal.
[34] Xiang Zhang,et al. A Survey on Platoon-Based Vehicular Cyber-Physical Systems , 2016, IEEE Communications Surveys & Tutorials.
[35] Ke Zhang,et al. A machine-learning based time constrained resource allocation scheme for vehicular fog computing , 2019, China Communications.
[36] Abdellah El Abbous,et al. A modeling of GPS error distributions , 2017, 2017 European Navigation Conference (ENC).
[37] 关欣,et al. Power Allocation based on Genetic Simulated Annealing Algorithm in Cognitive Radio Networks , 2013 .