Designing for a better commute

We developed simulations to test whether a new carriage design could improve passengers' experience

Suburban railways around the world are experiencing a rapid increase in use. While this is a welcome development as an alternative to road congestion, higher passenger densities – particularly during peak times of the day – can impact train punctuality, crowding, accessibility and passenger comfort.

For this project, SensiLab collaborated with the Mobility Design Lab within The Faculty of Art, Design and Architecture (MADA) to simulate how a series of innovative new features in the design of a train carriage affected these factors. Using game engine software to replicate human interactions, design features such as additional doors at peak periods and different carriage layouts, were tested. This research was extended with MADA and the Faculty of Arts to model more nuanced human interactions and behavior in order to examine individual passenger experiences.

3D simulations examined how carriage design affected human interactions
Design features that were examined included additional doors at peak periods and different carriage layouts
Re-thinking the design of public transport could have implications for ease of travel in the future

The simulations and modelling showed that the new train carriage designs were able to improve passenger flow through the carriages and on the station, which could potentially increase accessibility and passenger comfort, as well as reducing train dwell time between stops.

This work demonstrates how re-thinking the design of public transport can have implications for ease of travel in the future. Commuters’ relationships with train carriages have fundamentally changed over the past decade, with the train carriage becoming a shared space of private communication and media consumption. This change is yet to be reflected in the design of train carriages or understandings of commuter behaviour.

Project members

Tom Chandler
Selby Coxon
Dan Black
Elliott Wilson
Brent McKee
Su-Yiin Lai
Kingsley Stephens

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