Changes
On February 8, 2019 at 9:50:35 AM +1100, Department of Customer Service-8062:
-
No fields were updated. See the metadata diff for more details.
f | 1 | { | f | 1 | { |
2 | "author": "Transport for NSW", | 2 | "author": "Transport for NSW", | ||
3 | "author_email": "", | 3 | "author_email": "", | ||
4 | "creator_user_id": "aa05e915-b682-4fc9-aa19-5baf0671fe23", | 4 | "creator_user_id": "aa05e915-b682-4fc9-aa19-5baf0671fe23", | ||
5 | "id": "ba0ce484-fdd6-4b78-b92f-115809f356c9", | 5 | "id": "ba0ce484-fdd6-4b78-b92f-115809f356c9", | ||
6 | "license_id": "cc-by", | 6 | "license_id": "cc-by", | ||
7 | "maintainer": "meg-oliverchild-8062", | 7 | "maintainer": "meg-oliverchild-8062", | ||
8 | "maintainer_email": "", | 8 | "maintainer_email": "", | ||
9 | "metadata_created": "2013-05-24T01:03:50.279584", | 9 | "metadata_created": "2013-05-24T01:03:50.279584", | ||
t | 10 | "metadata_modified": "2019-02-07T22:31:09.383418", | t | 10 | "metadata_modified": "2019-02-07T22:50:35.403381", |
11 | "name": "travel-forecasts", | 11 | "name": "travel-forecasts", | ||
12 | "notes": "The Transport Performance and Analytics (TPA) produces | 12 | "notes": "The Transport Performance and Analytics (TPA) produces | ||
13 | travel forecasts using the Strategic Travel Model (STM). This model is | 13 | travel forecasts using the Strategic Travel Model (STM). This model is | ||
14 | a world class tool that projects travel patterns in the Sydney Greater | 14 | a world class tool that projects travel patterns in the Sydney Greater | ||
15 | Metropolitan Area under different land use, transport and pricing | 15 | Metropolitan Area under different land use, transport and pricing | ||
16 | scenarios. It can be used to test alternative settlement, employment | 16 | scenarios. It can be used to test alternative settlement, employment | ||
17 | and transport policies, to identify likely future capacity | 17 | and transport policies, to identify likely future capacity | ||
18 | constraints, or to determine potential usage levels of proposed new | 18 | constraints, or to determine potential usage levels of proposed new | ||
19 | transport infrastructure or services.\r\n\r\nThe STM is built largely | 19 | transport infrastructure or services.\r\n\r\nThe STM is built largely | ||
20 | in the EMME transport modelling software. It is comprised of a series | 20 | in the EMME transport modelling software. It is comprised of a series | ||
21 | of models and processes that attempt to replicate, in a simplified | 21 | of models and processes that attempt to replicate, in a simplified | ||
22 | manner, people\u2019s travel choices and behaviour under a given | 22 | manner, people\u2019s travel choices and behaviour under a given | ||
23 | scenario. The STM combines our understanding of travel behaviour with | 23 | scenario. The STM combines our understanding of travel behaviour with | ||
24 | likely population and employment size and distribution, and likely | 24 | likely population and employment size and distribution, and likely | ||
25 | road and public transport networks and services to estimate future | 25 | road and public transport networks and services to estimate future | ||
26 | travel under different strategic land use and transport | 26 | travel under different strategic land use and transport | ||
27 | scenarios.\r\n\r\nThe STM produces travel forecasts by origin (2,690) | 27 | scenarios.\r\n\r\nThe STM produces travel forecasts by origin (2,690) | ||
28 | and destination (2,690) STM zones for:\r\n\r\n* The Sydney Greater | 28 | and destination (2,690) STM zones for:\r\n\r\n* The Sydney Greater | ||
29 | Metropolitan Area which includes the Sydney Statistical Division, | 29 | Metropolitan Area which includes the Sydney Statistical Division, | ||
30 | Newcastle Statistical Subdivision and Illawarra Statistical | 30 | Newcastle Statistical Subdivision and Illawarra Statistical | ||
31 | Division.\r\n\r\n* 5 yearly intervals from the latest Census year up | 31 | Division.\r\n\r\n* 5 yearly intervals from the latest Census year up | ||
32 | to a 35-year horizon\r\n\r\n* 9 travel modes: Car driver, Car | 32 | to a 35-year horizon\r\n\r\n* 9 travel modes: Car driver, Car | ||
33 | passenger, Rail, Bus, Light rail, Ferry, Bike, Walk and Taxi\r\n\r\n* | 33 | passenger, Rail, Bus, Light rail, Ferry, Bike, Walk and Taxi\r\n\r\n* | ||
34 | 7 purposes: Work, Business, Primary/Secondary/Tertiary education, | 34 | 7 purposes: Work, Business, Primary/Secondary/Tertiary education, | ||
35 | Shopping, Other\r\n\r\n* 24 hour, average workday (Monday to Friday | 35 | Shopping, Other\r\n\r\n* 24 hour, average workday (Monday to Friday | ||
36 | excluding public holidays)\r\n\r\n* am/pm peak, interpeak and evening | 36 | excluding public holidays)\r\n\r\n* am/pm peak, interpeak and evening | ||
37 | travel", | 37 | travel", | ||
38 | "owner_org": "83ac2e16-3767-445a-ac37-98d7c152e8a8", | 38 | "owner_org": "83ac2e16-3767-445a-ac37-98d7c152e8a8", | ||
39 | "private": false, | 39 | "private": false, | ||
40 | "revision_id": "eee05577-e08d-4472-9065-d92cd45a2c41", | 40 | "revision_id": "eee05577-e08d-4472-9065-d92cd45a2c41", | ||
41 | "state": "active", | 41 | "state": "active", | ||
42 | "title": "Travel Forecasts", | 42 | "title": "Travel Forecasts", | ||
43 | "type": "dataset", | 43 | "type": "dataset", | ||
44 | "url": "", | 44 | "url": "", | ||
45 | "version": "" | 45 | "version": "" | ||
46 | } | 46 | } |