On the public citation graph

https://doi.org/10.2139/ssrn.4494030

0 signed · 19 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-31831-4_43openalex-extracted
An Automotive Cooperative Collision Avoidance Service Based on Mobile Edge Computing
inferredcites →https://doi.org/10.1016/j.vehcom.2016.11.009openalex-extracted
Vehicular cloud networks: Challenges, architectures, and future directions
inferredcites →https://doi.org/10.1016/j.vehcom.2022.100551openalex-extracted
Autonomous vehicles in 5G and beyond: A survey
inferredcites →https://doi.org/10.1109/5gwf49715.2020.9221221openalex-extracted
Vehicular Message Exchange in Cross-border Scenarios Using Public Cloud Infrastructure
inferredcites →https://doi.org/10.1109/access.2021.3068968openalex-extracted
Centralized and Distributed Control Framework Under Homogeneous and Heterogeneous Platoon
inferredcites →https://doi.org/10.1109/infocom42981.2021.9488872openalex-extracted
LiveMap: Real-Time Dynamic Map in Automotive Edge Computing
inferredcites →https://doi.org/10.1109/itsc48978.2021.9564783openalex-extracted
Towards Realistic Evaluation of Collective Perception for Connected and Automated Driving
inferredcites →https://doi.org/10.1109/itst.2015.7377190openalex-extracted
The potential of collective perception in vehicular ad-hoc networks
inferredcites →https://doi.org/10.1109/ivs.2011.5940479openalex-extracted
Analysis of V2X communication parameters for the development of a fusion architecture for cooperative perception systems
inferredcites →https://doi.org/10.1109/pimrc.2018.8580753openalex-extracted
Performance Evaluation of Vehicle-to-Vehicle Communications for a Collective Perception Application in Vehicular Ad hoc Networks
inferredcites →https://doi.org/10.1109/tmc.2021.3118058openalex-extracted
Collaborative Orchestration of Multi-Domain Edges From a Connected, Cooperative and Automated Mobility (CCAM) Perspective
inferredcites →https://doi.org/10.1109/tnsm.2019.2931878openalex-extracted
A MEC-Based Extended Virtual Sensing for Automotive Services
inferredcites →https://doi.org/10.1109/vtc2020-spring48590.2020.9129445openalex-extracted
Redundancy Mitigation in Cooperative Perception for Connected and Automated Vehicles
inferredcites →https://doi.org/10.1145/3416014.3424603openalex-extracted
A Multi-stack Simulation Framework for Vehicular Applications Testing
inferredcites →https://doi.org/10.23919/eeta.2019.8804512openalex-extracted
A MEC-based Extended Virtual Sensing for Automotive Services
inferredcites →https://doi.org/10.3390/s17020271openalex-extracted
Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles
inferredcites →https://doi.org/10.3390/s21010200openalex-extracted
Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations
inferredcites →https://doi.org/10.3390/vehicles4010003openalex-extracted
iLDM: An Interoperable Graph-Based Local Dynamic Map
inferredcites →https://doi.org/10.48550/arxiv.2011.08581openalex-extracted
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.