SYNCHROMODE | From chaos to coordination: how AI and simulation are transforming road maintenance
How AI and simulation can optimise roadworks management to reduce impact on traffic flow.
Innovation blog
Discover how data science and research at Aimsun support the deployment of transport management and new mobility solutions.
Data science blog posts
Machine Learning for Traffic Forecasting: A Practical Approach Deployed in the Future Road Lab of the C-32 motorway in Spain
Aimsun presents a new traffic forecasting approach that combines machine learning with online learning to adapt in real time. Deployed in Abertis’ Future Road Lab on a 50km stretch of the C-32 motorway near Barcelona, the system supports safer, more sustainable traffic management.
Enhancing Road Safety and Efficiency with Speed Recommendations
Nuria Toribio explores how advanced traffic management tools detect speed drops and provide progressive speed adjustments.
Towards ML-assisted traffic simulation
Machine learning can assist traffic simulation systems and reduce computational effort by providing network-wide traffic state estimation under unseen conditions.
How will ITS contribute to machine learning?
In the last post we discussed the current trends in Machine Learning (ML) and the need to go beyond big data. But how does this affect the fields of ITS and smart cities?
Is this the death of big data?
OK, big data is not dead, but the AI community is already moving beyond it and towards a new AI paradigm.
How to use random forests to predict mobility patterns
Supervised learning can help us to train our model to predict the right mobility patterns.
Understanding mobility using unsupervised learning
Unsupervised learning is a great tool for data analysis, particularly for understanding how mobility has changed due to COVID-19.
Metric selection for incident detection systems
Classification problems with highly unbalanced datasets, such as incident detection, pose the trade-off between true positive rate and false negative rate.
How to extract patterns from traffic data for better insights into mobility
Mobility patterns are a cornerstone of mobility demand modelling; clustering helps us extract usable daily patterns from huge sets of traffic data.
AI alone is not enough for real-time traffic management
The power of combining AI techniques with simulation in real time for accurate predictions and effective response plans under any conditions.
Mobility pattern prediction
Unlike purely data-driven methods, a simulation-based approach enables prediction of traffic states under recurrent conditions but also to predict the impact of incidents or changes to traffic control plans.
What is a digital twin?
The phrase “digital twin” has become ubiquitous in the field of transportation, but what does it really mean?
Deeper than Data
What is the value of data analytics in the mobility sector? The usual starting place is to look at historical data to find recurrences and trends but if you have real-time data feeds, then you can go deeper
Research blog posts
SYNCHROMODE | From chaos to coordination: how AI and simulation are transforming road maintenance
How AI and simulation can optimise roadworks management to reduce impact on traffic flow.
Better Bike-Share Planning and Operations with Aimsun Digital Twins
Predict demand for shared city bikes using Aimsun’s AI-powered Mobility Digital Twins – ensure bikes are always where they’re needed most.
The TANGENT Tool for Enhanced Real-Time Multimodal Transport Management
The TANGENT research project developed tools to assist transport authorities and operators in applying coordinated traffic and transport network management.
Innovation Planning for Interurban Transport Management: the Mediterranean Highway Pilot
Can Tradable Mobility Credits be effective, as “digital tolls“, for interurban mobility management? How could DRT services be utilized in an interurban context to further enhance network efficiency?
Seamless Multimodal Mobility – Making it a Reality
The ACUMEN research project team are creating a dynamic, data-driven digital framework for advanced network management. Marcel Sala updates us on their progress.
Testing Autonomous Driving Systems: Co-simulation and Human Driver Calibration
The journey toward fully autonomous driving is an exciting one, with innovations making cars smarter, safer, and more efficient. The EU-funded research project, i4Driving, contributes to this journey by developing a cutting-edge platform designed to test Autonomous Driving Systems (ADS). Alkis Papadoulis presents the latest advancements from the i4Driving team.
Safe integration of active mobility modes into Singapore’s transport ecosystem
Aimsun is part of a pilot project to evaluate options for safely integrating active mobility devices into Singapore’s transport ecosystem.
Automating real-time traffic management for cost efficiency
How automation is helping local transport authorities to reduce the maintenance costs of traffic management systems.
Shaping the Future of Advanced Traffic Management Solutions
Antonio Pellicer, PhD, explains Aimsun’s role in the SYNCHROMODE research project, focusing on enhancing transport network management through data-driven and simulation-based solutions.
More efficient traffic and fleet management
Athina Tympakianaki, PhD, explains the potential benefits to our cities of the CONDUCTOR HE urban transit research project.
Community-aware transport management
Mónica Domínguez, a data scientist at Aimsun, explains the paradigm shift from individual to community-aware transport solutions and how this has guided development of cooperative transport management strategies in the FRONTIER research project.
Road safety for all: how the PHOEBE project is enhancing traffic simulation to forecast infrastructure safety
In 2022, Europe witnessed over 20,000 road fatalities. The European Commission’s ‘vision zero’ aims to eliminate all road fatalities and serious injuries by 2050.
An Extension for Autonomous Vehicle Controllers in Aimsun Next
Aimsun Next has introduced an extension for autonomous vehicle controllers, enhancing the simulation of vehicle behavior in complex traffic scenarios.This blog reviews the extension for the autonomous vehicle controller developed for Aimsun Next within the EU-funded FRONTIER EU Project
Simulation-based and data-driven solutions for enhanced real-time multimodal transport management
How Aimsun contributes to the TANGENT Project by integrating data-driven and simulation-based solutions into different tools and technologies developed within the project, aiming to optimise multimodal transport operations
Seamless door-to-door air travel
How the IMHOTEP research project is using simulation technology to improve airport management and ease the many pain points for customers traveling to and from busy airports.
Real-time simulation training for traffic managers
When Main Roads Western Australia installed a new traffic management system, their staff needed to learn how to use it in a realistic but risk-free environment – simulation training was the perfect solution.
Demand Responsive Transport: flexible tools for planning and operational solutions
The MultiDEPART team developed tools to plan, manage and monitor DRT solutions in Lisbon, Barcelona Metropolitan Area and Thessaloniki, targeting PTAs and facilitating the harmonization and scalability of DRT services across European cities.
Towards agent-based models: simulating multimodal transport systems
How can we explicitly represent, simulate and evaluate within-day behavioural (demand) and operational (supply) dynamics in emerging multi-actor passenger and freight transport systems?
Road safety for all: how transport simulation can help predict and prevent blackspots
Road safety is a major concern for public administrations worldwide: severe injuries and fatalities are not only a human tragedy but also have huge social costs
Towards climate neutrality: integrating public transport with new mobility services
The EU-funded SPINE project employs simulation and data-driven models to virtually assess the impact of new solutions for increasing public transport’s modal share and user satisfaction.
