Please use this identifier to cite or link to this item:
PIRA download icon_1.1View/Download Full Text
Title: Efficient 3D road map data exchange for intelligent vehicles in vehicular fog networks
Authors: Ho, IWH 
Chau, SCK
Magsino, ER 
Jia, K
Issue Date: Mar-2020
Source: IEEE transactions on vehicular technology, Mar 2020, v. 69, no. 3, 8946549, p. 3151-3165
Abstract: Through connecting intelligent vehicles as well as the roadside infrastructure, the perception range of vehicles can be significantly extended, and hidden objects at blind spots can be efficiently detected and avoided. To realize this, accurate road map data must be downloaded in real time to these intelligent vehicles for navigation and localization purposes. Besides, the cloud must be updated with dynamic changes that happened in the road network. These involve the transmissions of high-definition 3D road map data for accurately representing the physical environments. In this work, we propose solutions under the fog computing architecture in a heterogeneous vehicular network to optimize data exchange among intelligent vehicles, the roadside infrastructure, as well as regional databases. Specifically, the efficiency of 3D road map data dissemination at roadside fog nodes is achieved by exploiting index coding techniques to reduce the overall data load, while opportunistic scheduling of heterogeneous transmissions can be done to judiciously manage network resources and minimize operating cost. In addition, 3D point cloud coding and hashing techniques are applied to expedite the updates of various dynamic changes in the network. We empirically evaluate the proposed solutions based on real-world mobility traces of vehicles and 3D LIght Detection And Ranging (LIDAR) data of city streets. The proposed system is also implemented in a multi-robotic testbed for practical evaluation.
Keywords: Fog computing
Index coding
Intelligent connected vehicles
Opportunistic scheduling
Vehicular networks
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on vehicular technology 
ISSN: 0018-9545
EISSN: 1939-9359
DOI: 10.1109/TVT.2019.2963346
Rights: © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See for more information.
The following publication Ho, I. W. H., Chau, S. C. K., Magsino, E. R., & Jia, K. (2019). Efficient 3D road map data exchange for intelligent vehicles in vehicular fog networks. IEEE Transactions on Vehicular Technology, 69(3), 3151-3165, is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
a0578-n02_FinalPaper.pdfPre-Published version5.34 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

Last Week
Last month
Citations as of May 28, 2023


Citations as of May 28, 2023


Citations as of Jun 1, 2023


Citations as of Jun 1, 2023

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.