The global market for Public Transport Time Series Data was valued at US$ 417 million in the year 2024 and is projected to reach a revised size of US$ 1304 million by 2031, growing at a CAGR of 17.7% during the forecast period.
Public transport time series data refers to the data related to public transport recorded in time order, which reflects the changes of various phenomena or events in the process of public transport operation over time. These data usually include the real-time location of public transportation such as buses, subways, trains, arrival time, departure time, operating speed, travel time and other information. Timing data can be single-dimensional, such as the location of a bus at different points in time, or multi-dimensional, such as recording the location and speed of multiple buses simultaneously.
North American market for Public Transport Time Series Data is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for Public Transport Time Series Data is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for Public Transport Time Series Data in Intelligent Traffic Management is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of Public Transport Time Series Data include Citymapper, Intel, Transit, Cubic Corporation, GTFS, Google, Deutsche Bahn, Swiftly, Wikiroutes, Optibus, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Public Transport Time Series Data, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Public Transport Time Series Data.
The Public Transport Time Series Data market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global Public Transport Time Series Data market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Public Transport Time Series Data companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Citymapper
Intel
Transit
Cubic Corporation
GTFS
Google
Deutsche Bahn
Swiftly
Wikiroutes
Optibus
HERE Technologies
TomTom
YITUOTONG Technology
Amap
Baidu
Alibaba Corporation
MetaLight
Sogu Internet Technology
Sudi Intelligent System
Shanghai Suishenxing Smart Transportation Technology
Segment by Type
Real-time Query
Real-time Prediction
Data Analysis
Data Processing
Segment by Application
Intelligent Traffic Management
Smart Travel
Others
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Public Transport Time Series Data company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
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1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Public Transport Time Series Data Market Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Real-time Query
1.2.3 Real-time Prediction
1.2.4 Data Analysis
1.2.5 Data Processing
1.3 Market by Application
1.3.1 Global Public Transport Time Series Data Market Growth by Application: 2020 VS 2024 VS 2031
1.3.2 Intelligent Traffic Management
1.3.3 Smart Travel
1.3.4 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global Public Transport Time Series Data Market Perspective (2020-2031)
2.2 Global Public Transport Time Series Data Growth Trends by Region
2.2.1 Global Public Transport Time Series Data Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 Public Transport Time Series Data Historic Market Size by Region (2020-2025)
2.2.3 Public Transport Time Series Data Forecasted Market Size by Region (2026-2031)
2.3 Public Transport Time Series Data Market Dynamics
2.3.1 Public Transport Time Series Data Industry Trends
2.3.2 Public Transport Time Series Data Market Drivers
2.3.3 Public Transport Time Series Data Market Challenges
2.3.4 Public Transport Time Series Data Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Public Transport Time Series Data Players by Revenue
3.1.1 Global Top Public Transport Time Series Data Players by Revenue (2020-2025)
3.1.2 Global Public Transport Time Series Data Revenue Market Share by Players (2020-2025)
3.2 Global Top Public Transport Time Series Data Players by Company Type and Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by Public Transport Time Series Data Revenue
3.4 Global Public Transport Time Series Data Market Concentration Ratio
3.4.1 Global Public Transport Time Series Data Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Public Transport Time Series Data Revenue in 2024
3.5 Global Key Players of Public Transport Time Series Data Head office and Area Served
3.6 Global Key Players of Public Transport Time Series Data, Product and Application
