发展基于交通数据的车辆行驶时间预测算法

Muna Hadi Saleh, Ahmed Nafea Ayesh, P. Sathyaprakash
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引用次数: 0

摘要

这项工作的基础是鼓励对改进的高速公路上车辆行驶时间的算法进行慷慨和可想象的估计,这些算法使用留出的相机图像分组从消除的交通信息中提取车辆行驶时间。车辆行驶时间的评估策略依赖于对交通状态的独特验证。通过计算经过过去时间所覆盖的距离,在移除的交通流数据之间进行平滑处理,并培养一个明确预测车辆行驶时间的计划,从两个持久图像中确认的车辆位置获得特定的车辆速度。埃尔比勒道路数据库用于识别道路段周围的道路位置,这些道路位置被投射到推荐的摄像机图像中,然后将不同的车辆分配到查看路线段,从而计算瞬时和当前速度。使用MATLAB和Python编程语言及其库对所有数据进行了有效的处理和可视化。
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Development prediction algorithm of vehicle travel time based traffic data
This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
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