Special issue on methodological advancements in understanding and managing urban traffic congestion
The increasing population in cities induces a high travel demand. Unfortunately, due to the
limited capacity of urban transport networks, this increasing demand for travel raises various …
limited capacity of urban transport networks, this increasing demand for travel raises various …
Impacts of the COVID-19 pandemic on the spatio-temporal characteristics of a bicycle-sharing system: A case study of Pun Pun, Bangkok, Thailand
The COVID-19 pandemic is found to be one of the external stimuli that greatly affects
mobility of people, leading to a shift of transportation modes towards private individual ones …
mobility of people, leading to a shift of transportation modes towards private individual ones …
The spatiotemporal patterns of bus passengers: visualisation and evaluation using non-negative tensor decomposition
NK Shanthappa, RH Mulangi… - Journal of Geovisualization …, 2023 - Springer
Spatiotemporal analysis of passenger mobility patterns provides valuable information
regarding the travel behaviour of passengers at different spatial and temporal scales …
regarding the travel behaviour of passengers at different spatial and temporal scales …
A customized data fusion tensor approach for interval-wise missing network volume imputation
Traffic missing data imputation is a fundamental demand and crucial application for real-
world intelligent transportation systems. The wide imputation methods in different missing …
world intelligent transportation systems. The wide imputation methods in different missing …
[HTML][HTML] Tensor Decomposition of Transportation Temporal and Spatial Big Data: A Brief Review
Recent development in sensing and communication technologies has made the collection of
a large amount of traffic data easy and transportation engineering has entered the big data …
a large amount of traffic data easy and transportation engineering has entered the big data …
Accurate map matching method for mobile phone signaling data under spatio-temporal uncertainty
Y Huang, D Wang, W Xu, Z Cai… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Understanding human mobility has become a greater demand in recent years. Among them,
how to extract people's travel trajectories and reconstruct them accurately is crucial to …
how to extract people's travel trajectories and reconstruct them accurately is crucial to …
Urban mobility analytics amid COVID-19 pandemic: A framework for promoting work resumption based on mobile phone data
Abstract The Corona Virus Disease 2019 (COVID-19) pandemic had a pernicious influence
on the whole world, so that the international community implemented various travel policies …
on the whole world, so that the international community implemented various travel policies …
Uncovering the spatiotemporal motif patterns in urban mobility networks by non-negative tensor decomposition
S Shi, L Wang, X Wang - Physica A: Statistical Mechanics and its …, 2022 - Elsevier
Investigating the macroscopic mobility laws of the population and the microscopic travel
characteristics of individuals in a city offers an essential way of understanding the city as a …
characteristics of individuals in a city offers an essential way of understanding the city as a …
[HTML][HTML] Entropy Tucker model: Mining latent mobility patterns with simultaneous estimation of travel impedance parameters
With the rapid increase in the availability of passive data in the field of transportation,
combining machine learning with transportation models has emerged as an important …
combining machine learning with transportation models has emerged as an important …
TensorAnalyzer: identification of urban patterns in big cities using non-negative tensor factorization
Extracting relevant urban patterns from multiple data sources can be difficult using classical
clustering algorithms since we have to make a suitable setup of the hyperparameters of the …
clustering algorithms since we have to make a suitable setup of the hyperparameters of the …