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Transport for NSW - Travel Forecasts
The Transport Performance and Analytics (TPA) produces travel forecasts using the Strategic Travel Model (STM). This model is a world class tool that projects travel patterns in the Sydney Greater Metropolitan Area under different land use, transport and pricing scenarios. It can be used to test alternative settlement, employment and transport policies, to identify likely future capacity constraints, or to determine potential usage levels of proposed new transport infrastructure or services. The STM is built largely in the EMME transport modelling software. It is comprised of a series of models and processes that attempt to replicate, in a simplified manner, people’s travel choices and behaviour under a given scenario. The STM combines our understanding of travel behaviour with likely population and employment size and distribution, and likely road and public transport networks and services to estimate future travel under different strategic land use and transport scenarios. The STM produces travel forecasts by origin (2,690) and destination (2,690) STM zones for: The Sydney Greater Metropolitan Area which includes the Sydney Statistical Division, Newcastle Statistical Subdivision and Illawarra Statistical Division. 5 yearly intervals from the latest Census year up to a 35-year horizon 9 travel modes: Car driver, Car passenger, Rail, Bus, Light rail, Ferry, Bike, Walk and Taxi 7 purposes: Work, Business, Primary/Secondary/Tertiary education, Shopping, Other 24 hour, average workday (Monday to Friday excluding public holidays) am/pm peak, interpeak and evening travel
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Transport for NSW - Workforce Forecasts
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Transport Performance and Analytics (TPA) provides projections of workforce at the small area (Travel Zone or TZ) level for the Sydney Greater Metropolitan Area (GMA). The GMA includes the Sydney Greater Capital City Statistical Area (GCCSA), the Southern Highlands and Shoalhaven SA4, Illawarra SA4, Newcastle and Lake Macquarie SA4, and Lower Hunter, Port Stephens, and Maitland SA3s, as defined by the Australian Bureau of Statistics (ABS). TPA workforce projections are five-yearly, from 2011 to 2056 and relate to usual residents of the GMA aged 15 years and over who are employed. They are estimates of employed people based on where they reside. TPA also produces employment projections based on the workplace or job location. They refer to persons aged 15 years and over, working in the GMA regardless of their place of usual residence. The majority of the persons employed in the GMA also reside in the GMA. Factors considered in the estimation of workforce projections include: population by age and gender; participation rates; unemployment rates; historical labour force data; past trends of employment in each industry and the forecasts of industry growth or decline in each region.
Transport for NSW - Transport Performance and Analytics (TPA) Travel Zone Explorer
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Travel Zones (TZs) are the spatial unit of geography defined by Transport Performance and Analytics (TPA), a business unit within Transport for NSW (TfNSW). The TZ spatial layer is applied to data sources used by TfNSW for transport modelling and analysis, including the Household Travel Survey and the Census 2016 Journey to Work data. The Australian Bureau of Statistics (ABS) Statistical Area boundaries form the foundation of the TZ. Generally, a TZ is larger than a Statistical Area Level 1 or Mesh Block, both ABS geography definitions. The ABS Statistical Areas are based on population counts whereas TZ boundaries are defined using population, employment, housing and transport infrastructure. TZs are designed to have standardised trip generation levels across all zones. This causes zones to be different sizes across the metropolitan area. As with many other spatial boundaries, TZs tend to be small in areas with high land-use densities and larger in areas of lower density.
Travel Monitoring Analysis System (TMAS)
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Internal FHWA data program that assists in the collection and analysis of data on traffic volumes, vehicle classification, truck weights for traffic statistics, analysis; it is used for development of policies and regulations. The monthly data are published in the Traffic Volume Trends (TVT) report.
Travel Zones 2001
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Transport Performance and Analytics (TPA) has a range of location information products which include digitised boundaries. Travel Zones (TZs) are the geographic units of TPA’s data collection, transport modelling and analysis. They are designed to align as much as possible with current Australian Bureau of Statistics (ABS) geographic classification for that year, to allow for comparison of different data sources at standard geographies. In order to provide for a similar level of trip generation across zones, TZs are designed to be small in areas with high land use densities and larger in areas of lower density. The key land uses of interest in defining TZs are employment, housing and transport infrastructure. As urban areas change over time, TPA creates a new zoning system in line with each 5-yearly population Census. Digitised boundaries for these zoning systems and equivalences between them, are available to users to undertake spatial analysis. 1991-2006 - Australian Standard Geographical Classification (ASGC), with Statistical Local Areas (SLA), Census Collection District (CCD) and Mesh Blocks (MB). Prior to 2006, TZs aligned to Statistical Local Areas (SLA) Note that GMA may change slightly at the boundary to align with ABS geographic classifications. This will not usually impact on the comparison of data over time.
