Integrated Connected Data for Safer, More Efficient Traffic Management

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

The Integrated Connected Data for Safer, More Efficient Traffic Management Operations project aims to assess how integrating existing and emerging vehicle data can enhance traffic control systems in the near term. This supports long-term safety and mobility goals while offering immediate improvements to traffic operations and driver support. Rather than waiting for fully realised connected vehicle ecosystems, the project focuses on leveraging available technology today to create safer, more efficient roads.

The progress report is now available here, with the full report launching soon.

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

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.