Low Latency Scalable Point Cloud Communication in VANETs using V2I Communication

Mobile edge and vehicle-based depth sending and real-time point cloud communication is an essential subtask enabling autonomous driving. In this paper, we propose a framework for point cloud multicast in VANETs using vehicle to infrastructure (V2I) communication. We employ a scalable Binary Tree embedded Quad Tree (BTQT) point cloud source encoder with bitrate elasticity to match with an adaptive random network coding (ARNC) to multicast different layers to the vehicles. The scalability of our BTQT encoded point cloud provides a trade-off in the received voxel size/quality vs channel condition whereas the ARNC helps maximize the throughput under a hard delay constraint. The solution is tested with the outdoor 3D point cloud dataset from MERL for autonomous driving. The users with good channel conditions receive a near lossless point cloud whereas users with bad channel conditions are still able to receive at least the base layer point cloud.

[1]  Tracey Ho,et al.  A Random Linear Network Coding Approach to Multicast , 2006, IEEE Transactions on Information Theory.

[2]  Radu Bogdan Rusu,et al.  3D is here: Point Cloud Library (PCL) , 2011, 2011 IEEE International Conference on Robotics and Automation.

[3]  C.-C. Jay Kuo,et al.  Technologies for 3D mesh compression: A survey , 2005, J. Vis. Commun. Image Represent..

[4]  Rufael Mekuria,et al.  Design, Implementation, and Evaluation of a Point Cloud Codec for Tele-Immersive Video , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Jeffrey G. Andrews,et al.  A Primer on Cellular Network Analysis Using Stochastic Geometry , 2016, ArXiv.

[6]  Philip A. Chou,et al.  Motion-Compensated Compression of Dynamic Voxelized Point Clouds , 2016, IEEE Transactions on Image Processing.

[7]  Zhi Chen,et al.  Digital Network Coding Aided Two-Way Relaying: Energy Minimization and Queue Analysis , 2013, IEEE Transactions on Wireless Communications.

[8]  John S. Thompson,et al.  Performance Analysis and Energy Efficiency of Random Network Coding in LTE-Advanced , 2012, IEEE Transactions on Wireless Communications.

[9]  Shahid Mumtaz,et al.  Social Big-Data-Based Content Dissemination in Internet of Vehicles , 2018, IEEE Transactions on Industrial Informatics.

[10]  Khaled Ben Letaief,et al.  On the Joint V2I and V2V Scheduling for Cooperative VANETs With Network Coding , 2012, IEEE Transactions on Vehicular Technology.

[11]  Reinhard Klein,et al.  Eurographics Symposium on Point-based Graphics (2006) Octree-based Point-cloud Compression , 2022 .

[12]  Torsten Braun,et al.  Content-Aware Delivery of Scalable Video in Network Coding Enabled Named Data Networks , 2018, IEEE Transactions on Multimedia.

[13]  Li Li,et al.  Scalable Point Cloud Geometry Coding with Binary Tree Embedded Quadtree , 2018, 2018 IEEE International Conference on Multimedia and Expo (ICME).

[14]  Kiyoharu Aizawa,et al.  Time-Varying Mesh Compression Using an Extended Block Matching Algorithm , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[15]  Shubhranshu Singh,et al.  5G service requirements and operational use cases: Analysis and METIS II vision , 2016, 2016 European Conference on Networks and Communications (EuCNC).

[16]  Nico Blodow,et al.  Real-time compression of point cloud streams , 2012, 2012 IEEE International Conference on Robotics and Automation.

[17]  Pierre Alliez,et al.  Recent advances in compression of 3D meshes , 2005, 2005 13th European Signal Processing Conference.

[18]  Ruonan Zhang,et al.  Adaptive Random Network Coding for Multicasting Hard-Deadline-Constrained Prioritized Data , 2016, IEEE Transactions on Vehicular Technology.

[19]  Joseph Kee-Yin Ng,et al.  Network-Coding-Assisted Data Dissemination via Cooperative Vehicle-to-Vehicle/-Infrastructure Communications , 2016, IEEE Transactions on Intelligent Transportation Systems.