Publications
Dynamic Traffic Assignment Model (May 2018)
We have completed building a regional scale traffic model covering the entire Auckland region. The model base year is 2016 and three assignment period models have been built. The models are all coded at the microscopic network level but will only be run and maintained as a core decision support tool for Auckland at the mesoscopic level. Due to requests from other organisations, we have set up a link for others to view our technical notes. These are provided in draft form (as at May 2018) for information only and to promote traffic modelling in the wider sense. The models are continuously amended and updated so we do not accept any liability for the use or interpretation of the information. If you have any queries please contact us as we are always keen to improve our models and to hear what others are doing. Happy modelling!
ADTA_Model_Development_Report_v1.2
Authors: AFC
Date: 20/06/2018
Part One: Emerging Technologies for Rapid Transit
As new technologies emerge, it is crucial to future-proof investment decisions for urban transit. There is a risk that current investment decisions ‘lock in’ technologies that may be superseded in coming decades. This report evaluates bus rapid transit (BRT) and light rail transit (LRT) systems, to inform investment decisions. The technology review summarises current and emerging technologies for various dimensions of rapid transit, including vehicle design, power sources and transmission, and control systems. The review highlights that there is an apparent convergence in certain dimensions of transit modes, such as ride quality, peak line capacity and energy sources, but concludes that there remain fundamental differences in the nature of transit services provided.
JMAC_Report2016-01_EmergingTechRapidTransit-Part1_Apr16
Authors: CIR (UofA), UCL, Synergine, Volterra
Date: 16/04/2016
Part Two: Future-proofing Investment Decisions
To inform current investment decisions for mass transit, this paper, Part Two of a series on Emerging Technologies for Rapid Transit, evaluates several emerging technologies in depth to understand their likely future trajectory, and impacts on the forecast costs and benefits of different investment options. Introduction of Connected and Autonomous Vehicles (CAVs) may affect transit demand, however CAVs are unlikely to be widely implemented for several decades. Over the investment timeframe, new technologies are unlikely to shift the relative costs and benefits of LRT and BRT sufficiently to change the conclusions reached in Part One.
JMAC_Report2016-02_EmergingTechRapidTransit-Part2_Jul16
Authors: CIR (UofA), UCL, Synergine, Volterra
Date: 16/07/2016
A thought piece: Transport demand implications of changing population age and ethnic diversity in Auckland
This report offers a thought piece that highlights aspects of the extent and scale of changes in population ageing and ethnicity patterns that may have an impact on travel and transport infrastructure requirements in a future Auckland. It summarises current international and New Zealand research on demographic change, provides some summary forecasts in terms of changing age and ethnic profiles in Auckland and identifies potential issues and causal factors in relation to travel demand (who is travelling how, when and why).
JMAC_Report2016-03_AgeEthnicity_final_19May16
Authors: Massey University
Date: 19/05/2016