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原文传递 Bus travel time modelling using GPS probe and smart card data: A probabilistic approach considering link travel time and station dwell time
题名: Bus travel time modelling using GPS probe and smart card data: A probabilistic approach considering link travel time and station dwell time
正文语种: 英文
作者: Zhuang Dai, Xiaolei Ma; Xi Chen
作者单位: School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle-Infrastructure System and Safety Control, Beihang University, Beijing, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China
关键词: GPS probe data; link travel time; smart card data; station dwell time; travel time reliability
摘要: Path travel time estimation for buses is critical to public transit operation and passenger information system. State-of-the-art methods for estimating path travel time are usually focused on single vehicle with a limited number of road segments, thereby neglecting the interaction among multiple buses, boarding behavior, and traffic flow. This study models path travel time for buses considering link travel time and station dwell time. First, we fit link travel time to shifted lognormal distributions as in previous studies. Then, we propose a probabilistic model to capture interactions among buses in the bus bay as a first-in-first-out queue, with every bus sharing the same set of behaviors: queuing to enter the bus bay, loading/unloading passengers, and merging into traffic flow on the main road. Finally, path travel time distribution is estimated by statistically summarizing link travel time distributions and station dwell time distributions. The path travel time of a bus line in Hangzhou is analyzed to validate the effectiveness of the proposed model. Results show that the model-based estimated path travel time distribution resembles the observed distribution well. Based on the calculation of path travel time, link travel time reliability is identified as the main factor affecting path travel time reliability.
出版年: 2019
期刊名称: Journal of Intelligent Transportation Systems Technology Planning and Operations
卷: 23
期: 2
页码: 175-190
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