基于并行计算策略的尼泊尔GPS道路交通拥堵预测预处理

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI:10.1109/icccis48478.2019.8974477

Suresh Mainali, S. Shakya

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引用次数: 0

摘要

估算特定道路上的旅行时间对于不同的企业和个人都是至关重要的。交通拥挤的道路使人们很难估计出行时间。为了避免道路拥堵，需要对道路的交通拥堵情况进行估计。在这个项目中，我们处理了8gb的6个月的原始轨迹GPS数据，这些数据来自一家在尼泊尔运营的车队管理公司。提取尼泊尔的道路网络，并利用这些轨迹点进一步绘制路网。并行计算采用任务规划策略，提高了计算速度，充分利用了计算资源。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Pre-processing for Road Traffic Congestion Prediction in Nepal Based On GPS Data Using Parallel Computing Strategy

Estimation of travel time on a particular road is vital for different businesses and individuals. Congested roads with heavy traffic make it difficult to estimate travel time. To avoid the congested road, traffic congestion of a road should be estimated. In this project, we process 8 GB of raw trajectory GPS data of 6 months, obtained from a fleet management company operating in Nepal. Road network of Nepal was extracted and further mapped with those trajectory points. Task programming strategy was used for parallel computing to increase computational speed and utilize the computational resources.

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2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)

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