Context-Aware Agent-based Model for Smart Long Distance Transport System

Muhammad Raees, Afzal Ahmed
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Abstract

Long-distance transport plays a vital role in the economic growth of countries. However, there is a lack of systems being developed for monitoring and support of long-route vehicles (LRV). Sustainable and context-aware transport systems with modern technologies are needed. We model for long-distance vehicle transportation monitoring and support systems in a multi-agent environment. Our model incorporates the distance vehicle transport mechanism through agent-based modeling (ABM). This model constitutes the design protocol of ABM called Overview, Design, and Details (ODD). This model constitutes that every category of agents is offering information as a service. Hence, a federation of services through protocol for the communication between sensors and software components is desired. Such integration of services supports monitoring and tracking of vehicles on the route. The model simulations provide useful results for the integration of services based on smart objects.
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基于情境感知的智能长途运输系统代理模型
长途运输对各国的经济增长起着至关重要的作用。然而,目前缺乏用于监控和支持长途车辆(LRV)的系统。我们需要采用现代技术的可持续的、能感知环境的交通系统。我们在多代理环境中建立了长途车辆运输监控和支持系统模型。我们的模型通过基于代理的建模(ABM)纳入了远距离车辆运输机制。该模型构成了 ABM 的设计协议,称为 "概述、设计和细节(ODD)"。因此,需要通过传感器和软件组件之间的通信协议建立服务联盟。这种服务集成支持对路线上的车辆进行监控和跟踪。模型模拟为基于智能对象的服务集成提供了有用的结果。
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