Your digital twin for real-time traffic management – operate a complex, large-scale network smoothly and reliably in all conditions.
A complete decision support solution for real-time transportation management. Operate a complex, large-scale mobility network smoothly and reliably in all conditions.
Aimsun Live is a digital twin for real-time traffic management.
It uses live and historical data to simulate and monitor a network and provide on-the-spot forecasts of upcoming traffic conditions. Traffic management centres use these predictions to preempt potential problems and take action to stop congestion before it builds up.
Aimsun Live can be applied in the following use cases:
Stay ahead of congestion
Inform road users in real time
Keep buses moving
Optimise smart motorways
Schedule signals predictively
Measure operational impact
Plan for major events
Respond faster to incidents
Reduce traffic emissions
Adjust tolls dynamically
Designed for Live Network Operations
Predict what’s coming: Near-term forecasts for proactive traffic management.
Compare response plans: Rank interventions by your chosen KPIs.
See the whole network: Fill data gaps and extend visibility beyond detectors.
Connect with your systems: Integrate with signals, control rooms and live data feeds.
Automate operations: Run 24/7 with human-in-the-loop or full automation.
Scale with confidence: Support corridor, city or region-scale operations.
Aimsun Live in Action
Regional highway management
Florida
Client: Florida Department of Transportation (FDOT)
Purpose: Predict the effectiveness of response plans to mitigate highway congestion at a regional level
- Detects current incidents and congestion across the regional network
- Simulates response plans in real time
- Scores and ranks options against selected performance metrics
- Supports proactive deployment before congestion worsens
Emissions management
Oxfordshire, UK
Client: National Highways
Purpose: Use intelligent transport systems to improve traffic flow and support emissions management.
- Created the UK’s first county-wide real-time traffic and emissions prediction model for Oxfordshire
- Integrated live traffic data with air quality monitoring and dispersion modelling
- Forecast traffic and nitrogen dioxide, NO₂, conditions up to one hour ahead
- Compared alternative traffic management strategies against flow and emissions KPIs
Bus reliability
Tees Valley, UK
Client: Tees Valley Combined Authority
Purpose: Improve bus reliability with an automated traffic digital twin that can detect disruption and trigger real-time interventions.
- Predicts traffic and bus conditions up to 60 minutes ahead
- Identifies buses at risk of delay before problems escalate
- Triggers automated, pre-approved signal timing plans
- Improves reliability at corridor level, not just for individual buses
- Helped buses return towards normal speeds within 15 minutes of intervention
- Cut delays for all traffic by nearly 14% in summer 2025 trials
- Recognised as the UK’s first region-wide automated Traffic Digital Twin connected directly to on-street traffic signals for automated intervention