3.7 Global Key Players of Public Transport Time Series Data, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Public Transport Time Series Data Breakdown Data by Type
4.1 Global Public Transport Time Series Data Historic Market Size by Type (2020-2025)
4.2 Global Public Transport Time Series Data Forecasted Market Size by Type (2026-2031)
5 Public Transport Time Series Data Breakdown Data by Application
5.1 Global Public Transport Time Series Data Historic Market Size by Application (2020-2025)
5.2 Global Public Transport Time Series Data Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America Public Transport Time Series Data Market Size (2020-2031)
6.2 North America Public Transport Time Series Data Market Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America Public Transport Time Series Data Market Size by Country (2020-2025)
6.4 North America Public Transport Time Series Data Market Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Public Transport Time Series Data Market Size (2020-2031)
7.2 Europe Public Transport Time Series Data Market Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe Public Transport Time Series Data Market Size by Country (2020-2025)
7.4 Europe Public Transport Time Series Data Market Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Public Transport Time Series Data Market Size (2020-2031)
8.2 Asia-Pacific Public Transport Time Series Data Market Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific Public Transport Time Series Data Market Size by Region (2020-2025)
8.4 Asia-Pacific Public Transport Time Series Data Market Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Public Transport Time Series Data Market Size (2020-2031)
9.2 Latin America Public Transport Time Series Data Market Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America Public Transport Time Series Data Market Size by Country (2020-2025)
9.4 Latin America Public Transport Time Series Data Market Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Public Transport Time Series Data Market Size (2020-2031)
10.2 Middle East & Africa Public Transport Time Series Data Market Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa Public Transport Time Series Data Market Size by Country (2020-2025)
10.4 Middle East & Africa Public Transport Time Series Data Market Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Citymapper
11.1.1 Citymapper Company Details
11.1.2 Citymapper Business Overview
11.1.3 Citymapper Public Transport Time Series Data Introduction
11.1.4 Citymapper Revenue in Public Transport Time Series Data Business (2020-2025)
11.1.5 Citymapper Recent Development
11.2 Intel
11.2.1 Intel Company Details
11.2.2 Intel Business Overview
11.2.3 Intel Public Transport Time Series Data Introduction
11.2.4 Intel Revenue in Public Transport Time Series Data Business (2020-2025)
11.2.5 Intel Recent Development
11.3 Transit
11.3.1 Transit Company Details
11.3.2 Transit Business Overview
11.3.3 Transit Public Transport Time Series Data Introduction
11.3.4 Transit Revenue in Public Transport Time Series Data Business (2020-2025)
11.3.5 Transit Recent Development
11.4 Cubic Corporation
11.4.1 Cubic Corporation Company Details
11.4.2 Cubic Corporation Business Overview
11.4.3 Cubic Corporation Public Transport Time Series Data Introduction
11.4.4 Cubic Corporation Revenue in Public Transport Time Series Data Business (2020-2025)
11.4.5 Cubic Corporation Recent Development
11.5 GTFS
11.5.1 GTFS Company Details
11.5.2 GTFS Business Overview
11.5.3 GTFS Public Transport Time Series Data Introduction
11.5.4 GTFS Revenue in Public Transport Time Series Data Business (2020-2025)
11.5.5 GTFS Recent Development
11.6 Google
11.6.1 Google Company Details
11.6.2 Google Business Overview
11.6.3 Google Public Transport Time Series Data Introduction
11.6.4 Google Revenue in Public Transport Time Series Data Business (2020-2025)
11.6.5 Google Recent Development
11.7 Deutsche Bahn
11.7.1 Deutsche Bahn Company Details
11.7.2 Deutsche Bahn Business Overview
11.7.3 Deutsche Bahn Public Transport Time Series Data Introduction
11.7.4 Deutsche Bahn Revenue in Public Transport Time Series Data Business (2020-2025)
11.7.5 Deutsche Bahn Recent Development
11.8 Swiftly
11.8.1 Swiftly Company Details
11.8.2 Swiftly Business Overview
11.8.3 Swiftly Public Transport Time Series Data Introduction
