Vehicular_Edge_Computing

This project gathers academic resources related to vehicular edge computing (VEC), and we welcome issue submissions.

Table of Contents

White paper

Awesome resources

IoV policy

Survey

  • T. Gong, L. Zhu, F. R. Yu and T. Tang, "Edge Intelligence in Intelligent Transportation Systems: A Survey," in IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 9, pp. 8919-8944, Sept. 2023, doi: 10.1109/TITS.2023.3275741. [paper]
  • Y. Chiang et al., "Management and Orchestration of Edge Computing for IoT: A Comprehensive Survey," in IEEE Internet of Things Journal, vol. 10, no. 16, pp. 14307-14331, 15 Aug.15, 2023, doi: 10.1109/JIOT.2023.3245611. [paper]
  • Behravan, K., Farzaneh, N., Jahanshahi, M., & Seno, S. A. H. (2023). A Comprehensive Survey on Using Fog Computing in Vehicular Networks. Vehicular Communications, 100604. [paper]
  • D. Katare, D. Perino, J. Nurmi, M. Warnier, M. Janssen and A. Y. Ding, "A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services," in IEEE Communications Surveys & Tutorials, doi: 10.1109/COMST.2023.3302474. [paper]
  • Haochen Hua, Yutong Li, Tonghe Wang, Nanqing Dong, Wei Li, and Junwei Cao. 2023. Edge Computing with Artificial Intelligence: A Machine Learning Perspective. ACM Comput. Surv. 55, 9, Article 184 (September 2023), 35 pages. https://doi.org/10.1145/3555802. [paper]
  • Rodolfo Meneguette, Robson De Grande, Jo Ueyama, Geraldo P. Rocha Filho, and Edmundo Madeira. 2021. Vehicular Edge Computing: Architecture, Resource Management, Security, and Challenges. ACM Comput. Surv. 55, 1, Article 4 (January 2023), 46 pages. https://doi.org/10.1145/3485129 [paper]
  • E. Karimi, Y. Chen and B. Akbari, "Intelligent and Decentralized Resource Allocation in Vehicular Edge Computing Networks," in IEEE Internet of Things Magazine, vol. 6, no. 4, pp. 112-117, December 2023, doi: 10.1109/IOTM.001.2200268.[paper]
  • G. Yan, K. Liu, C. Liu and J. Zhang, "Edge Intelligence for Internet of Vehicles: A Survey," in IEEE Transactions on Consumer Electronics, doi: 10.1109/TCE.2024.3378509. [paper]
  • Fatemeh Golpayegani, Nanxi Chen, Nima Afraz, Eric Gyamfi, Abdollah Malekjafarian, Dominik Schäfer, and Christian Krupitzer. 2024. Adaptation in Edge Computing: A review on design principles and research challenges. ACM Trans. Auton. Adapt. Syst. Just Accepted (May 2024). [paper]
  • 雷凯茹,余冰雁. 面向车联网的MEC跨域协同技术研究[J]. 信息通信技术与政策,2024,50(3):18-26. DOI:10.12267/j.issn.2096-5931.2024.03.003. [paper]

Simulator

  • Wei, Z., Huang, C., Li, B., Zhao, Y., Cheng, X., Yang, L. and Zhang, R., 2024. AirFogSim: A Light-Weight and Modular Simulator for UAV-Integrated Vehicular Fog Computing. arXiv preprint arXiv:2409.02518. [paper],[code]
  • Wu, Fan, Xiaolong Xu, Muhammad Bilal, Xiangwei Wang, Hao Cheng, and Siyu Wu. "VEC-Sim: A Simulation Platform for Evaluating Service Caching and Computation Offloading Policies in Vehicular Edge Networks." arXiv preprint arXiv:2410.06934 (2024). [paper]

