Mapping New Zealand’s Transport Demands
Researchers at the University of Canterbury in New Zealand have created a visual showing how regional transport demand, measured as passenger and freight activity, could evolve through 2050. The maps…
Researchers at the University of Canterbury in New Zealand have created a visual showing how regional transport demand, measured as passenger and freight activity, could evolve through 2050. The maps break down demand by mode, including road, rail, marine, and aviation, across regions. Each map shows where demand is expected to grow, with darker blue regions indicating stronger increases and lighter areas more modest change. This helps planners understand where transport systems will face the most pressure and where infrastructure and energy investments may be needed.
Take a look.
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https://datainnovation.org/2026/03/mapping-new-zealands-transport-demands/Sign in to highlight and annotate this article

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researchPassive iFIR filters for data-driven velocity control in robotics
arXiv:2603.29882v1 Announce Type: new Abstract: We present a passive, data-driven velocity control method for nonlinear robotic manipulators that achieves better tracking performance than optimized PID with comparable design complexity. Using only three minutes of probing data, a VRFT-based design identifies passive iFIR controllers that (i) preserve closed-loop stability via passivity constraints and (ii) outperform a VRFT-tuned PID baseline on the Franka Research 3 robot in both joint-space and Cartesian-space velocity control, achieving up to a 74.5% reduction in tracking error for the Cartesian velocity tracking experiment with the most demanding reference model. When the robot end-effector dynamics change, the controller can be re-learned from new data, regaining nominal performance.
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