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首页> 外文期刊>Journal of ambient intelligence and humanized computing >Smart traffic management system in metropolitan cities
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Smart traffic management system in metropolitan cities

机译:大都市城市的智能交通管理系统

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摘要

Now-a-days, traffic congestion is one of the troubles in metro cities. It is mainly due to escalate in vehicle, population etc. Due to the raise in vehicle, the road is incapable of handling the traffic. Consequently it is very important to revamp the traffic management system. The advanced traffic management system intention is to ameliorate the safety and efficiency of the transportation system. Advanced traffic management system permit opportunities for new methods of evaluations and continuing assessment is provided. A few scenarios were analysed in the traffic issues and better performance is acquired in this research. The traffic map in New York City is taken as a database model and to discover the shortest path an advanced Dijkstra's algorithm is applied. The advanced form of Hadoop known as Apache spark is used. Spark is the open standard and it is easy to program as it has tons of high level operators which can be flexible in-memory data processing that enables batch, real-time, and advanced analytics on the Apache Hadoop platform. R-tool is an open source programming language and software environment for statistical computing is also employed. By using time forecasting algorithm, for each scenarios the vehicle speed, count, collusion, time, etc. is calculated and the Map Analysis is done with good performance by using R-tool. The overall performance of the system that enhances the traffic control efficiency is 96.23%
机译:现在,交通拥堵是地铁城市的麻烦之一。它主要是由于车辆,人口等升级,由于车辆的升级,这条路无法处理交通。因此,重新加工交通管理系统非常重要。先进的交通管理系统意图是改善运输系统的安全性和效率。先进的交通管理系统允许提供新的评估方法和持续评估的机会。在交通问题中分析了一些情景,在本研究中获得了更好的性能。纽约市的交通贴图被视为数据库模型,并发现最短的路径应用了高级Dijkstra的算法。使用称为Apache Spark的Hadoop的高级形式。 Spark是开放标准,它易于编程,因为它具有大量的高级运算符,可以灵活地存储数据处理,该数据处理可在Apache Hadoop平台上启用批处理,实时和高级分析。 R-Top是一种开源编程语言和软件环境,也采用了统计计算。通过使用时间预测算法,对于每个场景,计算车速,计数,串集,时间等,通过使用R工具,使用良好的性能进行地图分析。系统的整体性能提高了交通管制效率为96.23%

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