词条 | Public transport accessibility level |
释义 |
The public transport accessibility level (PTAL) is a method sometimes used in United Kingdom transport planning to assess the access level of geographical areas to public transport. PTAL is a simple, easily calculated approach that hinges on the distance from any point to the nearest public transport stop, and service frequency at those stops. The result is a grade from 1–6 (including sub-divisions 1a, 1b, 6a and 6b), where a PTAL of 1a indicates extremely poor access to the location by public transport, and a PTAL of 6b indicates excellent access by public transport. BackgroundThe PTAL calculation was originally developed by the Borough of Hammersmith and Fulham, and was later adopted by Transport for London as the standard method for calculation of public transport access in London. It is not commonly used outside Greater London or the south east of England. MethodThe first stage in PTAL calculation[1] is to calculate the walking distance from the site (known as the point of interest (POI)) to the nearest bus stops and rail stations (where rail can be taken to also include London Underground, DLR and trams). These stops and stations are known as service access points (SAPs). Only SAPs within a certain distance of the POI are included (640m for bus stops and 960m for rail stations, which correspond to a walking time of 8 minutes and 12 minutes respectively at the standard assumed walking speed of 80m/min). The next stage is to determine the service level during the morning peak (defined as 0815-0915) for each route serving a SAP. Where service levels differ in each direction on a route, the highest frequency is taken. On railways, a route is generally defined as a service with a particular calling pattern – for example, services on the Piccadilly line from Hammersmith could be divided into two "routes": Cockfosters to Heathrow and Cockfosters to Uxbridge. A total access time for each route is then calculated by adding together the walking time from the POI to the SAP and the average waiting time for services on the route (i.e. half the headway). This is converted to an equivalent doorstep frequency (EDF) by dividing 30 (minutes) by the total access time, which is intended to convert total access time to a "notional average waiting time, as though the route were available at the doorstep of the POI". A weighting is applied to each route to simulate the enhanced reliability and attractiveness of a route with a higher frequency over other routes. For each mode (e.g. bus, Tube, DLR, tram, rail), the route with the highest frequency is given a weighting of 1.0, with all other routes in that mode weighted at 0.5. Finally, the EDF and the weighting are multiplied to produce an accessibility index for each route, and the accessibility indices for all routes are summed to produce an overall accessibility index for the POI. This accessibility index (AI) can then be converted to a PTAL grade (1–6) through a banding system (where AIs 0.00–5.00 are PTAL 1, 5.01–10.00 are PTAL 2, etc. up to PTAL 6 for scores of 25 and above). UsesThe PTAL is used as a development planning tool in London, to determine both permitted parking standards and development densities. Large site developments (those the London boroughs refer to the Greater London Authority) must follow planning guidelines that allow more parking in areas with low PTALs (i.e., poor public transport) and vice versa—and that also relate the allowed density of development to PTAL (i.e., areas with better public transport may have higher density housing or offices). TfL also have software to calculate PTALs across wide areas using GIS and timetable data, the typical result being a map with coloured bands relating to PTAL grades. Application to other countriesAhmedabad, IndiaThe London PTAL[2] method was first applied in the Indian context to Ahmedabad in 2014 by Bhargav Adhvaryu and Jay Shah[3]. PTAL mapping for Surat, Pune and Bangalore are under development. In the London method, points of interest (POIs) were considered by the actual development (e.g., buildings). However, in Ahmedabad, given the lack of availability of building footprint data at the time of the study, the method deviated by construing POIs as centroids of a 1 km2 grid. Given that the purpose of the study was to explore implications of PTAL at a macro-scale (i.e., development/ master plan level – the study area being 465 km2) and the data constraints, the grid-cell approach seemed justified. In addition, it made the computations much faster. The others adaptation of London method to Ahmedabad included revisiting walk speed and public transport service reliability assumptions. Most of the roads in Ahmedabad do not have footpaths and, if any, are usually occupied by street vendors and parking. Therefore, people are forced to walk on the road (the black-top surface), which creates unsafe and potentially hazardous situations, such that walking is avoided as much as possible, even for short trips. To account for this discomfort walk speed was decreased to 60m/min (based on a few samples) as against 80m/min used in London. The reliability factor added in case of London (to allow for additional wait times) were 2 minutes and 0.75 minutes for buses and rail services, respectively. In Ahmedabad, this was changed to 2.5 minutes for city buses (AMTS) and 1 minute for BRTS (based on empirical observations), and 0.75 minutes was not changed for the proposed metrorail (MEGA). Lastly, in London 8 minutes (i.e., 640m) and 12 minutes (i.e., 960m) were used as the threshold walk distances to bus and rail SAPs, respectively; SAPs beyond these distances are rejected. However, in Ahmedabad, surveys to determine willingness to walk for public transport were not carried out. Therefore, the farthest SAP from a POI (not accounted for in any other POI) was measured, which turned out to be 993m. At 60m/min, this give as willingness to walk at about 16 minutes, which seemed reasonable. The Ahmedabad study[3] discussed several uses of PTAL mapping:
Advantages & disadvantagesWhilst PTAL is a simple calculation (easily performed by a spreadsheet) that offers an obvious indication of the density of public transport provision in an area, it suffers two key problems:
Accessibility modelling has been proposed as a solution to these problems. It uses GIS to calculate door-to-door travel times by public transport to a grid of points around the point of interest, resulting in a set of isochrone maps – journey time contours – within which the number of workplaces, households or residents can be calculated using census data. This method takes into account many more factors than PTAL, but is much more time-consuming and requires expensive software. Similar methods
References1. ^London Datastore http://data.london.gov.uk/dataset/public-transport-accessibility-levels/resource/86bbffe1-8af1-49ba-ac9b-b3eacaf68137 2. ^{{Cite web|url=https://files.datapress.com/london/dataset/public-transport-accessibility-levels/PTAL-methodology.pdf|title=Measuring Public Transport Accessibility Levels|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=}} 3. ^1 {{Cite journal|last=Shah|first=Jay|last2=Adhvaryu|first2=Bhargav|date=2016|title=Public Transport Accessibility Levels for Ahmedabad, India|url=https://scholarcommons.usf.edu/jpt/vol19/iss3/2/|journal=Journal of Public Transportation|language=en|volume=19|issue=3|pages=19–35|doi=10.5038/2375-0901.19.3.2|issn=1077-291X|via=}} 4. ^Greater Manchester Transportation Unit, http://www.gmtu.gov.uk/gmbusroute/GMAL%20Calculation%20Guide.pdf External links
2 : Transportation planning|Public transport in the United Kingdom |
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