How LUPTAI Works

To help the user better understand the underlying model, we provide a quick description of the model along with the datasets required to support the model.

The LUPTAI Accessibility Model

LUPTAI requires an active transport network consisting of links and nodes, a public transport network consisting of a timetable of links between stops which are located on the active transport network and activity points which are also located on the network. Each activity has an exclusion probability which determines its probability of being included in a particular iteration of the model and a weighting determining how important the accessibility to a particular activity type is in relation to other activity types.

The exclusion probabilities represent how people choose different activity destinations and include issues such as how far people are prepared to travel to get to a particular activity type; how selective people are in choosing a particular activity type etc.

The active transport network, PT network and activities data are loaded into a model object with a set of parameters supplied through the LUPTAI interface. These parameters include such things as modes to be considered, walk speeds, exclusion probabilities, number of iterations etc.

An iteration consists of the following:

  • A set of included activities is evaluated using the exclusion probability. For example, an exclusion probability of 0 means that all activities of that type are included in an iteration. An exclusion probability of 0.5 means that each activity of that type has a 50% chance of being included in an iteration.

  • A random arrival time at each included destination is generated.

  • For each node on the network the lowest generalised cost as a combination of the required modes - walk, cycle, car, public transport, interchange penalties and wait time - to the included destination is calculated.

The above is repeated for each iteration:

  • An average generalised cost is calculated from the number of iterations for each node on the network to each purpose run in the model

  • A composite score for each node is also calculated as a weighted average of the average purpose costs.

The generalised cost is made up from weighted travel times using a cost of time (default is $36 per hour which equates to 1c = 1s).

The weightings for the travel time include:

  • walk weight

  • PT travel time weight

  • PT layover weight

  • interchange weight

  • destination wait weight

  • interchange cost

Activities Input Data

Activities are point destinations on the active transport network. They are associated with a network node.

There are two types of activities in LUPTAI at present:

  • Point activities – these represent a single activity at a point such as a GP or a school. They are stored in the ActivitiesPoints dataset.

  • Attributed activities – these represent multiple instances of an activity at a point. For example, employment is commonly supplied as the number of jobs in a polygon zone. These zones could relate to statistical areas such as CCDs (ABS Census Collection Districts; model zones used in transport network models (e.g. zones from the Brisbane Strategic Transport Model – BSTM) or any other similar zonal datasets. This is handled in LUPTAI as a point on the network close to the centroid of a zone with the number of jobs as an attribute of that activity point. Attributed activity points can therefore have multiple attributes associated with the point – e.g. jobs in different years (2006, 2011, 2016, etc) or different kinds of jobs (Blue Collar, White Collar). They are stored in the ActivitiesAttributes dataset.

In the QGIS Plugin, network links and nodes are two separate datasets and must be imported separately.

Public Transport Input Data

The Public transport data consists of PT Stops and PT Links. The stops represent where commuters can board and alight PT; the links connect two stops, with each service having its own set of links.

In the QGIS Plugin this data is created from PTM or GTFS data.