Task offloading and resource allocation

  • Y. Ju et al., "Joint Secure Offloading and Resource Allocation for Vehicular Edge Computing Network: A Multi-Agent Deep Reinforcement Learning Approach," in IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 5, pp. 5555-5569, May 2023, doi: 10.1109/TITS.2023.3242997. [paper]
  • W. Fan et al., "Joint Task Offloading and Resource Allocation for Vehicular Edge Computing Based on V2I and V2V Modes," in IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 4, pp. 4277-4292, April 2023, doi: 10.1109/TITS.2022.3230430. [paper]
  • Z. Nan, S. Zhou, Y. Jia and Z. Niu, "Joint Task Offloading and Resource Allocation for Vehicular Edge Computing With Result Feedback Delay," in IEEE Transactions on Wireless Communications, vol. 22, no. 10, pp. 6547-6561, Oct. 2023, doi: 10.1109/TWC.2023.3244391. [paper]
  • C. Tang, G. Yan, H. Wu and C. Zhu, "Computation Offloading and Resource Allocation in Failure-Aware Vehicular Edge Computing," in IEEE Transactions on Consumer Electronics, doi: 10.1109/TCE.2023.3342017.[paper]
  • X. Ye, K. Qu, W. Zhuang and X. Shen, "Accuracy-Aware Cooperative Sensing and Computing for Connected Autonomous Vehicles," in IEEE Transactions on Mobile Computing, doi: 10.1109/TMC.2023.3343709.[paper]
  • X. Fan, W. Gu, C. Long, C. Gu and S. He, "Optimizing Task Offloading and Resource Allocation in Vehicular Edge Computing Based on Heterogeneous Cellular Networks," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2023.3345364. [paper]
  • J. Zhang, Y. Wu, G. Min and K. Li, "Neural Network-Based Game Theory for Scalable Offloading in Vehicular Edge Computing: A Transfer Learning Approach," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2023.3348074. [paper]
  • W. Fan, Y. Zhang, G. Zhou and Y. Liu, "Deep Reinforcement Learning-Based Task Offloading for Vehicular Edge Computing With Flexible RSU-RSU Cooperation," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3349546. [paper]
  • Z. Lin, X. Chen, X. He, D. Tian, Q. Zhang and P. Chen, "Energy-Efficient Cooperative Task Offloading in NOMA-Enabled Vehicular Fog Computing," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2023.3349006. [paper]
  • L. Yin, J. Luo, C. Qiu, C. Wang and Y. Qiao, "Joint Task Offloading and Resources Allocation for Hybrid Vehicle Edge Computing Systems," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3351635. [paper]
  • H. Zhang, H. Liang, X. Hong, Y. Yao, B. Lin and D. Zhao, "DRL-Based Resource Allocation Game With Influence of Review Information for Vehicular Edge Computing Systems," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2024.3367657. [paper]
  • Li, Zhenyu, Yuchuan Fu, Mengqiu Tian, and Changle Li. "Cooperative Sensing, Communication and Computation Resource Allocation in Mobile Edge Computing-Enabled Vehicular Networks." Journal of Information and Intelligence (2024).[paper]
  • M. Huang, Z. Shen and G. Zhang, "Joint Spectrum Sharing and V2V/V2I Task Offloading for Vehicular Edge Computing Networks Based on Coalition Formation Game," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3371096. [paper]
  • C. Xu, G. Wang, M. Wei, P. Zhang and B. Peng, "Intelligent Transportation Vehicle Road Collaboration and Task Scheduling Based on Deep Learning in Augmented Internet of Things," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2024.3393940. [paper]
  • G. Ma et al., "Joint Partial Offloading and Resource Allocation for Vehicular Federated Learning Tasks," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3393529. [paper]
  • X. Wang et al., "Augmented Intelligence of Things for Priority-Aware Task Offloading in Vehicular Edge Computing," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3408157. [paper]
  • R. Xiong et al., "Reducing Power Consumption and Latency of Autonomous Vehicles With Efficient Task and Path Assignment in the V2X-MEC Based on Nash Equilibrium," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3430112. [paper]
  • Q. Luo, T. H. Luan, W. Shi and P. Fan, "Heterogeneous Task Oriented Data Scheduling in Vehicular Edge Computing via Deep Reinforcement Learning," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2024.3444815. [paper]
  • Y. Zhao et al., "Joint Content Caching, Service Placement and Task Offloading in UAV-Enabled Mobile Edge Computing Networks," in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2024.3460049. [paper]
  • H. Wang, D. Wang, Y. He, Q. Xu, X. Yang and F. Zhou, "A V2X-Enabled Framework for Delay-Sensitive Task Offloading in LAPS-Aided Internet of Vehicles," 2024 IEEE/CIC International Conference on Communications in China (ICCC), Hangzhou, China, 2024, pp. 485-490, doi: 10.1109/ICCC62479.2024.10681683. [paper]
  • J. Wu, M. Tang, C. Jiang, L. Gao and B. Cao, "Cloud-Edge-End Collaborative Task Offloading in Vehicular Edge Networks: A Multi-Layer Deep Reinforcement Learning Approach," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3472472. [paper]
  • J. Yang et al., "Service-Aware Computation Offloading for Parallel Tasks in VEC Networks," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3476476. [paper]
  • H. Wu, A. Gu and Y. Liang, "Federated Reinforcement Learning-Empowered Task Offloading for Large Models in Vehicular Edge Computing," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2024.3481876. [paper]
  • W. Zhao, C. Wu, R. Zhong, K. Shi and X. Xu, "Edge Computing and Caching Optimization Based on PPO for Task Offloading in RSU-Assisted IoV," 2023 IEEE 9th World Forum on Internet of Things (WF-IoT), Aveiro, Portugal, 2023, pp. 01-06, doi: 10.1109/WF-IoT58464.2023.10539436. [paper],[code]

