Poster: Analyzing VAM Sampling Rates for E-Bikes in VANETs

This paper investigates the effect of varying Vulnerable Road User Awareness Message (VAM) sampling rates on the network performance in Vehicular Ad-hoc Networks (VANETs), specifically focusing on e-bikes. Basic traffic scenarios were analyzed using the Artery simulation framework, which integrates SUMO for microscopic traffic modeling, OMNeT++ for network simulation, and the ETSI ITS-G5 protocol stack via Vanetza. To enhance realism, recorded cycling speeds from 15 e-bike riders were integrated into the simulation model. The results show that strategic adjustments of VAM transmission intervals improve channel efficiency to maintain high levels of timely attention with reduced channel load. We provide insights for optimizing the trade-off between communication frequency and performance for future deployments of Cooperative Intelligent Transportation Systems (C-ITS) involving Vulnerable Road Users.