Case study: iMOVE 60 - Integrated Connected Data for Safer, More Efficient Traffic Management

iMOVE60 project:  Integrated Connected Data for Safer, More Efficient Traffic Management

**See.Sense contribution to this project is short-listed in the ITS UK Better Mobility through Technology Award for 2025**

The iMOVE60 project — Integrated Connected Data for Safer, More Efficient Traffic Management Operations — is world-leading research by a multi-party government led team in Australia, which examines untapped data sources with the potential to revolutionise transport management. Examining how to better leverage existing data and technology; and embracing the opportunities offered by connected vehicles; the project determined how data will deliver safer, faster and more efficient road travel, shaping a future of seamless mobility. 

See.Sense contributed the bicycle AI-enabled sensor dataset used in the project’s cycling safety and efficiency analysis. This dataset, collected from around 1,000 cyclists in Melbourne between 2021 and 2024, provided high-resolution insights into cyclist behaviour, safety risks, and infrastructure performance.

This project builds on our successful UK deployments with Transport for London (TfL) and the Royal Society for the Prevention of Accidents (RoSPA), work which earned See.Sense the Prince Michael International Road Safety Award.

Through anonymised aggregated data, See.Sense’s technology identified:

• Surrogate safety measures such as harsh braking, swerving, and abnormal events, correlated with high-risk locations.
  

• Road surface quality assessments derived from vibration analysis, pinpointing maintenance needs.
  

• Cyclist flow and delay patterns across different road types, showing how infrastructure impacts journey efficiency.
  

"Incorporating cyclist movement and braking data revealed hidden safety risks and flow inefficiences, providing actionable insights for intersection and infrastructure design" 

How cycling data made an impact

As part of the project, See.Sense sensor data delivered real-world insights into cyclist behaviour, safety, and journey efficiency. By combining this with other traffic data, the project uncovered valuable findings to help design safer, more efficient streets.

Bicycle safety and risk identification

Cycling safety is often compromised at busy intersections and high-traffic areas. Key findings included:

• Crash risks at intersections: 59% of bicycle-involved crashes occurred at intersections.

• Harsh braking and swerving hotspots: See.Sense data was a strong indicator of potential crash sites, effectively identifying hotspots for improvement

• Surface quality insights:  See.Sense data highlighted poor road surfaces, identifying locations needing maintenance to prevent incidents.
  

Figure 1:  Areas of Extreme, High, Moderate and Low Braking in City of Melbourne identified with See.Sense data

Bicycle flow efficiency

Delays and slow speeds are a common challenge for cyclists, particularly in urban centres. The data from See.Sense showed:

• Longer delays at major intersections, especially where car-prioritised signals dominate.

• Better performance on dedicated bike paths, which allowed higher speeds and smoother journeys.

• Cyclist profiles identified through machine learning, revealing patterns across commuter, leisure, and delayed cyclist groups.

Figure 2:  Percentage of Cyclists Stopped in City of Melbourne, identified with See.Sense data

This data was integrated with traffic modelling, SCATS signal data, and other datasets by the University of Melbourne and partners, enabling advanced AI modelling for safer, more efficient multimodal traffic systems.

This project is an excellent example of Better Mobility through Technology by delivering:

1. Improved Safety for Vulnerable Road Users

Traditional safety analysis relies on crash data, missing near-misses and unreported incidents. See.Sense’s dataset provided proactive safety intelligence to identify risks before crashes occur — enabling targeted safety interventions that encourage cycling uptake.

2. Evidence-Based Infrastructure Improvement

Insights revealed where intersection delays, mid-block hazards, and poor surfaces hinder cycling flow and safety. This empowers planners to make data-led upgrades to lanes, intersections, and signal phasing.

3. Integration of Micromobility into Smart City Operations

By combining See.Sense data with connected vehicle and SCATS datasets, the project integrates cycling into multimodal traffic management frameworks, improving the balance between active travel and other modes.

4. Proven and Scalable Approach

The methodology is scalable across cities worldwide. The AI-enabled sensor approach can be deployed rapidly to support other cities seeking to improve cycling safety, uptake, and network efficiency.

Future opportunities for cycling in ITS

Building on these insights, See.Sense data can help shape even smarter traffic management through:

• Optimising signalised junctions: Using average delay and congestion data from cyclists to support multimodal capacity planning.

• Identifying car-bike conflict: Detecting and analysing extreme events where bikes and cars interact unfavourably to prioritise improvements.

• Modelling flow and collision risk: Contributing cumulative cycling distance data to enhance existing traffic flow and collision risk models, particularly on shared road sections.

These opportunities show how cycling data can extend the value of ITS beyond motor vehicles, supporting safer, more balanced urban mobility.

The bigger picture

Prioritising active transport is essential to reduce congestion and emissions while improving public health – and connected cycling data is key to making this happen safely and efficiently.

What’s next?

The findings from this project demonstrate how integrating cycling data into traffic management can unlock real improvements in safety, efficiency, and sustainability. With cycling on the rise globally, now is the time to put micromobility at the heart of intelligent transport systems.

If you'd like to learn more or explore how See.Sense data can support your transport projects, please get in touch. Together, we can help build safer, smarter cities.