DAG

  • X. He, S. Pang, H. Gui, K. Zhang, N. Wang and S. Yu, "Online Offloading and Mobility Awareness of DAG Tasks for Vehicle Edge Computing," in IEEE Transactions on Network and Service Management, doi: 10.1109/TNSM.2024.3470777. [paper]

Digital twin

  • **电子信息产业发展研究院:数字孪生白皮书(2019年)[paper]

  • A. Paul, K. Singh, C. -P. Li, O. A. Dobre and T. Q. Duong, "Digital Twin-Aided Vehicular Edge Network: A Large-Scale Model Optimization by Quantum-DRL," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2024.3410897. [paper]

  • S. Bounaira, A. Alioua and I. Souici, "Trust-Based Secure Task Offloading in Digital Twin Empowered Vehicular Edge Computing," 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS), EL OUED, Algeria, 2024, pp. 1-8, doi: 10.1109/PAIS62114.2024.10541161.(https://ieeexplore.ieee.org/abstract/document/10541161)

  • X. Tan, M. Wang, T. Wang, Q. Zheng, J. Wu and J. Yang, "Adaptive Task Scheduling in Digital Twin Empowered Cloud-Native Vehicular Networks," in IEEE Transactions on Vehicular Technology, vol. 73, no. 6, pp. 8973-8987, June 2024, doi: 10.1109/TVT.2024.3362841. [paper]

  • K. Wang et al., "Smart Mobility Digital Twin Based Automated Vehicle Navigation System: A Proof of Concept," in IEEE Transactions on Intelligent Vehicles, vol. 9, no. 3, pp. 4348-4361, March 2024, doi: 10.1109/TIV.2024.3368109. [paper]

  • Y. Zhang, W. Liang, Z. Xu and X. Jia, "Mobility-Aware Service Provisioning in Edge Computing via Digital Twin Replica Placements," in IEEE Transactions on Mobile Computing, doi: 10.1109/TMC.2024.3394839. [paper]

  • L. Tang, Z. Cheng, J. Dai, H. Zhang and Q. Chen, "Joint Optimization of Vehicular Sensing and Vehicle Digital Twins Deployment for DT-Assisted IoVs," in IEEE Transactions on Vehicular Technology, vol. 73, no. 8, pp. 11834-11847, Aug. 2024, doi: 10.1109/TVT.2024.3373175. [paper]

  • G. Chen, W. Duan, J. Sun, Q. Zeng and Y. -D. Zhang, "Social-Aware Assisted Edge Collaborative Caching Based on Deep Reinforcement Learning Joint With Digital Twin Network in Internet of Vehicles," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3392596. [paper]

  • X. Yuan et al., "Efficient IoV Resource Management Through Enhanced Clustering, Matching and Offloading in DT-Enabled Edge Computing," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3410176. [paper]

  • W. Fan, Y. Zhang, G. Zhou and Y. Liu, "Deep Reinforcement Learning-Based Task Offloading for Vehicular Edge Computing With Flexible RSU-RSU Cooperation," in IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 7, pp. 7712-7725, July 2024, doi: 10.1109/TITS.2024.3349546. [paper]

