Traffic flow prediction using neural network

Mouna Jiber, Imad Lamouik, Yahyaouy Ali, M. A. Sabri
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引用次数: 17

Abstract

Traffic flow management and analysis have become essential for both individuals to better manage and route their daily commutes, and for transportation planners to optimally schedule road infrastructure maintenance tasks. Therefore the ability to predict the nature of the traffic stream accurately is one of the most important requirements of traffic management systems. In this research, we will propose an intelligent method to predict traffic flow based on real data for the years 2016 and 2017 provided by the Moroccan center for road studies and research. The proposed solution focuses on training a neural network model to estimate future traffic flow on an hourly basis. Results determined by the simulation gave a good prediction to the traffic data.
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基于神经网络的交通流量预测
交通流量管理和分析对于个人更好地管理和安排日常通勤以及交通规划者优化道路基础设施维护任务都变得至关重要。因此,准确预测交通流性质的能力是交通管理系统最重要的要求之一。在本研究中,我们将根据摩洛哥道路研究中心提供的2016年和2017年的真实数据,提出一种智能的交通流量预测方法。提出的解决方案侧重于训练一个神经网络模型,以每小时为基础估计未来的交通流量。仿真结果表明,该方法对交通数据具有较好的预测效果。
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