[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Yang et al., 2017 - Google Patents

Efficient traffic congestion estimation using multiple spatio-temporal properties

Yang et al., 2017

View PDF
Document ID
630871010679490417
Author
Yang Y
Xu Y
Han J
Wang E
Chen W
Yue L
Publication year
Publication venue
Neurocomputing

External Links

Snippet

Traffic estimation is an important issue to analyze the traffic congestion in large-scale urban traffic situations. Recently, many researchers have used GPS data to estimate traffic congestion. However, how to fuse the multiple data reasonably and guarantee the accuracy …
Continue reading at core.ac.uk (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202Market predictions or demand forecasting
    • G06Q30/0204Market segmentation
    • G06Q30/0205Location or geographical consideration
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01Social networking

Similar Documents

Publication Publication Date Title
Yang et al. Efficient traffic congestion estimation using multiple spatio-temporal properties
Kong et al. Urban traffic congestion estimation and prediction based on floating car trajectory data
Li et al. Real-time GIS for smart cities
Zhang et al. Spatial patterns and determinant factors of population flow networks in China: Analysis on Tencent Location Big Data
Huang et al. A dynamical spatial-temporal graph neural network for traffic demand prediction
Liao et al. Deep sequence learning with auxiliary information for traffic prediction
Chen et al. Fine-grained prediction of urban population using mobile phone location data
Dong et al. Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review
Niu et al. Real-time taxi-passenger prediction with L-CNN
Zhang et al. Urban traffic flow forecast based on FastGCRNN
Zhang et al. Full-scale spatio-temporal traffic flow estimation for city-wide networks: A transfer learning based approach
Zhao et al. Incorporating spatio-temporal smoothness for air quality inference
Bwambale et al. Modelling long-distance route choice using mobile phone call detail record data: a case study of Senegal
Moosavi et al. Modeling urban traffic dynamics in coexistence with urban data streams
Deng et al. The pulse of urban transport: Exploring the co-evolving pattern for spatio-temporal forecasting
Pang et al. Development of people mass movement simulation framework based on reinforcement learning
Zhang et al. Identifying region-wide functions using urban taxicab trajectories
Mahmoud et al. Estimating cycle-level real-time traffic movements at signalized intersections
Zhao et al. Station-level short-term demand forecast of carsharing system via station-embedding-based hybrid neural network
Xu et al. Urban short-term traffic speed prediction with complicated information fusion on accidents
Luo et al. Spatiotemporal hashing multigraph convolutional network for service-level passenger flow forecasting in bus transit systems
Hou et al. Urban region profiling with spatio-temporal graph neural networks
Li et al. Potential predictability of vehicular staying time for large-scale urban environment
Zhang et al. Gof-tte: Generative online federated learning framework for travel time estimation
Habib et al. Application of an independent availability logit model (IAL) for route choice modelling: Considering bridge choice as a key determinant of selected routes for commuting in Montreal