  • X. Wang et al., "Augmented Intelligence of Things for Priority-Aware Task Offloading in Vehicular Edge Computing," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3408157. [paper]

  • K. Sun et al., "Personalized Privacy-Preserving Distributed Artificial Intelligence for Digital-Twin-Driven Vehicle Road Cooperation," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3389656. [paper],[code]

  • A. Gupta, D. Diwani, V. A. Bohara and A. Srivastava, "QoS Aware Task Offloading for Digital-Twin Enabled Connected Vehicular Network," 2024 IEEE Wireless Communications and Networking Conference (WCNC), Dubai, United Arab Emirates, 2024, pp. 1-6 [paper],[code]

  • L. Zhao et al., "A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing," in IEEE Journal on Selected Areas in Communications, vol. 41, no. 11, pp. 3386-3400, Nov. 2023. [paper],[code]

  • Digital-twin Network Service Pre-migration Scheme for Vehicular Edge Computing : [code]

  • Zhu, Lin, Bingxian Li, and Long Tan. "A Digital Twin-based multi-objective optimized task offloading and scheduling scheme for vehicular edge networks." Future Generation Computer Systems (2024): 107517. [paper]

  • H. Kaur and M. Bhatia, "Digital Twin-Driven Performance Assessment for IoT-Integrated Autonomous Driving Systems," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3481501. [paper]

  • C. Xu, P. Zhang, X. Xia, L. Kong, P. Zeng and H. Yu, "Digital Twin-Assisted Intelligent Secure Task Offloading and Caching in Blockchain-Based Vehicular Edge Computing Networks," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3482870. [paper]

  • S. Ghannay and S. M. Gammar, "The Digital Twin in Vehicular Network: A Key to the Future of IoV ?," 2024 13th IFIP/IEEE International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN), Agadir, Morocco, 2024, pp. 1-6, doi: 10.23919/PEMWN62766.2024.10737568. [paper]

  • F. Mou et al., "Adaptive Digital Twin Migration in Vehicular Edge Computing and Networks," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2024.3492349. [paper]

Physical technology

  • V. Kumar, M. F. Hanif, M. Juntti and L. -N. Tran, "A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access," in IEEE Transactions on Vehicular Technology, vol. 72, no. 9, pp. 12332-12337, Sept. 2023, doi: 10.1109/TVT.2023.3263791. [paper],[code]

NOMA

  • Z. Wang, Y. Liu, X. Mu, Z. Ding and O. A. Dobre, "NOMA Empowered Integrated Sensing and Communication," in IEEE Communications Letters, vol. 26, no. 3, pp. 677-681, March 2022, doi: 10.1109/LCOMM.2022.3140271. [paper],[code],people:[Zhaolin Wang],[github]
  • Z. Wang, X. Mu, Y. Liu, X. Xu and P. Zhang, "NOMA-Aided Joint Communication, Sensing, and Multi-Tier Computing Systems," in IEEE Journal on Selected Areas in Communications, vol. 41, no. 3, pp. 574-588, March 2023, doi: 10.1109/JSAC.2022.3229447. [paper],[code]
  • Y. Mao, B. Clerckx and V. O. K. Li, "Rate-splitting multiple access for downlink communication systems: bridging, generalizing, and outperforming SDMA and NOMA," EURASIP Journal on Wireless Communications and Networking 2018.1 (2018): 133. [paper],[code],people:[Yijie (Lina) Mao]
  • QIN, Langtian (2023). Joint Transmission and Resource Optimization in NOMA-assisted IoVT with Mobile Edge Computing. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.22679962.v1 [paper],[code],people:[Langtian Qin],[github]
  • Z. Ding, D. Xu, R. Schober and H. V. Poor, "Hybrid NOMA Offloading in Multi-User MEC Networks," in IEEE Transactions on Wireless Communications, vol. 21, no. 7, pp. 5377-5391, July 2022, doi: 10.1109/TWC.2021.3139932. [paper],[code],people:[Zhiguo Ding]
  • V. Kumar, M. F. Hanif, M. Juntti and L. -N. Tran, "A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access," in IEEE Transactions on Vehicular Technology, vol. 72, no. 9, pp. 12332-12337, Sept. 2023, doi: 10.1109/TVT.2023.3263791. [paper],[code],[vkumar-ucd]
  • Xu, X., Liu, K., Dai, P., Jin, F., Ren, H., Zhan, C., & Guo, S. (2023). Joint task offloading and resource optimization in noma-based vehicular edge computing: A game-theoretic drl approach. Journal of Systems Architecture, 134, 102780. [paper],[code]
  • H. Zhu, Q. Wu, X. -J. Wu, Q. Fan, P. Fan and J. Wang, "Decentralized Power Allocation for MIMO-NOMA Vehicular Edge Computing Based on Deep Reinforcement Learning," in IEEE Internet of Things Journal, vol. 9, no. 14, pp. 12770-12782, 15 July15, 2022, doi: 10.1109/JIOT.2021.3138434. [paper],[code]
  • L. P. Qian, X. Dong, M. Wu, Y. Wu and L. Zhao, "Long-Term Energy Consumption Minimization in NOMA-Enabled Vehicular Edge Computing Networks," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3404991. [paper]

