Intelligent
transport
My Role: Service Designer
End-to-end design for an IoT solution for transport. Design of interconnected and interdependent systems consisting of physical and digital artifacts, human actors, technology touch points, and infrastructure that offer a holistic user experience.
Strategy & Concept
Transport vs Data
The problem
The primary challenge, transport operators facing, is obtaining a precise and reliable measurement of real-time passenger demand and understanding not only passenger behaviours in their different settings
but also the meaning behind those behaviour patterns.
The transport sector has a torrid relationship with IT and data.
Infrastructure is chunky
Data solutions are inherently incremental
Transport and data struggle to live in harmony because it’s hard to reconcile a chunky industry with an incremental industry.
Showcases
A bit more about rail industry in the UK
The core “tell me where the trains are” functionality in the 70s was augmented by the “tell me how late the trains are and why” functionality.
None of these systems come with anything resembling a human-friendly user interface (except perhaps CCF includes some diagrams) and they all rely on some combination of containerisation, virtual machines, and a diminishing pool of legacy coders to keep them running in the present day.
Approach to the problem
Some presentations require more steps to compute and inference. The mental model of people incite them to use new technologies as they would use old physical systems.
Transform the service delivery experience for both customers and organisations
Improve digital, physical and social experiences with human-centered design approaches to service delivery
Reduce complexity of system disconnects and causes of customer, service provider and stakeholder pain
Collecting data from various ecosystems, and experiment with different user groups to make sense of the data using inference, interpretation, analysis and synthesis. Then, addressing all the inductive and deductive reasoning to point toward a design.
Integrating passenger data from both the platforms/stops and the carriages/vehicles in real-time has multiple benefits including:
• Targeting service delivery with real-time passenger demand
• Better space and route planning
• Limiting disruption, congestion and improved resourcing
• Improved customer satisfaction from passengers through better journeys
• Enhanced station facilities management and energy saving
All on the same page
App Design
Capturing user's motivations, intentions, behaviours and goals
Transport operators are, rightly, run predominantly by engineers, often with immense pressure to demonstrate value for money and efficiencies. Given the choice, they will generally invest in better physical infrastructure over data infrastructure.
People who work on the railways are massively dedicated to their work, and passionate about delivering a better service to the public.
They work to squeeze every last drop of efficiency out of Britain’s ageing rail infrastructure.
But this relentless focus on making the infrastructure work better often blinds the organisation to the important contribution made by systems.
IT and data can’t, on their own, make the trains run efficiently and on time.
And yet relying on aged systems is causing loses of millions every year in performance penalties, inefficient working practices, and unexplained delays.
Navigation
Dashboard design should make use of such perceptual abilities to help viewers while visual foraging.
The 2 variables, passanger data from the trains and occupancy data from the platforms, are seen on the same map which allows users to make sense of the interconnected data and make comparisons.
Making sense of the data
We are really good at recalling places because as hunter-gatherers, we didn’t need to remember numbers and words, but we needed to remember where things were.
Following the information scent
Our ability to pick up the 'scent' of information with personal significance is greatly reduced when all areas of the visual array appear the same. The viewer then has to scan the display until they receive a visual clue to the whereabouts of the most relevant information. When the design fails to draw the user's attention to relevant data, the scanning process is reduced to a 'item-by-item' strategy, where all areas of the display are consciously attended to, which is cognitively demanding and likely to impact on the viewing experience.
Recall is a much more effortful memory process than recognition, as it requires conscious, cognitive exertion to actively remember where information is in the display. In order to save the user from having to recall data locations the most important, and regularly attended, information should stand out from the rest of the dashboard contents.
Color blind tests & UI style sheets
Passenger Crowd Simulation & Fruin Density
Understanding not only passenger behaviours in their different settings but also the meaning behind those behaviour patterns
In a non-operational environment, we are more in control of the demonstration parameters and can recreate a reasonable range of these ‘real-life examples’ to demonstrate the true capability of the technology through simulation of scenarios that occur in live operational environments.
Counting Interval
London Underground trains only stop at a station for approximately 1 minute in peak times, whilst Intercity train stops can be longer.
Therefore, the toughest test would be to count passengers boarding/alighting within a minute.
Time of the day
Trains are busier at certain times of day than others, i.e. at peak times (morning and evening commutes) compared to off peak (between the commuting periods and at weekends).
Surroundings and its effects
Vibration Acceleration/deceleration and vibration are not primary aspects for the performance of our solution because most passenger movements, including the most critical ones of alighting and boarding, occur when transports are stationary.Environmental Effects of the climate & temperature are investigated in Asia & Europe.
Culture Awareness of needs of the people in different parts of the world. What is normal in other places in terms of transport usage? How are the other people dealing with problems?
The ground truth
When products are tested in different transportation and in different locations in the world, this process will allow data scientists to better understand,
interpret the data collected remotely that has been inferred and adjust the algorithm accordingly.
The passenger boarding/alighting scenarios simulated are influenced by different levels of Fruin crowd density.
The Fruin scale is an accepted standard to describe different densities of people per square foot, depending on an acceptable level of service descending from A (least crowded) to F (most crowded) –
this is illustrated in the table.
Off-peak scenario:
1. Passengers entering or exiting, one passenger at a time, at close following distance.
Peak crowding scenarios:
2. Passengers entering or exiting, two passengers at a time, at close following and side distances.
3. Passengers entering and exiting at the same time, at close proximity following and side distances.
4&5. Passengers entering or exiting, at close following distances, with one or two additional static passengers standing at the doors, inside the train.
6. Passengers walking through the train carriage corridor into and out of the seating area.
The passengers alighting the train at different speeds based on the Fruin level of scale to simulate on/off peak.
Passengers alighting/boarding wearing overcoats/rain jackets with hoods, thermal hats and carrying bags.
Luggage being pulled from behind and pushed in front of passengers, which will also cover the pushchair and bicycle scenario.