A real-time discovery method for vehicle companion via service collaboration

IF 2.5 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Web Information Systems Pub Date : 2023-09-11 DOI:10.1108/ijwis-07-2023-0112

Zhongmei Zhang, Qingyang Hu, Guanxin Hou, Shuai Zhang

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引用次数: 0

Abstract

Purpose Vehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time. Design/methodology/approach This paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles. Findings Experiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method. Originality/value To reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.

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基于服务协作的车辆同伴实时发现方法

车辆同伴是日常生活中最常见的同伴模式之一，在事故调查、群体跟踪、拼车推荐和道路规划等方面具有重要价值。由于车辆传感器流数据的复杂性和大规模，现有工作难以保证实时车辆同伴发现(VCD)的效率和有效性。本文旨在提供一种高质量、低成本的实时车辆同伴发现方法。本文提出了一种基于主动数据服务协作的实时VCD方法。本研究利用动态服务协作对相关传感器产生的数据进行选择性处理，放宽车辆伴侣模式的时空约束，从而发现更多潜在的伴侣车辆。结果基于真实数据和仿真数据的实验表明，与集中式方法相比，该方法能多发现67%的同伴车辆，响应时间缩短62%。为了减少流数据的处理量，本研究提出了一种基于主动数据服务模型的基于服务协作的车辆伴侣发现方法。本研究通过放宽时间和空间约束，尽可能多地发现同伴车辆，提供了一种新的车辆同伴定义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Web Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

4.60

自引率

0.00%

发文量

期刊介绍： The Global Information Infrastructure is a daily reality. In spite of the many applications in all domains of our societies: e-business, e-commerce, e-learning, e-science, and e-government, for instance, and in spite of the tremendous advances by engineers and scientists, the seamless development of Web information systems and services remains a major challenge. The journal examines how current shared vision for the future is one of semantically-rich information and service oriented architecture for global information systems. This vision is at the convergence of progress in technologies such as XML, Web services, RDF, OWL, of multimedia, multimodal, and multilingual information retrieval, and of distributed, mobile and ubiquitous computing. Topicality While the International Journal of Web Information Systems covers a broad range of topics, the journal welcomes papers that provide a perspective on all aspects of Web information systems: Web semantics and Web dynamics, Web mining and searching, Web databases and Web data integration, Web-based commerce and e-business, Web collaboration and distributed computing, Internet computing and networks, performance of Web applications, and Web multimedia services and Web-based education.