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Estimating Dynamic Origin-Destination Data and Travel Demand Using Cell Phone Network Data

机译:使用手机网络数据估算动态始发地数据和旅行需求

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This study develops cell phone location tracking algorithms from a large cell phone network database to estimate the dynamic origin-destination (O-D) traffic flow and travel demand data as well as commuting traffic. A case study was conducted in the Kansas Metro Corridor to analyze the feasibility of using cell phone data to track cross-region (cities) traffic activities, and to derive the O-D traffic, travel demand by time-of-day and commuting traffic data along the traffic corridor based on a 6 week observation period. The results found that the available cell phone network data detected about 17.6% of the daily traffic data compared to the AADT data along the Kansas Metro Corridor. Approximately 58% of the total traffic was determined to be O-D traffic through the study corridor. This indicates that most of the traffic is from three major regions (the Kansas City metropolitan area, the City of Topeka, KS and the City of Lawrence, KS) and the estimated dynamic travel demand can be used for public transportation system planning and schedule arrangements. Due to the low location resolution using the network-based cell phone network, the use of cell phone network in collecting traffic data would be more feasible for long distance or inter-city trips. A longer observation period is also needed to increase the cell phone sample size and could be useful to obtain stable cell phone traffic, reducing the bias of the data.
机译:这项研究从大型手机网络数据库开发了手机位置跟踪算法,以估计动态始发地(O-D)交通流量和旅行需求数据以及通勤交通。在堪萨斯都市走廊进行了案例研究,分析了使用手机数据跟踪跨地区(城市)交通活动的可行性,并得出了OD流量,按时间的出行需求以及沿途的通勤数据基于6周的观察期的交通走廊。结果发现,与沿堪萨斯地铁走廊沿线的AADT数据相比,可用的手机网络数据检测到的每日交通数据约占17.6%。确定通过研究走廊的总流量中约58%是O-D流量。这表明大部分交通来自三个主要地区(堪萨斯城大都市区,堪萨斯州托皮卡市和堪萨斯州劳伦斯市),估计的动态旅行需求可用于公共交通系统的规划和时间表安排。由于使用基于网络的手机网络的位置分辨率较低,因此在长途旅行或城际旅行中使用手机网络收集交通数据将更加可行。还需要更长的观察时间来增加手机样本的数量,这对于获得稳定的手机流量,减少数据偏差可能很有用。

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