An intelligent clustering algorithm based on hybrid RF/VLC communication model for VANET

Yin, Rui; Cui, Xiaohan; Liu, Sijia; Song, Xudan; Zhu, Huahua; Ma, Xuyao

doi:10.1109/csndsp54353.2022.9908048

Cited by 2 publications

(1 citation statement)

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“…However, the directional nature of VLC poses some challenges for its application, especially at road intersections, where signal propagation in diverse directions is required. Therefore, hybrid RF/VLC systems that leverage the advantage of both the RF and VLC technologies are widely investigated [18]. While RF has broader coverage and is suitable for usage beyond LoS, VLC provides valuable redundancy with low interference for shortrange transmissions, where a direct signal path exists.…”

Section: Introductionmentioning

confidence: 99%

An Emergency Message Routing Protocol for Improved Congestion Management in Hybrid RF/VLC VANETs

Hassan,

Fernando,

Woungang

2023

Telecom

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Unexpected traffic incidents cause safety concerns and intense traffic congestion on crowded urban road networks. Vehicular ad-hoc network (VANET)-aided Intelligent Transport Systems (ITS) aim to mitigate these risks through timely dissemination of alert messages. However, conventional Radio frequency (RF) mobile ad-hoc routing protocols are ill-suited for dynamic VANET environments due to high mutual interference, packet collisions, high end-to-end delay from frequent route discoveries, and periodic beaconing requirements. Fortunately, the quickly emerging Visible Light Communications (VLC) provide complementary short-range connectivity with high bandwidth and low interference. This paper proposes an efficient adaptive routing protocol for emergency messages in dense VANET scenarios leveraging a hybrid RF/VLC system. When an incident or congestion happens, the source vehicle disseminates the information to the incoming vehicles as quickly as possible using a combination of VLC and RF communication networks. Multi-hop relays extend the connectivity if the direct links are blocked. The coverage area is partitioned into zones based on road segments, intersections, and traffic flows. The Road Side Units (RSU)s are intelligently assigned to zones and they analyze the historical traffic data to characterize each zone and decide a response strategy. We also propose a congestion detection scheme that utilizes traffic simulations to forecast the clearance times under different response strategies. The highest-scoring strategy is selected based on the predicted impacts on travel time, emissions, and driver stress levels. The proposed algorithm adaptively uses the selected strategy to proactively alleviate the predicted congestion through optimized routing and control. Overall, the protocol maximizes safety and efficiency during emergencies by leveraging the hybrid RF/VLC, incorporating real-time congestion forecasting and dynamic rerouting into the response strategies.

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Section: Introductionmentioning

confidence: 99%