Application

  • G. Luo et al., "EdgeCooper: Network-Aware Cooperative LiDAR Perception for Enhanced Vehicular Awareness," in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2023.3322764. [paper]

Chinese

  • 郭欣宇. 基于深度学习的智能网联汽车的感知与通信相关技术研究[D]. 吉林:吉林大学,2023. [paper]
  • 杨春. 基于深度强化学习策略的车载计算任务卸载方法研究[D]. 天津:天津理工大学,2023. [paper]
  • 任琦琦. 车联网环境中计算卸载方案研究[D]. 陕西:西安电子科技大学,2022. [paper]
  • 许世琳. 车联网中基于深度强化学习的计算任务卸载策略研究[D].北京邮电大学,2022.DOI:10.26969/d.cnki.gbydu.2021.000141. [paper]
  • 郭欣宇. 基于深度学习的智能网联汽车的感知与通信相关技术研究[D]. 吉林:吉林大学,2023. [paper]
  • 王妍聪. 边缘计算与车联网融合的应用技术和算法研究[D]. 吉林:吉林大学,2023. [paper]
  • 宋坤,黄超平,黄兴伟,等. 基于5G边缘计算的高可靠车路协同组网技术研究与实践[J]. 移动通信, 2023,47(12): 2-8. [paper]

Background

  • 陈山枝. 蜂窝车联网(C-V2X)及其赋能智能网联汽车发展的辩思与建议[J]. 电信科学,2022,38(7):1-17. DOI:10.11959/j.issn.1000−0801.2022154. [paper]
  • 陈山枝,葛雨明,时岩. 蜂窝车联网(C-V2X)技术发展、应用及展望[J]. 电信科学,2022,38(1):1-12. DOI:10.11959/j.issn.1000−0801.2022007.[paper]

Cooperative perception

  • K. Qu and W. Zhuang, "Scalable and Dynamic Cooperative Perception: A Data/Model Co-Driven Framework," in IEEE Network, doi: 10.1109/MNET.2024.3354209. [paper],[code]

  • Dakic, Anja, Benjamin Rainer, Peter Priller, Guo Nan, Anamarija Momic, Xiaochun Ye, and Thomas Zemen. "Wireless V2X Communication Testbed for Connected, Cooperative and Automated Mobility." [paper] [code]

  • People: [Thomas Zemen]

Security

  • H. Guo, X. Chen, X. Zhou and J. Liu, "Trusted and Efficient Task Offloading in Vehicular Edge Computing Networks," in IEEE Transactions on Cognitive Communications and Networking, doi: 10.1109/TCCN.2024.3412394. [paper]

Cooperative perception task offloading

  • Z. Xiao, J. Shu, H. Jiang, G. Min, H. Chen and Z. Han, "Perception Task Offloading With Collaborative Computation for Autonomous Driving," in IEEE Journal on Selected Areas in Communications, vol. 41, no. 2, pp. 457-473, Feb. 2023, doi: 10.1109/JSAC.2022.3227027. [paper]

