A true traffic digital twin for real-time traffic management. Operate a complex, large-scale mobility 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 real-time predictive traffic management solution. It uses live and historical data to simulate and monitor a network and provide on-the-spot forecasts of upcoming traffic conditions in under 5 minutes. Its speed and accuracy mean that traffic management centers can use these predictions to preempt potential problems and take action to stop congestion before it builds up.
Aimsun Live helps transportation agencies save time, money, and effort by assessing conditions and evaluating actions before intervening in the real world.
Aimsun Live – Top benefits
Full digital twin: detailed representation of individual lanes, traffic control devices, vehicles, and traffic management actions.
Real-time traffic management: get response plans ranked in order of effectiveness according to the selected KPIs.
AI can fill in the information gaps: our digital twins can formulate predictions all over the network, even where detectors are not present.
Adapt to new situations: estimate the impact of events that haven’t been experienced in the past.
System automation: Aimsun Live can run continuously 24/7 and, where authorized, deploy traffic management decisions with no human in the loop.
Ultra large scale: city or even regional-scale simulation.
Signal control: connect with emulators of adaptive signal control systems such as SCATS and SCOOT.
Integration: slots into existing traffic management infrastructure.
Customizable measures of effectiveness: align with traffic management policies and strategies.
Machine learning: Aimsun Live keeps improving the accuracy of its forecasts by continuously comparing forecast performances against real field measurements.
Hosting: on-site and cloud-based simulation.
Aimsun has already provided solutions for the most common use cases to many major transportation authorities worldwide, including Transport for London, National Highways, the Florida Department of Transportation, the Land Transport Authority of Singapore, and Transport for New South Wales.
Top use cases include:
- Proactive network management: predict when and where congestion will happen and take preemptive action to stop traffic jams before they start.
- Real-time and predictive traffic information for road users: improve the customer experience and get higher satisfaction ratings.
- Better bus reliability: ensure dependable journey times for public transport users.
- Smart motorway management: integrate real-time information, communication and traffic management.
- Predictive signal plan scheduling: select the best signal plan to mitigate forecasted congestion due to planned or unplanned events.
- Operational benefits realization: develop business cases for network – operations initiatives and resource prioritization.
- Decision support to manage traffic incidents and events: reduce the impact of events on the network.
- Incident response management: reduce the time that it takes emergency services to get to critical incidents.
- Environmental traffic management: keep emissions within legal thresholds and improve air quality.
- Dynamic tolling: plan and operate user charging.
- Predictive policy-based prioritization: adapt network control measures to maintain performance of selected user groups.
Case studies
Regional highway management
Florida
Client: Florida Department of Transportation (FDOT)
Aim: Predict the effectiveness of response plans to mitigate highway congestion at a regional level
Decision support is key to the Central Florida Regional Integrated Corridor Management System (R-ICMS); it helps transport control center operators to detect current incidents and congestion on the regional network, and to develop proactive, on-demand response plans which can be evaluated against predicted conditions and reviewed for deployment across the central Florida transportation network.
As part of the decision support system, Aimsun developed the predictive engine to help operators manage recurring and non-recurring congestion conditions. Requests for evaluations are simulated in real-time and then scored and ranked based on different traffic performance metrics so that operators can choose the best response plan. The simulations find the best responses by evaluating the benefits of the different combinations of re-routed traffic along pre-defined routes. The Signal Optimization Tool allows Traffic Engineers to test and optimize the signal timing plans and corridors throughout the network. Prior to approval, the system runs simulations in an offline environment for a final analysis of the new timings, which includes incurred demand associated with the optimized timings and improved travel times.
Emissions Management
Oxfordshire, UK
Client: National Highways
Aim: Use ITS solutions to improve traffic flow and reduce emissions on the Strategic Road Network and local roads in Oxfordshire.
NEVFMA is the Network Emissions and Vehicle Flow Management Adjustment project.
An offline digital twin was built and then fed with real-time information on traffic volumes (from road sensors) and emissions levels (from EarthSense Zephyr air quality sensors).
The solution gave short-term predictions for traffic flow and emissions over the upcoming 60 minutes, returning KPI data in around 8 minutes.
Wherever necessary, traffic managers used these KPIs to hold traffic in areas that could withstand a short-term pollutant increase and create a green wave through hot spot areas where emissions were higher. Drivers were informed of detours via media and VMS.
Test results showed a potential saving in peak-period emissions of 4 to 14%.
