High-resolution vehicle telemetry via heterogeneous IVC

Abstract

Backend services enable the large-scale aggregation of vehicle data. This Floating Car Data (FCD) can be used to detect traffic disturbances. Although today's vehicles are able to determine their position on a per-lane level, FCD is typically only used on a per-street level granularity. In this paper, we show that using the fleet-data from one Original Equipment Manufacturer (OEM) alone as the database (i. e., on a backend) is not sufficient to detect lane-level traffic phenomena, independent from the accuracy of the vehicle localization. We thus present a high-resolution telemetry service based on heterogeneous Inter-Vehicle Communication (IVC). We introduce a holistic IVC simulation framework which we make publicly available and use it to experimentally verify the proposed telemetry service. Results show a significant leverage of IVC on both the resolution of FCD and the accuracy of detecting lane-level traffic phenomena.