Accessibility Measures in TfL

31st March 2009

HUDU - SMART Population Analysis

Transport Network Planning

Presentation Outline

• TfL’s Accessibility models – PTALs and CAPITAL

• CAPITAL d fi iti d f t• CAPITAL - definition and features

• Health Service Travel Analysis Tool (HSTAT)

• L i d Skill C il St d• Learning and Skills Council Study

Transport Network Planning, 1

TfL’s Accessibility models

• TfL maintains 2 main accessibility models:

PTAL d CAPITAL• PTALs and CAPITAL

• PTALs measures access to the network – network density

• CAPITAL th h th t k j ti• CAPITAL measures access through the network – journey times

PTAL Output CAPITAL Output

Transport Network Planning, 2

CAPITAL – Definition

• Calculator for measuring public transport accessibility in London

• A strategic and local planning tool that calculates detailed minimum travel times through the network.

• Typically the model would calculate travel times from all output areas in London (24,000 locations) to one final destination.destination.

• The model combines GIS and a transportation model to calculate

– Walk times to/from the PT network (GIS)

– Travel times through the PT network (Railplan/EMME2)

– Standard outputs from transportation models can be use but the advantage of CAPITAL is that it can go to a finer level of detail

Transport Network Planning, 3

CAPITAL – Features

• Linked to TfL’s strategic PT models used in scheme evaluation - both current and future.Linked to TfL s strategic PT models used in scheme evaluation both current and future.

• A highly detailed representation of all public transport services – including interchanges, platforms etc

• Can select individual modes or groups of modes – bus, LUL, rail, etc.Can select individual modes or groups of modes bus, LUL, rail, etc.

• Detailed walk catchments possible to final origins and destinations

• Variable walk speeds – to reflect different user groupsVariable walk speeds to reflect different user groups

• Links travel times to a detailed geographic level ..

Typically we consider Output Areas but we can also calculate travel times to postcode centroids, grid points, yp y O p p , g p ,and other user defined origins/destinations.

• Travel times can be linked to individual locations/people.- census data, social segmentation etc

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CAPITAL Outputs

• Travel times from all London census t t t id t B k St tioutput area centroids to Bank Station

• Demonstrates that virtually all of London can reach Bank LUL station within 1 hour

• Can calculate number of people etc within 45 minute travel time of Bank Station

• Travel times to a series of services or t ithi 30 i t t l ticentres within 30 minute travel time.

• Can identify areas more than 30 minutes from a service

• Highlights areas of poor accessibility.

Transport Network Planning, 5

Health Service Travel Analysis Tool (HSTAT)

Outcome of partnership between TfL and NHS

Offers a consistent approach to analysing health service accessibilityOffers a consistent approach to analysing health service accessibility

A toolkit of Accessibility Modelling techniques using ‘CAPITAL’ to calculate travel times

HSTAT is managed by Jacobs Consultancy on behalf of TfL/NHS.S s a aged by Jacobs Co su ta cy o be a o / S

HSTAT will be able to answer questions such as:

How many patients could be disadvantaged by changes to service locations?How many patients could be disadvantaged by changes to service locations?

How many could benefit?

What is the average travel time increase/decrease to services?

What percentage of people live within x minutes by public transport of this service?

Could there be a disproportionate effect on disadvantaged groups?

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Example 1 – NHS Local Service Analysis

• Travel times to a site in BrentBrent

•Times derived from a grid of points to one final destination

•Overlay patient locations or other dataset to relate travel times to the local population.

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Example 2 – NHS Local Service Analysis

Hypothetical exampleexample

•Impact on travel times caused by centralising

New site

Old sites centralising services in a London borough

•Centralisation can extend journey times

•Depending on p gthe type of service, relate journey times to specific pdemographic groups – elderly, young etc

Transport Network Planning, 8

Learning and Skills Council Study

•How and why people travel for post-compulsory education and training

G d d th i it•Gender and ethnicity

•Assumed most students use public transport

•Used CAPITAL to provide detailed travel times and relate results to students origin postcode

Sex Students Median TimeFemale 243,858 33.45Male 163,592 36.03

Main Market Segment Students Median TimeUpper secondary 60,473 37.98Extended upper secondary 17,408 36.28Apprentice type 61,652 35.21Adult returner 22,947 32.35Workforce and community 209,344 33.69

Transport Network Planning, 9