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.

中文翻译：

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基于物联网的人群管理框架，用于离港控制和导航

本文利用人群感知提出了一种新颖的基于IoT的车辆人群管理（IoT-VCM）框架。通过有效地管理车辆的出发和导航，IoT-VCM在更短的时间内清理了网络，同时将网络保持在低拥挤水平，以减少平均旅行时间。为了在这些相互矛盾的目标之间折衷，所提议的系统包括两个相互协调工作的子系统：行驶时间系统最佳导航（TTSON）和车辆离场控制（VDC）。IoT-VCM使用不同的网络传感设备（已连接的车辆和智能手机）来收集网络信息，这些信息融合在一起以计算当前路况，然后VDC确定车辆允许的离场率，然后TTSON优化其导航。拟议的系统是在微观交通模拟器中开发的，并在经过校准的模拟真实网络上进行了测试。将IoT-VCM控制器与文献中报道的最新技术进行了比较，即动态的，与时间有关的增量用户最佳流量分配。