  • Z. Xiao, J. Shu, H. Jiang, G. Min, J. Liang and A. Iyengar, "Toward Collaborative Occlusion-free Perception in Connected Autonomous Vehicles," in IEEE Transactions on Mobile Computing, doi: 10.1109/TMC.2023.3298643. [paper]

  • H. Yang, Z. Wei, Z. Feng, X. Chen, Y. Li and P. Zhang, "Intelligent Computation Offloading for MEC-Based Cooperative Vehicle Infrastructure System: A Deep Reinforcement Learning Approach," in IEEE Transactions on Vehicular Technology, vol. 71, no. 7, pp. 7665-7679, July 2022, doi: 10.1109/TVT.2022.3171817. [paper]

  • Z. Xiao, J. Shu, H. Jiang, G. Min, H. Chen and Z. Han, "Overcoming Occlusions: Perception Task-Oriented Information Sharing in Connected and Autonomous Vehicles," in IEEE Network, vol. 37, no. 4, pp. 224-229, July/August 2023, doi: 10.1109/MNET.018.2300125. [paper]

  • . -J. Ku, S. Baidya and S. Dey, "Uncertainty-Aware Task Offloading for Multi-Vehicle Perception Fusion Over Vehicular Edge Computing," in IEEE Transactions on Vehicular Technology, vol. 72, no. 11, pp. 14906-14923, Nov. 2023, doi: 10.1109/TVT.2023.3284369. [paper]

  • Zaki, Amr M., Sara A. Elsayed, Khalid Elgazzar, and Hossam S. Hassanein. "Quality-Aware Task Offloading for Cooperative Perception in Vehicular Edge Computing." arXiv preprint arXiv:2405.20587 (2024). [paper]

  • related work

  • P. Lv et al., "Edge Computing Task Offloading for Environmental Perception of Autonomous Vehicles in 6G Networks," in IEEE Transactions on Network Science and Engineering, vol. 10, no. 3, pp. 1228-1245, 1 May-June 2023, doi: 10.1109/TNSE.2022.3211193. [paper]

  • L. Liu, M. Zhao, M. Yu, M. A. Jan, D. Lan and A. Taherkordi, "Mobility-Aware Multi-Hop Task Offloading for Autonomous Driving in Vehicular Edge Computing and Networks," in IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 2, pp. 2169-2182, Feb. 2023, doi: 10.1109/TITS.2022.3142566. [paper]

Cooperative pose optimization

  • 毛瑞清,贾宇宽,孙宇璇,等. 定位与通信受限的网联协同感知算法[J]. 模式识别与人工智能,2023,36(11):1019-1028. DOI:10.16451/j.cnki.issn1003-6059.202311005. [paper]
  • 孙宁. 基于多源信息融合的智能汽车环境感知技术研究[D]. 江苏:江苏大学,2018.[paper]
  • 王法安. 面向城市场景的智能网联汽车协同定位关键技术研究[D]. 江苏:东南大学,2022. [paper]
  • 程超轶. 基于车-车信息动态交互的智能车辆协同定位方法研究[D]. 陕西:长安大学,2021. [paper]
  • P. Yang, D. Duan, C. Chen, X. Cheng and L. Yang, "Multi-Sensor Multi-Vehicle (MSMV) Localization and Mobility Tracking for Autonomous Driving," in IEEE Transactions on Vehicular Technology, vol. 69, no. 12, pp. 14355-14364, Dec. 2020, doi: 10.1109/TVT.2020.3031900.[paper]

Group

People Web Affiliation Github
Arvind Easwaran Cyber-Physical Systems (CPS) Research Group Nanyang Technological University Link
Rajkumar Buyya The Cloud Computing and Distributed Systems (CLOUDS) Laboratory University of Melbourne Link
Zhiwei Zhao MobiNetS (Mobile, Networked and Smart Computing) University of Electronic Science and Technology of China Link
Qiong Wu - Jiangnan University Link
Weisong Shi THE CAR LAB University of Delaware -
Sidi Lu - William & Mary Link
Zhaolong Ning - Chongqing University of Posts and Telecommunications -
Xincao Xu - University of Electronic Science and Technology of China Link
Muhammad Ayzed Mirza - Beijing University of Posts & Telecommunications -
Keqin Li - HUNAN University -
Wei Zhao - Anhui University of Technology -

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