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

Guo et al., 2020 - Google Patents

Fine-grained dynamic price prediction in ride-on-demand services: Models and evaluations

Guo et al., 2020

View PDF
Document ID
1292641185316456044
Author
Guo S
Chen C
Wang J
Liu Y
Xu K
Chiu D
Publication year
Publication venue
Mobile Networks and Applications

External Links

Snippet

Abstract Ride-on-demand (RoD) services use dynamic prices to balance the supply and demand to benefit both drivers and passengers, as an effort to improve service efficiency. However, dynamic prices also create concerns for passengers: the “unpredictable” prices …
Continue reading at www.thucsnet.com (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
    • 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
    • G06Q30/0241Advertisement
    • G06Q30/0251Targeted advertisement
    • 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
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01Social networking
    • 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
    • G06F17/30241Information retrieval; Database structures therefor; File system structures therefor in geographical information databases
    • 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
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • 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
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/3453Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492Special 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
    • 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
    • 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
    • G06Q50/10Services
    • G06Q50/20Education
    • 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
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/20Instruments for performing navigational calculations
    • 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
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles

Similar Documents

Publication Publication Date Title
Cui et al. Forecasting current and next trip purpose with social media data and Google places
Wu et al. Quantifying uncertainty in deep spatiotemporal forecasting
Jiang et al. A review of urban computing for mobile phone traces: current methods, challenges and opportunities
Wang et al. Predicting shared-car use and examining nonlinear effects using gradient boosting regression trees
Zheng Urban computing
Guo et al. A simple but quantifiable approach to dynamic price prediction in ride-on-demand services leveraging multi-source urban data
Mishra et al. A tool for measuring and visualizing connectivity of transit stop, route and transfer center in a multimodal transportation network
Aschwanden et al. Learning to walk: Modeling transportation mode choice distribution through neural networks
Griswold et al. A pedestrian exposure model for the california state highway system
Zhang et al. Full-scale spatio-temporal traffic flow estimation for city-wide networks: A transfer learning based approach
Chen et al. STLP-GSM: a method to predict future locations of individuals based on geotagged social media data
Zhao et al. Incorporating spatio-temporal smoothness for air quality inference
Liu et al. Modeling the interaction coupling of multi-view spatiotemporal contexts for destination prediction
Terroso-Saenz et al. Human mobility forecasting with region-based flows and geotagged Twitter data
Wu et al. Assuring quality and waiting time in real-time spatial crowdsourcing
Zou et al. An urban big data-based air quality index prediction: A case study of routes planning for outdoor activities in Beijing
Guo et al. Fine-grained dynamic price prediction in ride-on-demand services: Models and evaluations
Li et al. Book-ahead ride-hailing trip and its determinants: Findings from large-scale trip records in China
Zhang et al. Research on the realization of travel recommendations for different users through deep learning under global information management
Saha et al. Use of a model-based gradient boosting framework to assess spatial and non-linear effects of variables on pedestrian crash frequency at macro-level
Gong et al. Modeling the impact of COVID-19 on transportation at later stage of the pandemic: A case study of Utah
Zhao et al. Exploring the impact of trip patterns on spatially aggregated crashes using floating vehicle trajectory data and graph Convolutional Networks
Jena et al. Assessment of service quality at unsignalized intersections using traffic simulation and computational intelligence
Liu et al. Estimation of travel flux between urban blocks by combining spatio-temporal and purpose correlation
Li et al. How spatial features affect urban rail transit prediction accuracy: A deep learning based passenger flow prediction method