11.8.4 Swiftly Revenue in Public Transport Time Series Data Business (2020-2025)
11.8.5 Swiftly Recent Development
11.9 Wikiroutes
11.9.1 Wikiroutes Company Details
11.9.2 Wikiroutes Business Overview
11.9.3 Wikiroutes Public Transport Time Series Data Introduction
11.9.4 Wikiroutes Revenue in Public Transport Time Series Data Business (2020-2025)
11.9.5 Wikiroutes Recent Development
11.10 Optibus
11.10.1 Optibus Company Details
11.10.2 Optibus Business Overview
11.10.3 Optibus Public Transport Time Series Data Introduction
11.10.4 Optibus Revenue in Public Transport Time Series Data Business (2020-2025)
11.10.5 Optibus Recent Development
11.11 HERE Technologies
11.11.1 HERE Technologies Company Details
11.11.2 HERE Technologies Business Overview
11.11.3 HERE Technologies Public Transport Time Series Data Introduction
11.11.4 HERE Technologies Revenue in Public Transport Time Series Data Business (2020-2025)
11.11.5 HERE Technologies Recent Development
11.12 TomTom
11.12.1 TomTom Company Details
11.12.2 TomTom Business Overview
11.12.3 TomTom Public Transport Time Series Data Introduction
11.12.4 TomTom Revenue in Public Transport Time Series Data Business (2020-2025)
11.12.5 TomTom Recent Development
11.13 YITUOTONG Technology
11.13.1 YITUOTONG Technology Company Details
11.13.2 YITUOTONG Technology Business Overview
11.13.3 YITUOTONG Technology Public Transport Time Series Data Introduction
11.13.4 YITUOTONG Technology Revenue in Public Transport Time Series Data Business (2020-2025)
11.13.5 YITUOTONG Technology Recent Development
11.14 Amap
11.14.1 Amap Company Details
11.14.2 Amap Business Overview
11.14.3 Amap Public Transport Time Series Data Introduction
11.14.4 Amap Revenue in Public Transport Time Series Data Business (2020-2025)
11.14.5 Amap Recent Development
11.15 Baidu
11.15.1 Baidu Company Details
11.15.2 Baidu Business Overview
11.15.3 Baidu Public Transport Time Series Data Introduction
11.15.4 Baidu Revenue in Public Transport Time Series Data Business (2020-2025)
11.15.5 Baidu Recent Development
11.16 Alibaba Corporation
11.16.1 Alibaba Corporation Company Details
11.16.2 Alibaba Corporation Business Overview
11.16.3 Alibaba Corporation Public Transport Time Series Data Introduction
11.16.4 Alibaba Corporation Revenue in Public Transport Time Series Data Business (2020-2025)
11.16.5 Alibaba Corporation Recent Development
11.17 MetaLight
11.17.1 MetaLight Company Details
11.17.2 MetaLight Business Overview
11.17.3 MetaLight Public Transport Time Series Data Introduction
11.17.4 MetaLight Revenue in Public Transport Time Series Data Business (2020-2025)
11.17.5 MetaLight Recent Development
11.18 Sogu Internet Technology
11.18.1 Sogu Internet Technology Company Details
11.18.2 Sogu Internet Technology Business Overview
11.18.3 Sogu Internet Technology Public Transport Time Series Data Introduction
11.18.4 Sogu Internet Technology Revenue in Public Transport Time Series Data Business (2020-2025)
11.18.5 Sogu Internet Technology Recent Development
11.19 Sudi Intelligent System
11.19.1 Sudi Intelligent System Company Details
11.19.2 Sudi Intelligent System Business Overview
11.19.3 Sudi Intelligent System Public Transport Time Series Data Introduction
11.19.4 Sudi Intelligent System Revenue in Public Transport Time Series Data Business (2020-2025)
11.19.5 Sudi Intelligent System Recent Development
11.20 Shanghai Suishenxing Smart Transportation Technology
11.20.1 Shanghai Suishenxing Smart Transportation Technology Company Details
11.20.2 Shanghai Suishenxing Smart Transportation Technology Business Overview
11.20.3 Shanghai Suishenxing Smart Transportation Technology Public Transport Time Series Data Introduction
11.20.4 Shanghai Suishenxing Smart Transportation Technology Revenue in Public Transport Time Series Data Business (2020-2025)
11.20.5 Shanghai Suishenxing Smart Transportation Technology Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 Market Size Estimation
13.1.1.3 Market Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer
Citymapper
Intel
Transit
Cubic Corporation
GTFS
Google
Deutsche Bahn
Swiftly
Wikiroutes
Optibus
HERE Technologies
TomTom
YITUOTONG Technology
Amap
Baidu
Alibaba Corporation
MetaLight
Sogu Internet Technology
Sudi Intelligent System
Shanghai Suishenxing Smart Transportation Technology
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听
*If Applicable.
