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A hybrid HMM model for travel path inference with sparse GPS samples

Erdem Ozdemir, Ahmet E. Topcu, Mehmet Kemal Ozdemir
2016 Transportation  
In this study, we propose a novel method for a travel path inference problem from sparse GPS trajectory data.  ...  Particularly, we model travel path inference as an optimization problem in both the spatial and temporal domains and propose a novel hybrid hidden Markov model (HMM) that uses a uniform cost search (UCS  ...  VTrack uses only positions of GPS samples and road network for travel path inference problem while our algorithm uses temporal domain as well.  ... 
doi:10.1007/s11116-016-9734-2 fatcat:lm72u6pm2vcbhamnuxnogbt3ey

Survey on Recommendation of Personalized Travel Sequence

Mayuri D. Aswale, Dr. Dharmadhikari S. C.
2017 IJARCCE  
Then high stratified routes are more optimized by using social similar users travel records for more accuracy.  ...  To solve the problem of providing personalized and sequential travel package recommendation, a topical package model is created using social media data in which automatically mine user travel interest  ...  Existing studies on travel recommendation use the different types of social media data, GPS trajectory, check-in-data, geo tag and blogs which are used for mining famous travel POIS and routes [2] [  ... 
doi:10.17148/ijarcce.2017.6122 fatcat:lwfeqtmakbcoxke5uqn3ut4od4

Monitoring Travel Time Reliability from the Cloud

Hao Lei, Tao Xing, Jeffrey D. Taylor, Xuesong Zhou
2012 Transportation Research Record  
Extracting travel time variability and trip reliability information from a large amount of spatially correlated data from a large-scale network with dramatic variations in travel demand and road capacity  ...  and extracting desirable corridor-level and network-level information through a systematic and seamless integration of data sources.  ...  essential data processing service that converts raw GPS location data samples to 10 useful traffic information in node-link traffic network representation form.  ... 
doi:10.3141/2291-05 fatcat:3c3yrz7yarandeuhie53pbchbu

Constructing popular routes from uncertain trajectories

Ling-Yin Wei, Yu Zheng, Wen-Chih Peng
2012 Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12  
In this paper, we present a Route Inference framework based on Collective Knowledge (abbreviated as RICK) to construct the popular routes from uncertain trajectories.  ...  First, we explore the spatial and temporal characteristics of uncertain trajectories and construct a routable graph by collaborative learning among the uncertain trajectories.  ...  |ܧ|/|‪ሽ‬ܧ‬ The temporal constraint ߠ and the minimum connection support C are used for constructing a routable graph.  ... 
doi:10.1145/2339530.2339562 dblp:conf/kdd/WeiZP12 fatcat:cn6skuqbbng5je6sclzquxzbze

Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments

Siyuan Liu, Yisong Yue, Ramayya Krishnan
2015 IEEE Transactions on Knowledge and Data Engineering  
Using this congestion model, we develop efficient algorithms for nonmyopic adaptive routing to minimize the collective travel time of all vehicles in the system.  ...  Our approach is validated by traffic data from two large Asian cities. Our congestion model is shown to be effective in modeling dynamic congestion conditions.  ...  We computed Figure 4 by sampling from a GPDCM estimated using real traffic data from a real road network (see Section 5), and using a diverse set of source and destination locations.  ... 
doi:10.1109/tkde.2015.2411278 fatcat:iqjidw56vza4zjpz2mul2iic3e

A Survey on Destination Prediction Using Trajectory Data Mining Technique

Banupriya C S
2016 International Journal Of Engineering And Computer Science  
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.  ...  Trajectories provide intelligence to estimate, compare and construct candidate routes by historical road network.  ... 
doi:10.18535/ijecs/v5i12.67 fatcat:lzg2mq6fdnfstj3ll4s76a35je

Haversine Formula and RPA Algorithm for Navigation System

Nyein Chan Soe, Thin Lai Lai Thein
2020 International Journal of Data Science and Analysis  
The system provides accurate maps for estimating traffic conditions more efficiently from GPS data, saving more time.  ...  The proposed system displays changes in the position, distance and direction of vehicles traveling on the streets of Yangon by using traffic state and routing pattern algorithm.  ...  This structural application uses data from the urban network in Yangon. This article aims to follow these factors.  ... 
doi:10.11648/j.ijdsa.20200601.14 fatcat:he3qej35anecfdmpj2gm2lwfay

Linked Open Data in Location-Based Recommendation System on Tourism Domain: a survey

Phatpicha Yochum, Liang Chang, Tianlong Gu, Manli Zhu
2020 IEEE Access  
Third, we group the linked open data sources used in location-based recommendation system on tourism.  ...  In the tourism domain, many studies are using linked open data to address the problem of location-based recommendation by integrating data with other linked open datasets to enrich data and tourism content  ...  The recommender system used fuzzy logic techniques to the rank point of interests and used an ant colony optimization algorithm to construct a travel route.  ... 
doi:10.1109/access.2020.2967120 fatcat:yqwkrko6mzfw5e5kckfaxbxzju

