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Spatio-temporal compression of trajectories in road networks

Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, Ahmed Kharrat
2014 Geoinformatica  
In this paper, we tackle the problem of compressing trajectory data in road networks with deterministic error bounds.  ...  A few works in the field of moving object databases deal with spatio-temporal compression. However, these works only consider the case of objects moving freely in the space.  ...  Cao et al. defined in [3] several distance functions between the spatio-temporal locations of trajectories.  ... 
doi:10.1007/s10707-014-0208-4 fatcat:z5efnrabkzahnofg2bp2jpm22m

A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation

Haitao Yuan, Guoliang Li
2021 Data Science and Engineering  
With the development of mobile Internet and position technologies, it is reasonable to collect spatio-temporal data and then leverage these data to achieve the goal of intelligent transportation, and here  ...  In this paper, we provide a comprehensive survey on traffic prediction, which is from the spatio-temporal data layer to the intelligent transportation application layer.  ...  Road network-based methods enhance the quality of compression using the road network. The authors in [93] match each trajectory onto roads and then represent it with a sequence of roads.  ... 
doi:10.1007/s41019-020-00151-z fatcat:nnnnxnpo3bgk3l4hpr7kk2n4xa

A Survey on Destination Prediction Using Trajectory Data Mining Technique

Banupriya C S
2016 International Journal Of Engineering And Computer Science  
Trajectory is represented by a sequence of time stamped geographical location. Trajectories provide intelligence to estimate, compare and construct candidate routes by historical road network.  ...  Mobility pattern of the user is predicted using next check-in data. Prediction features that exploit different information dimensions about users based on venue prediction.  ...  [8] proposed the sampling big trajectory data increase the scale of spatio-temporal trajectory data.  ... 
doi:10.18535/ijecs/v5i12.67 fatcat:lzg2mq6fdnfstj3ll4s76a35je

A Hybrid Method to Incrementally Extract Road Networks Using Spatio-Temporal Trajectory Data

Yunfei Zhang, Zexu Zhang, Jincai Huang, Tingting She, Min Deng, Hongchao Fan, Peng Xu, Xingshen Deng
2020 ISPRS International Journal of Geo-Information  
patterns in road networks from spatio-temporal trajectory data to help with road map renewal.  ...  Recently, with the emergence of crowdsourced mapping, a surge in academic attention has been paid to generating road networks from spatio-temporal trajectory data.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi9040186 fatcat:pjyslx6yqbelvmglds7majku4q

Mining Spatio-Temporal Reachable Regions over Massive Trajectory Data

Guojun Wu, Yichen Ding, Yanhua Li, Jie Bao, Yu Zheng, Jun Luo
2017 2017 IEEE 33rd International Conference on Data Engineering (ICDE)  
Mining spatio-temporal reachable regions aims to find a set of road segments from massive trajectory data, that are reachable from a user-specified location and within a given temporal period.  ...  In this thesis, we develop two indexing structures: 1) spatio-temporal index (ST-Index) and 2) connection index (Con-Index) to reduce redundant trajectory data access operations.  ...  A trajectory is a sequence of spatio-temporal points.  ... 
doi:10.1109/icde.2017.171 dblp:conf/icde/WuDLBZL17 fatcat:bczyu7fccjhd3ciawpkqulva74

A Hybrid Model and Computing Platform for Spatio-semantic Trajectories [chapter]

Zhixian Yan, Christine Parent, Stefano Spaccapietra, Dipanjan Chakraborty
2010 Lecture Notes in Computer Science  
With large-scale adoption of GPS-driven systems in several application sectors (shipment tracking to geo-social networks), there is a growing demand from applications to understand the spatio-semantic  ...  Spatio-semantic behavior essentially means a semantic (and preferably contextual) abstraction of raw spatio-temporal location feeds.  ...  Definition 1 (Spatio-temporal Trajectory Tspa). A spatio-temporal trajectory Tspa is a cleansed subsequence of raw GPS feed for a given moving object in a given time interval [t begin , t end ].  ... 
doi:10.1007/978-3-642-13486-9_5 fatcat:wacna7rgbrc5zfqha3ozz27sia

Semantic trajectories

Zhixian Yan, Dipanjan Chakraborty, Christine Parent, Stefano Spaccapietra, Karl Aberer
2013 ACM Transactions on Intelligent Systems and Technology  
Such data are typically modeled as streams of spatio-temporal (x,y,t) points, called trajectories.  ...  We also analyze a number of experiments we did with semantic trajectories in different domains.  ...  Semantics is contained both in the geometric properties of the spatio-temporal stream (e.g. when the user stops/moves) as well as in the geography on which the trajectory passes (e.g. shops, roads).  ... 
doi:10.1145/2483669.2483682 fatcat:ppv7g6kihjattjmf7g6nb3txxy

Nonmaterialized Motion Information in Transport Networks [chapter]

