V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures
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Abstract (arXiv)
Scalable communication is of utmost importance for reliable dissemination of time-sensitive information in cooperative vehicular ad-hoc networks (VANETs), which is, in turn, an essential prerequisite for the proper operation of the critical cooperative safety applications. The model-based communication (MBC) is a recently-explored scalability solution proposed in the literature, which has shown a promising potential to reduce the channel congestion to a great extent. In this work, based on the MBC notion, a technology-agnostic hybrid model selection policy for Vehicle-to-Everything (V2X) communication is proposed which benefits from the characteristics of the non-parametric Bayesian inference techniques, specifically Gaussian Processes. The results show the effectiveness of the proposed communication architecture on both reducing the required message exchange rate and increasing the remote agent tracking precision.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Mar 2019.
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Citing papers per year: 2021: 3; 2022: 3.
6 papers.
- 2021Social Coordination and Altruism in Autonomous Drivingcited by 28
- 2022Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Trafficcited by 15
- 2021Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Criticcited by 11
- 2022Prediction-aware and Reinforcement Learning based Altruistic Cooperative Drivingcited by 6
- 2021Towards Learning Generalizable Driving Policies from Restricted Latent Representationscited by 4
- 2022Context-Aware Target Classification with Hybrid Gaussian Process prediction for Cooperative Vehicle Safety systemscited by 0
- 2022Context-Aware Target Classification with Hybrid Gaussian Process prediction for Cooperative Vehicle Safety systems24 Dec 2022
- 2022Prediction-aware and Reinforcement Learning based Altruistic Cooperative Driving19 Nov 2022
- 2022Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic2 Feb 2022
- 2021Towards Learning Generalizable Driving Policies from Restricted Latent Representations5 Nov 2021
- 2021Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic12 Jul 2021
- 2021Social Coordination and Altruism in Autonomous Driving1 Jul 2021