Intelligent Safety Message Dissemination with Vehicle Trajectory Density Predictions in VANETs

Karimzadeh Motallebiazar, Mostafa; Mariano de Souza, Allan; Zhao, Zhongliang; Braun, Torsten; Villas, Leandro; Sargento, Susana; Loureiro, Antonio A. F. (2020). Intelligent Safety Message Dissemination with Vehicle Trajectory Density Predictions in VANETs (Submitted) IEEE Transactions on Vehicular Technology Special Issue on Vehicular Networks in the era of 6G: IEEE

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Intelligent Safety Message Dissemination with Vehicle Trajectory Density Predictions in VANETs.pdf - Submitted Version
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Integration of wireless communication systems and machine learning techniques are generating new applications and services in vehicle ad-hoc networks (VANETs). By analyzing data transmission in vehicle-to-vehicle (V2V) communications and vehicle-to-infrastructure (V2I) communications, an intelligent transportation system (ITS) can provide better safety applications. This work explores machine learning approaches to estimate vehicle density on predicted trajectories, which is further utilized to provide intelligent safety message dissemination. With our approach, the traffic safety message, such as accident notifications, will only be disseminated to relevant vehicles that are predicted to pass by the accident areas. Depending on the network connectivity, our system adaptively chooses vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) or hybrid communications to disseminate a message to relevant vehicles. We evaluate the system by using real-world VANET mobility datasets, and experiment results show that our system outperforms other mechanisms without considering predicted vehicle trajectory density information.

Item Type:

Working Paper

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF)
08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)

UniBE Contributor:

Karimzadeh Motallebiazar, Mostafa, Mariano de Souza, Allan, Zhao, Zhongliang, Braun, Torsten

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

Publisher:

IEEE

Language:

English

Submitter:

Dimitrios Xenakis

Date Deposited:

07 Mar 2019 10:58

Last Modified:

05 Dec 2022 15:26

Uncontrolled Keywords:

Vehicle Trajectory Density Prediction, Congestion Prediction, Intelligent Transport System, Safety Data Dissemination

BORIS DOI:

10.7892/boris.127318

URI:

https://boris.unibe.ch/id/eprint/127318

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