Transport for London - TfL Business Plan 2009/10 to 2017/18
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Data incorporated in Transport for London's Business Plan. TfL's Business Plan sets out how TfL will improve and expand London's transport network over the next 10 years. It defines the priorities and programmes to be delivered over the period of TfL’s funding settlement with Government. The data supports and describes the Plan's objectives. Data is currently available in Excel format. We are working to make this data available in CSV format.
opendata@tmr.qld.gov.au - Translink PT Performance Dashboard
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The Translink PT (Passenger Transport) performance dashboard is a digital resource that brings greater accessibility and visibility of performance on SEQ's public transport network. The dashboard represents the SEQ area from the Sunshine Coast to the Gold Coast, and includes measures from on-time running, patronage, fines and warnings, passenger injuries, and 25 customer experience metrics. Translink will continue to invest in data collection with new performance measures, regional areas and enhanced filtering features to be added in the future.
Trip generation, parking demand and vessel movement surveys of marinas : data report
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The Transport Planning Partnership (TTPP) has been commissioned by the Transport for NSW (TfNSW) to undertake a trip generation and parking analysis of marina sites across Sydney and Regional NSW. The current Roads and Maritime Services (former Roads and Traffic Authority) rates for marinas have been in place since the 1992 edition of Roads and Maritime’s Guide to Traffic Generating Developments. The rates set out in the 1992 Guide are based on the surveys undertaken in Pittwater in 1978 and Middle Harbour in 1990. With the growth in the number and variety of marinas throughout Australia, it is deemed necessary to undertake a new study for marinas. This study has been undertaken as part of Roads and Maritime’s programme to update trip generation and parking generation studies for specific development types throughout NSW, which commenced in 2008. This data report accompanies the analysis report and contains details of the selected marinas and the survey results.
Bureau of Transport Statistics - Employment Forecasts
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Transport Performance and Analytics (TPA) provides projections of employment at the small area (Travel Zone or TZ) level for the Sydney Greater Metropolitan Area (GMA). The GMA includes the Sydney Greater Capital City Statistical Area (GCCSA), the Southern Highlands and Shoalhaven SA4, Illawarra SA4, Newcastle and Lake Macquarie SA4, and Lower Hunter, Port Stephens, and Maitland SA3s, as defined by the Australian Bureau of Statistics (ABS). There are 2,949 Travel Zones in the Sydney GMA.
Strategic Measures Transit Travel Time Reliability: Percent change in MetroBus on-time performance by Type
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This dataset supports measure M.A.2.a of SD 2023. The source of the data is Capital Metro. Each row displays the statistics related to performance by time.This dataset can be used to know more about on-time performance trends for transit in Austin. View more details and insights related to this measure on the story page : https://data.austintexas.gov/stories/s/M-A-2-a-Transit-Travel-Time-Reliability-percent-ch/ktzy-fxx3/
Travel Zones 2006
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Transport Performance and Analytics (TPA) has a range of location information products which include digitised boundaries. Travel Zones (TZs) are the geographic units of TPA’s data collection, transport modelling and analysis. They are designed to align as much as possible with current Australian Bureau of Statistics (ABS) geographic classification for that year, to allow for comparison of different data sources at standard geographies. In order to provide for a similar level of trip generation across zones, TZs are designed to be small in areas with high land use densities and larger in areas of lower density. The key land uses of interest in defining TZs are employment, housing and transport infrastructure. As urban areas change over time, TPA creates a new zoning system in line with each 5-yearly population Census. Digitised boundaries for these zoning systems and equivalences between them, are available to users to undertake spatial analysis. 1991-2006 - Australian Standard Geographical Classification (ASGC), with Statistical Local Areas (SLA), Census Collection District (CCD) and Mesh Blocks (MB). Prior to 2006, TZs aligned to Statistical Local Areas (SLA) Note that GMA may change slightly at the boundary to align with ABS geographic classifications. This will not usually impact on the comparison of data over time.
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