IoT-Based Crowd Management Framework for Departure Control and Navigation

Abstract

This paper exploits crowdsensing to propose a novel IoT-Based Vehicle Crowd Management (IoT-VCM) framework. By efficiently managing vehicle departures and navigation, the IoT-VCM clears the network in a shorter time, while maintaining the network at low congestion levels to reduce the average travel time. To compromise between these conflicting objectives, the proposed system encompasses two subsystems that work in harmony, namely; the Travel-Time System-Optimum Navigation (TTSON) and the Vehicle Departure Control (VDC). The IoT-VCM uses different network sensory devices (connected vehicles and smartphones) to collect network information that is fused to compute the current road state conditions, based on which, the VDC determines the allowable vehicle departure rates, and the TTSON optimizes their navigation. The proposed system is developed in a microscopic traffic simulator and tested on a calibrated simulated real network. The IoT-VCM controller is compared to the state-of-the-art techniques reported in the literature, namely the dynamic time-dependent incremental user-optimum traffic assignment.