Lei et al., 2016 - Google Patents
Research on multi-objective bus route planning model based on taxi GPS dataLei et al., 2016
- Document ID
- 13432611965558991264
- Author
- Lei S
- Li Z
- Wu B
- Wang H
- Publication year
- Publication venue
- 2016 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)
External Links
Snippet
Effective bus route planning is important for management to solve the traffic problems. In this paper, we analyze the spatiotemporal characteristics of resident trips from real GPS data of taxi in the city of Beijing, China and find that it has significant sub-period and cyclical …
- 238000004422 calculation algorithm 0 abstract description 28
Classifications
-
- 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
- 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
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
-
- 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
- G06Q10/063—Operations research or analysis
- G06Q10/0631—Resource planning, allocation or scheduling for a business operation
-
- 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
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
- G06Q10/047—Optimisation of routes, e.g. "travelling salesman problem"
-
- 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
- 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
- G06Q10/02—Reservations, e.g. for tickets, services or events
- G06Q10/025—Coordination of plural reservations, e.g. plural trip segments, transportation combined with accommodation
-
- 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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Tang et al. | Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city—China | |
Luo et al. | Analysis on spatial-temporal features of taxis' emissions from big data informed travel patterns: a case of Shanghai, China | |
Yang et al. | Comparing travel mode and trip chain choices between holidays and weekdays | |
CN102496076B (en) | Macroscopic, mid-scope and microscopic multilevel urban parking demand prediction model integrated system | |
CN105825310A (en) | Taxi passenger-searching path recommendation method based on information entropy | |
Rothfeld et al. | Analysis of European airports’ access and egress travel times using Google Maps | |
CN104809112A (en) | Method for comprehensively evaluating urban public transportation development level based on multiple data | |
Zahabi et al. | Spatio-temporal analysis of car distance, greenhouse gases and the effect of built environment: A latent class regression analysis | |
Qu et al. | Location optimization for urban taxi stands based on taxi GPS trajectory big data | |
CN109583611A (en) | Customization bus station site selecting method based on net about car data | |
Mayakonda et al. | A top-down methodology for global urban air mobility demand estimation | |
Hashi et al. | GIS based heuristic solution of the vehicle routing problem to optimize the school bus routing and scheduling | |
Ku et al. | Interpretations of Downs–Thomson paradox with median bus lane operations | |
Lei et al. | Research on multi-objective bus route planning model based on taxi GPS data | |
CN117745108B (en) | Passenger flow demand prediction method and system for advanced air traffic | |
Otte et al. | The future of urban freight transport: Shifting the cities role from observation to operative steering | |
Yuan et al. | Taxi high-income region recommendation and spatial correlation analysis | |
Sun et al. | Subway passenger flow analysis and management optimization model based on AFC data | |
Liqun et al. | Research on taxi drivers' passenger hotspot selecting patterns based on GPS data: A case study in Wuhan | |
Tian et al. | Designing and planning sustainable customized bus service for departing attendees of planned special events: A two-phase methodology integrating data-driven and demand-responsive | |
Gallo et al. | Network-wide public transport occupancy prediction framework with multiple line interactions | |
Moreira-Matias et al. | An online learning framework for predicting the taxi stand's profitability | |
Huo et al. | Development of Level-of-Service Criteria based on a Single Measure for BRT in China | |
Oskarbski | Perspectives of telematics implementation in Tri-city transport systems management and planning | |
Salanova et al. | Use of probe data generated by taxis |