EdgeMap: CrowdSourcing High Definition Map in Automotive Edge Computing
Author:
Affiliation:
1. University of Nebraska-Lincoln
2. Xidian University
3. University of North Carolina at Charlotte
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838617.pdf?arnumber=9838617
Reference22 articles.
1. VirtualEdge: Multi-Domain Resource Orchestration and Virtualization in Cellular Edge Computing
2. An Open-Source Techno-Economic Assessment Framework for 5G Deployment
3. Study on channel model for frequencies from 0.5 to 100 GHz;3GPP,2018
4. LiveMap: Real-Time Dynamic Map in Automotive Edge Computing
5. Deep learning;goodfellow,2016
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1. Data Collection for HD Map Updates through MEC-assisted Vehicle Crowdsourcing: A Trade off between Accuracy and Cost;2023 IEEE 23rd International Conference on Communication Technology (ICCT);2023-10-20
2. Performance Analysis of High-Definition Map Distribution in VANET;2023 International Wireless Communications and Mobile Computing (IWCMC);2023-06-19
3. CoMap: Proactive Provision for Crowdsourcing Map in Automotive Edge Computing;ICC 2023 - IEEE International Conference on Communications;2023-05-28
4. Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving;Remote Sensing;2023-02-07
5. DynNetSLAM: Dynamic Visual SLAM Network Offloading;IEEE Access;2022
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