How can we make a difference by making ‘accessibility’ measurable?
We are looking for a way to measure ‘accessibility’ to help us set car parking rates for new development that are more responsive to locational context.
We want to understand how people use public and active transport, and emerging transport solutions like car share, to meet their transport needs – and where on-site car parking requirements can be reduced as a result.
Land use planners are keen to ensure that requirements for car parking provision by new development are appropriate.
Appropriate levels of car parking provision vary dramatically depending on the type of development and its location. A key factor appears to be the accessibility of the development’s location. A highly-accessible area tends to be thought of as one that is well-connected to key services via active or public transport, and/or to have a high level of access to emerging transport solutions like car share.
Ensuring appropriate levels of car parking can have significant flow-on effects for the broader community – for example:
• In low-accessibility areas, appropriate car parking can reduce time taken to find, or queue for, parking; this can also reduce the number and duration of traffic jams.
• In high-accessibility areas, appropriate car parking can encourage use of active and public transport, and result in reduced levels of car use and ownership.
There is currently no reliable way for accessibility to be measured. So, we are looking for a way to measure accessibility that:
• Can be defined in legislation
• Can be easily used by anyone, for any location in NSW
• Enables the setting of clear thresholds – e.g. if a location satisfies a certain threshold for accessibility, a new development would not be required to provide car parking, or could provide it at a lower rate because the people living there are less likely to need to use or own cars.
A way of visualising this measure of accessibility (for example, via a heat map or similar) would also be highly valued.
Such a measure would provide land use planners with an evidence base for setting the most appropriate car parking requirements for new development.
In solving this problem, it might be useful to consider:
• Where are we already seeing reduced dependency on cars? What factors are influencing this?
• Where is dependency on cars still high? What factors are influencing this?
Factors might include things like:
• How long it takes to get to essential services like shops and schools by active (walking, cycling) or public transport
• Public transport accessibility:
o How many routes are available within a certain distance of each location?
o How many services do those routes receive at different times of day?
o Is access direct or are service changes needed?
• The availability and uptake of novel transport solutions like car share
The following websites may provide some insights into how this problem could be addressed:
• AwaP-IC – an open-source GIS tool for measuring walkable access
• London’s WebCAT is an example of how another major city has tried to grapple with this issue. WebCAT provides information on London's transport system to the professional planning community; its connectivity assessment toolkit provides two ways of measuring transport connectivity:
o PTAL assesses connectivity (level of access) to the transport network, combining walk time to the public transport network with service wait times
o Time Mapping analysis (TIM) assesses connectivity through the transport network or, in other words, how far a traveller can go expressed as a series of travel time catchments
• The report “Assessing transport connectivity in London” provides a user-friendly background to London’s approach, and details of how PTAL and TIM are calculated.
• Transport for NSW’s propensity to cycle report
• Transport for NSW - Travel Choices
• City of Sydney - Travel planning guidelines
Image credit: Aerial view of a city at night, photo by Jeremy Bishop on Unsplash
Entry: Challenge entry is available to all teams in Australia.
NSW Active transport hub dataset
NSW Household travel survey data
Census of Population and Housing: Commuting to Work
NSW Parking and Council Data
NSW Collective Cycling Datasets (Cycling and bicycle counts)
NSW Public Transport Accessibility Level (PTAL)