A complete decision support solution for real-time transportation 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: traffic management centers can be proactive rather than reactive, predicting when and where congestion will happen and taking preemptive action to stop traffic jams before they even start.
- Real-time and predictive traffic information for road users: improve the customer experience and get higher satisfaction ratings.
- Smart motorway management: integrate real-time information, communication, and traffic management to ensure safer, faster, less polluting journeys on motorways and arterial roads.
- Predictive signal plan scheduling: select the signal plan that best mitigates 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: reduced 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: systems are in place to keep emissions within legal thresholds and improve air quality.
- Dynamic tolling: a framework for planning and operating user charging.
- Predictive policy-based prioritization: adapting 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.
Smart, sustainable motorways
M4 Smart Motorway, Sydney
Client: Transport for New South Wales
Aim: Implement Australia’s first simulation-based predictive solution for faster, less polluting journeys on the M4 Smart Motorway
Aimsun Live helps emulate the M4’s ITS policies, like ramp meters, variable speed limit, and variable message signs, providing analytical predictions, continuous monitoring, and on-demand response plan evaluations, with one-hour forecasts set at 15-minute intervals.
Aimsun Live can also emulate the Sydney Coordinated Adaptive Traffic System (SCATS) traffic signal logic to read detection data and real-time traffic signal controller status in over 700 intersections.
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%.
Transitioning from other solutions to Aimsun Live
Start small, evolve to match your resources and strategic objectives.
The Simulation Model is a virtual replica of real traffic scenarios.
The Simulation Model is a virtual replica of real traffic scenarios.
Proprietary Data is non-public data, important enough to give a competitive advantage.
A combination of detection data and traffic-control data.
A combination of detection data and traffic-control data.
A combination of detection data and traffic-control data.
Get in touch with us today at info@aimsun.com and we can start the conversation.
Custom solution design
From autonomous vehicle stack testing to building a business case for a ride-sharing service, Aimsun can do it all. Get in touch and tell our solution design team what you need.
To learn more about Aimsun’s modular platform, click here.
Custom solution design
From autonomous vehicle stack testing to building a business case for a ride-sharing service, Aimsun can do it all. Get in touch and tell our solution design team what you need.
To learn more about Aimsun’s modular platform, click here.
