MC-COCO4V2P: Multi-Channel Clustering-Based Congestion Control for Vehicle-to-Pedestrian Communication
Parag Sewalkar, Jochen Seitz
Abstract
Vehicle-to-Pedestrian communication can extend crash prevention capabilities of the current driver assistance systems in vehicles. This requires vehicles and pedestrians to exchange safety messages with each other. However, as the number of pedestrians increases, the numerous safety messages transmitted by pedestrians can quickly congest the network. This can severely affect Vehicle-to-Pedestrian and Vehicle-to-Vehicle communication. Hence, a mechanism for the mitigation of network congestion caused by pedestrian safety messages is required. This article proposes a Multi-channel Clustering-based Congestion Control (MC-COCO4V2P) algorithm, a proactive and infrastructure-independent clustering-based approach to mitigate the network congestion caused by pedestrians. Our approach clusters pedestrians based on their location and direction and uses separate channels for exchanging cluster and safety messages, thereby reducing the control information overhead. It also employs a transmit power control mechanism to make the clustering mechanism energy efficient. Our results show that the clustering of pedestrians can significantly improve network performance and reduce the power consumption of pedestrians' devices.