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CCTV traffic congestion analysis at Pejompongan using case based reasoning

机译:基于案例推理的北榄府闭路电视交通拥堵分析

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摘要

Congestion in Jakarta is a chronic problem and is still being sought. The growing city of Jakarta is facing various international events, increasing the complexity of these congestion problems. This research is aimed to propose an alternative solution for congestion problem in Jakarta using Cased-Based Reasoning (CBR) approach on Pejompongan area. The CBR integrated model analyzes congestion at a given point in a particular hour to identify the same case. The Cased-Based Management (CBM) algorithm approach is used to capture transient problems and ultimately reduce case base cases for their contribution to long-term maintenance. Congestion data is obtained from CCTV cameras via website lewatmana.com in some strategic areas. With that data, we use CBR's integrated model to adjust traffic time for traffic flow to be optimized so that congestion will decompose. The results of this study can be used by relevant government agencies and policymakers in Jakarta to formulate the best solution to solve the congestion problem in the Indonesian capital. Image analysis at nights and bad weather conditions become a limitation and also the integration with traffic lights control in this paper that can be a new topic for further research.
机译:雅加达的交通拥堵是一个长期问题,目前仍在寻找之中。不断发展的雅加达市面临着各种国际事件,这些拥堵问题的复杂性日益增加。这项研究旨在为Pejompongan地区的基于案例推理(CBR)的方法提出一种解决雅加达交通拥堵问题的替代方案。 CBR集成模型分析特定小时内给定点的拥塞,以识别同一病例。基于案例的管理(CBM)算法用于捕获瞬态问题,并最终减少基于案例的案例对长期维护的贡献。在某些战略领域,可以通过lewatmana.com网站从闭路电视摄像机获取拥堵数据。利用这些数据,我们使用CBR的集成模型来调整交通时间,以优化交通流量,以免拥堵分解。雅加达的相关政府机构和政策制定者可以使用这项研究的结果,制定解决印度尼西亚首都拥堵问题的最佳解决方案。夜间和恶劣天气条件下的图像分析成为一种局限性,并且与交通信号灯控制的集成成为本文中可能成为进一步研究的新课题。

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