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Real-time traffic distribution prediction protocol (TDPP) for vehicular networks
Journal of Ambient Intelligence and Humanized Computing ( IF 3.662 ) Pub Date : 2020-10-09 , DOI: 10.1007/s12652-020-02585-9
Maram Bani Younes

Over downtown and highway road scenarios several applications have been proposed to enhance the quality of driving trips there. Safety, efficiency and entertainment services are provided to vehicles through several advanced technologies. Many of these applications require accurate investigation of the traffic characteristics and distributions over the area of interest in order to successfully provide the targeted services. To mention a few, path recommendation protocols, traffic light scheduling algorithms and driving assistance techniques need specific, detailed and accurate traffic distribution reports regarding the investigated area of interest. Several traffic prediction and evaluation protocols have been proposed in the literature using historical, visual and wireless connecting technologies to gather the real-time basic traffic data. Accuracy, delay, bandwidth consumption and high cost required equipments are the main challenges of the previous protocols. In this paper, we aim to propose a real-time traffic distribution prediction protocol (TDPP) using the vehicular network technology. The proposed protocol aims to produce accurate traffic evaluation and distribution of the investigated area of interest based on gathering the basic traffic data of some traveling vehicles there. From the experimental results we can infer that the TDPP protocol provides more accurate traffic evaluation in the case that only a few vehicles are equipped with wireless transceivers. Moreover, it requires less bandwidth and time to evaluate the traffic characteristics compared to traditional protocols in this field, since it only processes the basic traffic data of the small selected set of vehicles there.



中文翻译:

车载网络的实时流量分布预测协议(TDPP)

在市区和高速公路道路场景中,已经提出了几种应用来提高那里的驾驶旅行的质量。通过多种先进技术为车辆提供安全,高效和娱乐服务。为了成功提供目标服务,许多这些应用程序需要对感兴趣区域内的流量特性和分布进行准确调查。仅举几例,路径推荐协议,交通信号灯调度算法和驾驶辅助技术需要有关所研究的感兴趣区域的特定,详细和准确的交通分布报告。文献中已经提出了几种使用历史,视觉和无线连接技术的交通预测和评估协议,以收集实时的基本交通数据。准确性,延迟,带宽消耗和所需的高成本设备是先前协议的主要挑战。在本文中,我们旨在提出一种使用车载网络技术的实时流量分布预测协议(TDPP)。所提出的协议旨在基于收集那里一些行驶车辆的基本交通数据来产生准确的交通评估和感兴趣区域的分布。从实验结果可以推断,在只有少数车辆配备无线收发器的情况下,TDPP协议可提供更准确的流量评估。此外,与该领域的传统协议相比,评估流量特性所需的带宽和时间更少,

更新日期:2020-10-11
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