Hu Cao, Ouri Wolfson
2004 Lecture Notes in Computer Science  
The traditional way of representing motion in 3D space-time uses a trajectory, i.e. a sequence of (x,y,t) points.  ...  We examine an alternative representation, called a nonmaterialized trajectory, which addresses both problems by taking advantage of the a priori knowledge that the motion occurs on a transport network.  ...  We show that in general, although the distance between a trajectory T and its road-snapped trajectory T is bounded, the error of spatio-temporal queries may be unbounded.  ... 
doi:10.1007/978-3-540-30570-5_12 fatcat:2vgpe445yraq5jfh7uynaod5sa

Compact Trip Representation over Networks [chapter]

Nieves R. Brisaboa, Antonio Fariña, Daniil Galaktionov, M. Andrea Rodríguez
2016 Lecture Notes in Computer Science  
We show how CTR can solve relevant spatial and spatio-temporal queries over large sets of trajectories.  ...  We also represent the temporal component of the trips, that is, the time instants when users visit nodes in their trips.  ...  It partitions trajectories into segments from an underlaying road network, and then adds one temporal B + -tree to index the trajectory segments from each road.  ... 
doi:10.1007/978-3-319-46049-9_23 fatcat:tvxkrzxh75e5lbr6snsss5fjk4

Prediction-based Online Trajectory Compression [article]

Arlei Silva, Ramya Raghavendra, Mudhakar Srivatsa, Ambuj K. Singh
2016 arXiv   pre-print
Trajectory compression is a promising approach for scaling up spatio-temporal databases.  ...  However, existing techniques fail to address the online setting, in which a compressed version of a trajectory stream has to be maintained over time.  ...  Theorem 1 enables the comparison of two road networks (e.g. different cities), quantifying the hardness of compressing trajectories on them.  ... 
arXiv:1601.06316v2 fatcat:wpyhhypirbfqlhuzltzp55arw4

Compression of uncertain trajectories in road networks

Tianyi Li, Ruikai Huang, Lu Chen, Christian S. Jensen, Torben Bach Pedersen
2020 Proceedings of the VLDB Endowment  
Unlike existing studies that target accurate trajectories, we propose a framework that accommodates uncertain trajectories in road networks.  ...  In particular, a new compression scheme for temporal information is presented to take into account variations in sample intervals.  ...  Road network-embedded compression can be classified as spatial compression or spatio-temporal compression. Spatial compression. Krogh et al.  ... 
doi:10.14778/3384345.3384353 fatcat:2j3iewdblrdm3axo6mxbdxfv7u

A Novel Spatio-Temporal Model for City-Scale Traffic Speed Prediction

Kun Niu, Huiyang Zhang, Tong Zhou, Cheng Cheng, Chao Wang
2019 IEEE Access  
INDEX TERMS Convolutional neural network, long short-term memory neural network, spatio-temporal modeling, traffic speed prediction. 30050 2169-3536  ...  In this paper, we propose a novel spatio-temporal model named L-U-Net based on U-Net as well as long short-term memory architecture and develop an effective speed prediction model, which is capable of  ...  After comprehensive consideration of spatio-temporal features, L-U-Net could output the prediction results of traffic speed on urban roads.  ... 
doi:10.1109/access.2019.2902185 fatcat:u3y3fgyci5aj3h5zhk2xa77f2y

Semantic trajectories modeling and analysis

Christine Parent, Nikos Pelekis, Yannis Theodoridis, Zhixian Yan, Stefano Spaccapietra, Chiara Renso, Gennady Andrienko, Natalia Andrienko, Vania Bogorny, Maria Luisa Damiani, Aris Gkoulalas-Divanis, Jose Macedo
2013 ACM Computing Surveys  
This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies.  ...  In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application.  ...  Therefore, recent works like Schmid et al. [2009] and Kellaris et al. [2009] design another kind of trajectory compression models that make use of the underlying road network.  ... 
doi:10.1145/2501654.2501656 fatcat:g7nr36bop5eslcfmr4z34mvj4i

Detecting Congestion Patterns in Spatio Temporal Traffic Data Using Frequent Pattern Mining

Sivaranjani S.
2018 Bonfring International Journal of Networking Technologies and Applications  
Frequent substructures of these causality trees reveal not only recurring interactions among spatial-temporal congestions, but potential bottlenecks or flaws in the design of existing traffic networks.  ...  In this research, the detection of unusual traffic patterns based on spatio-temporal traffic data is by constructing causal congested tree and then to find the frequent sub tree, FP-Growth algorithm is  ...  trajectory patterns, the associative classification- Detecting Congestion Patterns in Spatio Temporal Traffic Data Using Frequent Pattern Mining S.  ... 
doi:10.9756/bijnta.8372 fatcat:2xxpisuozzc57jewajfbeenkjm

SeMiTri

Zhixian Yan, Dipanjan Chakraborty, Christine Parent, Stefano Spaccapietra, Karl Aberer
2011 Proceedings of the 14th International Conference on Extending Database Technology - EDBT/ICDT '11  
from chosen geographic sources (e.g. points-of-interest, road networks).  ...  GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatio-temporal (x,y,t) points.  ...  As a subsequence of raw trajectory Q, a move episode also includes a list of spatio-temporal points.  ... 
doi:10.1145/1951365.1951398 dblp:conf/edbt/YanCPSA11 fatcat:d2v4jtbbxrdrrkkuymyjfwv26a
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