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

Haitao Yuan, Guoliang Li
2021 Data Science and Engineering  
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.  ...  At first, we split the whole research scope into four parts from bottom to up, where the four parts are, respectively, spatio-temporal data, preprocessing, traffic prediction and traffic application.  ...  from cars' GPS points.  ... 
doi:10.1007/s41019-020-00151-z fatcat:nnnnxnpo3bgk3l4hpr7kk2n4xa

An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City

Xiaoguang Niu, Ying Zhu, Qingqing Cao, Xining Zhang, Wei Xie, Kun Zheng
2015 International Journal of Distributed Sensor Networks  
O-Sense firstly exploits a deep learning approach to process spatial and temporal taxi GPS traces shown in dynamic patterns.  ...  Experimental results show that O-Sense can estimate the travel time for driving routes more accurately.  ...  Temporally Related Supplementary Feature Learning. Observing from the data distribution, there are enough taxi GPS traces at day, which is, however, insufficient at midnight.  ... 
doi:10.1155/2015/970256 fatcat:pv6nnyb3wfhfjnw4kwdk72jlve

Applications of Trajectory Data from the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study [article]

Nikola Marković, Przemysław Sekuła, Zachary Vander Laan, Gennady Andrienko, Natalia Andrienko
2018 arXiv   pre-print
In addition, it visually explores 20 million GPS traces in Maryland, illustrating existing and suggesting new applications of trajectory data.  ...  To overcome this issue, the current paper explores trajectory data from the perspective of a road transportation agency interested in acquiring trajectories to enhance its analyses.  ...  Help from the I-95 Corridor Coalition and the City of Annapolis are also appreciated.  ... 
arXiv:1708.07193v2 fatcat:3whfpziwlbggzau4rixofqhcay

Applications of Trajectory Data From the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study

Nikola Markovic, Przemyslaw Sekula, Zachary Vander Laan, Gennady Andrienko, Natalia Andrienko
2018 IEEE transactions on intelligent transportation systems (Print)  
In addition, it visually explores 20 million GPS traces in Maryland, illustrating existing and suggesting new applications of trajectory data.  ...  To overcome this issue, the current paper explores trajectory data from the perspective of a road transportation agency interested in acquiring trajectories to enhance its analyses.  ...  Help from the I-95 Corridor Coalition and the City of Annapolis are also appreciated.  ... 
doi:10.1109/tits.2018.2843298 fatcat:c4qp3znlevb4dm4bhoeuww2cc4

Mining Urban Congestion Evolution Characteristics Based on Taxi GPS Trajectories

Weiyan Xu, Yumei Huang
2020 American Journal of Traffic and Transportation Engineering  
The taxi GPS trajectories involve sufficient temporal and spatial characteristics and make it easy for us to obtain potential knowledge for understanding human mobility pattern and urban traffic network  ...  Second, the average speed of the road segments is obtained according to the taxi GPS trajectories and a dynamic weighted graph of urban road network is constructed to capture complicated urban traffic  ...  Huifang Feng for providing the GPS data used in this work. This work is partially supported by the National Natural Science Foundation of China under Grant (11571156, 71761031).  ... 
doi:10.11648/j.ajtte.20200501.11 fatcat:fvgemjqy2zgd5d6xnhu6367iju

Analysis of Spatial-Temporal Characteristics of Operations in Public Transport Networks Based on Multisource Data

Hui Zhang, Yanjun Liu, Baiying Shi, Jianmin Jia, Wei Wang, Xiang Zhao, Yong Wang
2021 Journal of Advanced Transportation  
In this paper, we propose a data-driven framework to analyze the efficiency and stability based on small granularity GPS trajectory data from the perspective of entire bus network.  ...  The IC card data and route data are used to extract the boarding passenger number and topological structure, respectively.  ...  Tang et al. used GPS trajectory data and smart card data to optimize the timetable of the bus line [41] . e GPS trajectory data could also be used to identify transportation mode by GIS information and  ... 
doi:10.1155/2021/6937228 fatcat:kegq5j5sg5dhvetyc3j4bkcaea

Preface

2021 2021 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)  
the entire traffic network, and deduce the temporal and spatial distribution of the future traffic, as well as predict and detect network congestion nodes, then it will be used for traffic flow guidance  ...  Big data obtained from traffic cards, GPS locations, video monitors, traffic sensors, mobile phone signals, Internet and social media and sources from other ways can provide data governance and data services  ...  Big data analysis will monitor the distribution of passenger flow in real time, predict travel demands, and build intelligent bus schedule model based on artificial intelligence method to optimize routes  ... 
doi:10.1109/icitbs53129.2021.00005 fatcat:ve7k3bvlzjg6jb7gixg74dcepi
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