Development and testing of a 3G/LTE adaptive data collection system in vehicular networks

Abstract

Vehicular ad hoc networks (VANETs) are a special case of mobile ad hoc networks (MANETs). The distinctive characteristics of VANETs include high-speed vehicular nodes and significant variability in node density. Collecting data from VANETs is important in monitoring, controlling, and managing road traffic. However, efficient collection of the needed data is challenging because vehicles are continuously moving and generating a significant amount of events and data. The focus of this paper is on vehicle data collection using 3G/LTE. Initially, a comparison of proactive and reactive data collection schemes is conducted using simulation. The results show that proactive schemes produce the lowest delay and bandwidth usage but the highest loss ratio. To efficiently use the available bandwidth, an adaptive data collection scheme is developed and described. This adaptive data collection scheme is based on a proactive scheme using variable polling periods depending on the vehicle positions in the network and travel time to provide accurate traffic and travel time information to the Traffic Management Center (TMC). Simulation results, using taxi traces in Qatar, show that the proposed algorithm consumes an acceptable amount of megabytes (≈31 MB) per month when the basic polling interval is set to 10 s. Furthermore, traffic simulation results demonstrate that the proposed scheme has a minimum impact on delay and travel time estimates (relative error less than 2.5%), but can produce significant degradations in fuel consumption and emission estimates if computations are made at the TMC (relative error greater than 28% and 65%, respectively). These errors can be eliminated if computations are done on the vehicle.