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

Chen et al., 2019 - Google Patents

Data‐Driven Prediction System of Dynamic People‐Flow in Large Urban Network Using Cellular Probe Data

Chen et al., 2019

View PDF @Full View
Document ID
14252196177900920200
Author
Chen X
Wan X
Ding F
Li Q
McCarthy C
Cheng Y
Ran B
Publication year
Publication venue
Journal of Advanced Transportation

External Links

Snippet

Cellular probe data, which is collected by cellular network operators, has emerged as a critical data source for human‐trace inference in large‐scale urban areas. However, because cellular probe data of individual mobile phone users is temporally and spatially …
Continue reading at onlinelibrary.wiley.com (PDF) (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
    • 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
    • G06Q30/0202—Market predictions or demand forecasting
    • G06Q30/0204—Market segmentation
    • G06Q30/0205—Location or geographical consideration
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATIONS NETWORKS
    • H04W4/00—Mobile application services or facilities specially adapted for wireless communication networks
    • H04W4/02—Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26—Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
    • 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
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models

Similar Documents

Publication Publication Date Title
Reif et al. Exploring new ways of visitor tracking using big data sources: Opportunities and limits of passive mobile data for tourism
Ghahramani et al. Urban sensing based on mobile phone data: Approaches, applications, and challenges
Jiang et al. Activity-based human mobility patterns inferred from mobile phone data: A case study of Singapore
Widhalm et al. Discovering urban activity patterns in cell phone data
Sun et al. DxNAT—Deep neural networks for explaining non-recurring traffic congestion
Chen et al. Data‐Driven Prediction System of Dynamic People‐Flow in Large Urban Network Using Cellular Probe Data
Steenbruggen et al. Mobile phone data from GSM networks for traffic parameter and urban spatial pattern assessment: a review of applications and opportunities
Poonawala et al. Singapore in motion: Insights on public transport service level through farecard and mobile data analytics
Zheng et al. Exploring both home-based and work-based jobs-housing balance by distance decay effect
Wen et al. Understanding the topological characteristics and flow complexity of urban traffic congestion
Ma et al. Deriving operational origin-destination matrices from large scale mobile phone data
Qian et al. Using mobile phone data to determine spatial correlations between tourism facilities
Demissie et al. Analysis of the pattern and intensity of urban activities through aggregate cellphone usage
Breyer et al. Comparative analysis of travel patterns from cellular network data and an urban travel demand model
Xue et al. Multi-source data-driven identification of urban functional areas: A case of Shenyang, China
Miller et al. Scaling GPS trajectories to match point traffic counts: A convex programming approach and Utah case study
Fekih et al. Potential of cellular signaling data for time-of-day estimation and spatial classification of travel demand: a large-scale comparative study with travel survey and land use data
Di Lorenzo et al. Identifying human spatio-temporal activity patterns from mobile-phone traces
Duan et al. MobilePulse: Dynamic profiling of land use pattern and OD matrix estimation from 10 million individual cell phone records in Shanghai
Breyer et al. Cellpath routing and route traffic flow estimation based on cellular network data
Demissie Combining datasets from multiple sources for urban and transportation planning: Emphasis on cellular network data
Florez et al. Measuring the impact of economic well being in commuting networks–A case study of Bogota, Colombia
Jacques Mobile phone metadata for development
Jin et al. Augmented Intention Model for Next‐Location Prediction from Graphical Trajectory Context
Hadachi et al. A survey on the advancement of travel time estimation using mobile phone network data