Background.

Challenges for modern traffic management solutions.

The UN predicts that by 2030, metropolitan areas are projected to house 60% of the world’s population.

Managing traffic and optimising traffic signals have long relied on traditional modelling and forecasting. Real-time events, changing conditions, and evolving mobility patterns mean existing systems can no longer keep pace and adapt to new needs in urban environments.

Two main problems have always had to be overcome; congestion and road safety. They remain to be an issue to this day. Now, a third challenge has been added; environmental protection. Congestion in urban environments needs to be managed to maintain our health in cities.

Intelligent Transport Systems (ITS)

Modern traffic management solutions monitor and control different types of traffic using digital technology such as Automation, Artificial Intelligence (AI), Machine Learning (ML) and Floating Car Data (FCD).

ITS can help to make traffic more efficient and reduce fuel consumption. ITS can also be used to make other modes of transport, such as public transport, more attractive.

Brief.

Team shape and design goal.

SWARCO are internationally recognised for their solutions in Traffic Telematics, Highway and Tunnel Management and Port Solutions.

At the time, the client was looking to modernise their approach to all digital solutions but our focus (as part of a pre-sales exercise) would be Urban Traffic Management, where the company’s commercial offering was less established.

We were a team of three; including 1x Head of Engineering, 1x Senior Visual Designer and 1x Senior UX Designer.

The client brief:

Design a conceptual solution that helps Traffic Management Operators and Data Analysts to maintain the flow of traffic and reduce(or avoid) congestion; thereby increasing traffic safety, efficiency in logistics and reducing fuel consumption.

To achieve these and other goals, the solution, as a modern traffic control platform, must perform several functions:

Real-time traffic observation.
Traffic data collection.
Diagnostics.
Incident report logging.
Real-time visualisation.

The output was to be a design prototype only but should consider the future integration of AI and ML in order to automate and improve the outcome of incident response.

Design.

The solution combines data from various systems to create a holistic view of the city‘s current traffic situation, future forecast, notable events and incidents, in various modes of transport. Data is retrieved using an open API to integrate with other systems.

Monitor.

The traffic information provided by signal heads, sensors, video cameras, controllers and detector stations is aggregated and normalised to provide a real-time overview of the current traffic situation - and to be able to react to it if necessary.
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The primary dashboard serves to provide a birds-eye view of the city, including a ‘health bar’ of indicators that summarise collisions, ‘logjams’, environmental incidents and anything that can have an adverse or positive impact on traffic flow. Future event popularity predictions are provided for more efficient planning.

By leveraging Mapbox as a data-visualisation tool, the solution would extend the app’s data-source coverage for more reliable traffic representations. Users can aggregate activity, density and movement over time at the city, regional, or country scale.

Log In.

Dashboard: Infrastructure Status View

Wireframe Examples: Dashboard, Map, Scenario Builder.

Map City View: Los Angeles/ Status Summary

Map City View: Incident Zoom

Map City View: Notification

Incident Focus: Traffic Density Forecast

Respond.

Users in the traffic control centre receive relevant information regarding traffic irregularities, e.g., accidents, at an early stage and thus can proactively initiate necessary steps to improve the city’s traffic flow.

Data such as emission counters, traffic light sensors and connected IoT sources help to predict variations from the ‘typical’ or normal state. The user is empowered to start preventative traffic management actions to prevent congestion and escalation.

Operators are notified and, if configured to do so, predesigned automated procedures to manage incident situations will be presented.

Incident Focus: Automated Response Suggestion

Analyse.

Users in the traffic control centre receive relevant information regarding traffic irregularities, e.g., accidents, at an early stage and thus can proactively initiate necessary steps to improve the city’s traffic flow.

Data such as emission counters, traffic light sensors and connected IoT sources help to predict variations from the ‘typical’ or normal state. The user is empowered to start preventative traffic management actions to prevent congestion and escalation.

Operators are notified and, if configured to do so, predesigned automated procedures to manage incident situations will be presented.

Analytics Dashboard.

Scenario Builder: Dashboard

Scenario Builder: Create New Scenario

Build.

Responses to real-time incidents and suggestions, or to hypothetical (typical) scenarios, can be created, customised and tested within the Scenario Builder.
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The user can change variables such as weather, time of day, traffic flow density, parking capacity etc. The system will offer the ability to simulate the effect of additional bus lanes, building works, and emissions limit alterations for example, to urban mobility.
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In this scenario, we are using the use case of a known event coming up next month which is forecasted to have a large attendance, severe traffic conditions and is situated close to LA Airport.