TransPosition to present two papers at this year's AITPM National Conference

10 Apr 2019

Peter Davidson

TransPosition will present two papers at this year's AITPM National Conference.

What goes on inside a zone? - The secrets of intrazonal modelling

Transport models generally work by dividing the city into traffic zones (TAZ), and considering travel between these zones. Travel that remains within a zone -- the intrazonal travel -- is typically handled quite poorly. The quantity of intrazonal trips obviously depend on the size of the model's TAZ, but typical figures are around 15% of all travel, with more significant numbers for active transport modes with around 18% of bicycle trips and 50% of walking trips remaining within a zone. This problem is compounded as a result of many current policy objectives, as increased density, mixed use development and reduced car ownership all increase intrazonal travel. This paper examines the methods and assumptions used for intrazonal modelling. As it does not have traffic zones and explicitly models all travel, TransPosition's 4S model for Brisbane, Sydney and Melbourne is used to refine the assumptions and make recommendations for improvements.

Primary objectives

The objective of this paper is to review and critique the way in which intrazonal travel is considered in strategic transport models. It also seeks to examine the significance of this type of travel, and whether the simple rules of thumb that have typically been used can continue to be supported. This is done through a case study in Brisbane, Melbourne and Sydney, allowing a comparison between and within each area. Results from the strategic models are compared with results from TransPosition's 4S model for these cities. The higher network detail in the 4S model (where all roads and paths are included) and the differing treatment of local travel (where travel is from point-to-point rather than zone-to-zone) allows more explicit calculation of intrazonal travel times and distances. This allows for improvements to the rules of thumb used in traditional models, where intrazonal travel times are related to zonal area or shortest inter-zonal distances.

Conclusion

Historically transport models were focused on modelling car travel, usually on arterial roads and above. When this was the case intrazonal travel could usually be ignored - trips within a zone are short, with high active transport proportions and travel on local roads. However this is increasingly not the case - increased density, mixed use development and reduced car ownership all lead to increased intrazonal travel. Moreover, many policy issues are now concerned with supporting active transport, where these local issues are critical. Finally, public transport demand always has an active transport component, requiring local connectivity and network permeability. This paper explores the methods and assumptions for intrazonal modelling, with case studies in Brisbane, Melbourne and Sydney.

Household travel survey analysis is combined with modelling results. They show that the intrazonal task varies between cities and across different areas, with higher proportions at both ends of the zone size spectrum - smaller high density zones and large outer zones. The intrazonal travel task is also contrasted with the important local walking task of multi-modal trips.

The 4S model, which does not use zones and allows for node-to-node travel with fully detailed networks, is used to test the assumptions that are typically made. These include the calculation of intrazonal distance from zonal area, and the estimate of intrazonal travel time from a factor of the shortest inter-zonal skim.

One city many perspectives - how well does the city serve the varying needs of its residents

Different people need different things - families need access to jobs and schools, whereas retirees may be more focused on retail and medical services. The transport network also appears different to different travellers - school children cannot drive themselves, older people will generally be reluctant to ride bicycles and may walk more slowly, but may have cheaper taxi and PT fares. Because of these factors, the aggregate accessibility of different groups can vary widely. This paper examines these different accessibility profiles for a number of key demographic groups in Brisbane, Melbourne and Sydney using results from multi-modal modelling of these cities. For each group the different areas of the city are assessed to identify the least and most desirable locations for residential dwellings. These are combined with 2016 census data to find those groups most at risk of living in unsuitable areas. The implications of these findings for transport and land use policy are considered.

Primary objectives

The primary objective of this paper is to show how the accessibility of a city varies for different demographic groups and across different cities. The work uses TransPosition's multi-model strategic model, the 4S model, which allows the accessibility across all modes of transport, walking, cycling, car and public transport, to be determined simultaneously. By comparing the ideal residential locations for different demographic groups to their current locations, we identify the groups that seem to be living in non-ideal locations. This leads to discussion of the causes of these variations, and how planning policies, housing affordability projects and transport policy, pricing and infrastructure could be used to lead to better outcomes for those with limited choice. The paper also shows how accessibility analysis can be applied to optimise the location of new facilities such as hospitals, libraries, schools and sporting grounds.

Conclusion

The paper classifies 16 key demographic groups that exist across Australia, and uses household travel survey (HTS) data to identify their travel behaviour, such as maximum walking distances, mode preferences and mode restrictions. This is combined with detailed information on variations in price, walking speeds etc. Additionally the HTS is used to identify travel requirements, such as universities for students; schools, shops and jobs for families; and retail, service and medical facilities for retirees.

Accessibility is highly correlated to the liveability of an area and is related to the opportunities available to people and the ease of accessing them using all modes of transport. TransPosition's 4S model allows travel parameters to be adjusted for each group and their accessibility to be determined in Brisbane, Sydney and Melbourne. From this we identify the locations most suitable for each group, and compare this with current demographics. This allows us to identify groups most at risk of living in locations with poor accessibility for their requirements.

The comparison between Brisbane, Sydney and Melbourne gives insight into how the size of the city, the land structure, public transport options and traffic congestion influence accessibility. Though the solution to improving the accessibility for "at risk" groups is complex, this work gives valuable insights into the parameters and policies that could ensure a better and fairer outcome for different groups.