Nothing Special   »   [go: up one dir, main page]

Wang et al., 2014 - Google Patents

Visual exploration of sparse traffic trajectory data

Wang et al., 2014

Document ID
6503450413049428700
Author
Wang Z
Ye T
Lu M
Yuan X
Qu H
Yuan J
Wu Q
Publication year
Publication venue
IEEE transactions on visualization and computer graphics

External Links

Snippet

In this paper, we present a visual analysis system to explore sparse traffic trajectory data recorded by transportation cells. Such data contains the movements of nearly all moving vehicles on the major roads of a city. Therefore it is very suitable for macro-traffic analysis …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
    • G06F17/30994—Browsing or visualization
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30241—Information retrieval; Database structures therefor; File system structures therefor in geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/20—Drawing from basic elements, e.g. lines or circles
    • G06T11/206—Drawing of charts or graphs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA 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
    • G06Q30/00—Commerce, e.g. shopping or e-commerce
    • G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA 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
    • G06Q10/00—Administration; Management

Similar Documents

Publication Publication Date Title
Wang et al. Visual exploration of sparse traffic trajectory data
Andrienko et al. Scalable analysis of movement data for extracting and exploring significant places
Wang et al. Visual traffic jam analysis based on trajectory data
Andrienko et al. From movement tracks through events to places: Extracting and characterizing significant places from mobility data
Chu et al. Visualizing hidden themes of taxi movement with semantic transformation
Chen et al. A survey of traffic data visualization
Pan et al. Crowd sensing of traffic anomalies based on human mobility and social media
Shang et al. Inferring gas consumption and pollution emission of vehicles throughout a city
Liu et al. Visual analysis of route diversity
KR102124955B1 (en) Method and server for identifying the cause of traffic congestion using visual analytics
Ma et al. Mobility viewer: An Eulerian approach for studying urban crowd flow
Saldivar-Carranza et al. Deriving operational traffic signal performance measures from vehicle trajectory data
Pu et al. T-watcher: A new visual analytic system for effective traffic surveillance
Tang et al. A network Kernel Density Estimation for linear features in space–time analysis of big trace data
Esfahani et al. Three-phase classification of an uninterrupted traffic flow: a k-means clustering study
Andrienko et al. Extracting Semantics of Individual Places from Movement Data by Analyzing Temporal Patterns of Visits.
Shi et al. Detecting anomalies in spatio-temporal flow data by constructing dynamic neighbourhoods
Shi et al. UrbanMotion: Visual analysis of metropolitan-scale sparse trajectories
Ding et al. Understanding taxi driving behaviors from movement data
Tageldin et al. Automated analysis and validation of right-turn merging behavior
Zhang et al. A framework of abnormal behavior detection and classification based on big trajectory data for mobile networks
Wang et al. A feature-based method for traffic anomaly detection
Gomes et al. Interactive visualization of traffic dynamics based on trajectory data
Yu et al. Smoothing regression and impact measures for accidents of traffic flows
Fan et al. Context-aware big data analytics and visualization for city-wide traffic accidents