Journal ArticleDOI
Citywide road-network traffic monitoring using large-scale mobile signaling data
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TLDR
The Urban-STM scheme, which utilizes large-scale anonymous and coarse-grained mobile signaling data to infer road-network traffic conditions, is presented and experiment results show that the scheme improves traffic monitoring performance in terms of coverage and accuracy.About:
This article is published in Neurocomputing.The article was published on 2021-07-15. It has received 16 citations till now. The article focuses on the topics: Mobile phone.read more
Citations
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Journal ArticleDOI
Explore the recreational service of large urban parks and its influential factors in city clusters – Experiments from 11 cities in the Beijing-Tianjin-Hebei region
Fangzheng Li,Na Yao,Dining Liu,Wenping Liu,Yihao Sun,Wenwen Cheng,Xiong Li,Xiaoli Wang,Yannan Zhao +8 more
TL;DR: In this paper, the authors used the density of mobile phone park check-ins and the average service radius of large urban parks, extracted from a massive volume of anonymized mobile phone signaling data, as two rapid indicators of the recreational use efficiency of urban parks for 11 cities in the Beijing-Tianjin-Hebei (BTH) region.
Journal ArticleDOI
Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China
TL;DR: The carrying capacity and spatial distribution of medical resources in Shenzhen from the perspective of supply and demand and a time-series variation of the coupling coordination degree from 1986 to 2019 are evaluated to provide a theoretical reference for Shenzhen to rationally plan medical resources and improve the carrying capacity.
Journal ArticleDOI
A Deep Learning Framework for Video-Based Vehicle Counting
TL;DR: The results show that the proposed deep learning vehicle counting framework can achieve lane-level vehicle counting without enough annotated data, and the accuracy of vehicle counting can reach up to 99%.
Proceedings ArticleDOI
Data Fusion for Public Transport Traffic Data Analysis: A Case Study
TL;DR: This paper describes how such data collection and analysis can be done in the city of Bratislava following public transport vehicle movement and delays, current weather, and information related to traffic accidents and road closures.
Journal ArticleDOI
Human Origin-Destination Flow Prediction Based on Large Scale Mobile Signal Data
TL;DR: Large-scale mobile phone signal data is used to achieve citywide human OD flow prediction between the coverage of varying signal base stations and a TGCN model combined with a graph fusion module is adopted to pretrain the dynamic population distribution prediction task.
References
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Proceedings ArticleDOI
Hidden Markov map matching through noise and sparseness
Paul E. Newson,John Krumm +1 more
TL;DR: A novel, principled map matching algorithm that uses a Hidden Markov Model (HMM) to find the most likely road route represented by a time-stamped sequence of latitude/longitude pairs, which elegantly accounts for measurement noise and the layout of the road network.
Proceedings ArticleDOI
Map-matching for low-sampling-rate GPS trajectories
TL;DR: The results show that the ST-matching algorithm significantly outperform incremental algorithm in terms of matching accuracy for low-sampling trajectories and when compared with AFD-based global algorithm, ST-Matching also improves accuracy as well as running time.
Journal ArticleDOI
Real-Time Detection of Traffic From Twitter Stream Analysis
TL;DR: A real-time monitoring system for traffic event detection from Twitter stream analysis that fetches tweets from Twitter according to several search criteria; processes tweets, by applying text mining techniques; and finally performs the classification of tweets.
Journal ArticleDOI
Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data
TL;DR: This paper first uses a dynamic traffic simulator to generate flows in all links using available traffic information, estimated demand, and historical traffic data available from links equipped with sensors, and implements an optimization methodology to adjust the origin-to-destination matrices driving the simulator.
Journal ArticleDOI
Traffic flow prediction using LSTM with feature enhancement
TL;DR: This work proposes an improved approach that connects the high-impact value of remarkably long sequence time steps to the current time step, and these high- impact traffic flow values are captured using the attention mechanism.
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