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Traffic models & simulation

Create a digital twin for simulation to support your planning, programming & network operation tasks

Build a replica model of your road network and travel demand in just a few clicks: defining scenarios, launching calculations, archiving results and replaying simulations at any time.

  • Static & dynamic modeling.

  • Microscopic & macroscopic simulation.

  • Cartographic exploration.

  • Multi-indicator and comparative vision.

Essential insights to prepare future investments, integrate new usages in mobility and choose the best operating strategies.


For an optimal allocation of budgetary, economic and environmental resources!

Traffic model
Traffic model
Traffic model

Using a controlled virtual environment

A digital twin is an object's or a physical process's digital representation in a virtual environment. It can be static or dynamic according to the question it answers. In the field of mobility, using a digital twin is about modeling a mobility system combining the offer (the network, the infrastructure) and the demand (the needs for moving). It reproduces the mobility system from a referent time-period on a given geographical scale (neighborhood, city, urban areas, territories, etc.) exhaustively and integrally based on partial historical data collected from the field. This controlled virtual environment enables the simulation of new situations by projecting one or many physical elements in diverse virtual scenarios. It is then called a simulation digital twin. 

Various applications

  • Evaluate new projets feasibility and their impacts for transportation infrastructures and networks (road mobility, public transportation, shared mobility, soft modes, etc.).

  • Simulate the impact of roads and highways operating strategies on traffic flows and the environment (dynamic traffic management, access control, roadwork operations, etc.).

  • Plan tomorrow's mobility system at the scale of a city, an urban area or a territory regardless of the transportation mode (private car, public transportation, bicycle, etc.).

  • Rethink the urban road mobility scheme (traffic plan, traffic lights control optimization, etc.).

A reliable, robust and cost-effective solution

  • Help the decision making at both  strategical level (planning, programming) and operational level (traffic operations).

  • Build a multi-scale vision of impacts (microscopic or macroscopic) and also multi-criteria (service level, delays due to traffic jam, environmental pollution, etc).

  • Forecast and evaluate scenarios never observed before.

  • Test scenarios requiring expensive financial investments or a too complex  deployment to be tested in the real world.

  • Evaluate the operational efficiency of a specific or planned measure and optimize it if necessary.

Prediction & traffic operations

Road traffic management
Road traffic management
Road traffic management

Predict future traffic conditions, travel times or size the most suitable offer

Integrate a set of ready-to-use tools and indicators to forecast the most realistic possible conditions in the short, medium or long term.

  • Service level, journey time, traffic volumes & speed.

  • Global vision on the network or on a route.

  • Analysis and selections by time periods.

  • Comparison of situations.

A real control tower to optimize the programming of operations, gain in agility in the management of exceptional events and better synchronize the players involved.


To always offer the best level of information and service!

Various applications

  • Deciding on the right road operating measures to use and on the right roadwork program to minimize the impact on the traffic conditions and the environment.

  • Testing and evaluating traffic management strategies and plans to anticipate and face exceptional incidents efficiently (accidents, weather events, peak times, etc.).

  • Objectifying key characteristics of the traffic flow offered by the road infrastructures (traffic volumes, speed, fundamental diagram, etc.) by relying on existing historical data.

  • Predicting on short and mid-term traffic conditions and travel times to optimize operations and inform users.


A unique goal: anticipating and predicting

  • Offering a dynamic and macroscopic vision of the traffic flow

  • Relying on high-speed advanced algorithms able to give results in a few seconds on large scale networks of dozens of miles.

  • Predicting traffic jams and travel times evolution with reliability and efficiency.

  • Bringing quick, synthesized and intelligible answers to anticipate and guide the decisions on operations.

Carbon footprint & pollutants

Evaluate impacts of new projects, optimize low carbon strategies

Evaluate, analyze and optimize CO2 and pollutants emissions of road mobility to decrease carbon footprint and environmental impacts.

  • Assessment of current situation.

  • What-if scenarios comparison.

  • Various dimensions: CO2, NOx, fine particules, noise.

  • Dashboards and map based views.


Key insights to inform decisions with relevant and realistic indicators to deploy environmental friendly solutions in traffic management or mobility policies planning.


For an even more sustainable mobility!

Calculating carbon footprint for business
Calculating carbon footprint for business
Calculating carbon footprint for business

Solutions integrating advanced models

The road mobility is at the core of many environmental challenges: its greenhouse gas emissions contribute to climate change and impact negatively the air quality in urban areas. The road traffic contributes to over 30% of the global pollution. Evaluating carbon and pollutant emissions is now a major challenge for road infrastructures and road operations projects, as well as for mobility strategies and policies. Integrating traffic modeling and simulating tools with CO2 and pollutants emission models is a key solution to bring a complete and objective vision of the environmental impacts.  

To reduce environmental impacts of road mobility

  • Enhancing the vision coming from a limited network of environmental and noise sensors deployed on the field.

  • Integrating multiple variables of a complex problem (engines specifications from the current car fleet, emissions factors, traveled distances, flow speed, etc.) to objectify phenomenons.

  • Comparing alternate scenarios by relying on robust and proven scientific methods to calculate CO2, pollutants and noise emissions.

Neovya Mobility by Technology

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