Aimsun traffic digital twins provide a high fidelity representation of current- and future- on-street traffic conditions, in real-time. These are typically driven by traffic data from a range of automatic traffic counters including: SCOOT / MOVA loops, computer-vision based camera detection and floating vehicle data.
The project owners wanted to know if the partially tolled Fast Lane running parallel to Highway 1 would remain operational and profitable if they were to double the capacity of the park and ride facility serving the airport.
With the ever-increasing demand for traffic modeling, Townsville City Council (TCC) found that the resources required were getting larger and more complicated by the year, which had a knock-on effect on the technical complication of transferring information.
An Aimsun Live deployment in Oxfordshire, UK with integrated air dispersion modeling.
A video guide to the new features in Aimsun Next for helping planners understand the movement of pedestrians, cyclists, and users of public transportation.
To improve air quality in the city of Wiesbaden, Aimsun Live forecasts combine with the IMMIS emission model and Siemens’ Sitraffic Concert to assess traffic management strategies in real time.
Aimsun Live is the predictive engine that will analyze and forecast the effectiveness of response plans to mitigate congestion.
Aimsun collaborated with the Land Transport Authority of Singapore (LTA) to develop a real-time traffic simulation and predictive system in Aimsun Live.
Aimsun Live is the traffic prediction software at the heart of the NSW Government’s $600m M4 Smart Motorway project. The project uses real-time data, communications and ITS to improve traffic flow.
Queensland Department of Transport and Main Roads commissioned an operational Aimsun Live implementation to assess its accuracy and potential value for future operations planning.
Satellite-generated atmospheric data helps local authorities devise real-time traffic management strategies for reducing pollution levels.
Three-year, EC-backed pilot project to show how prediction tools can help traffic centre operators anticipate and mitigate congestion, particularly at peak times.
Aimsun built and implemented the world’s first simulation-based traffic forecasting system for traffic evacuation and incident response operations in the Madrid traffic control center.
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Aimsun Next 20
Aimsun Next 8.4
Aimsun Next 20
@manual {AimsunManual,
title = {Aimsun Next 20 User’s Manual},
author = {Aimsun},
edition = {Aimsun Next 20.0.3},
address = {Barcelona, Spain},
year = {2021. [In software]},
month = {Accessed on: Month, Day, Year},
url = {qthelp://aimsun.com.aimsun.20.0/doc/UsersManual/Intro.html},
}
Aimsun Next 8.4
@manual {AimsunManual,
title = {Aimsun Next 8.4 User’s Manual},
author = {Aimsun},
edition = {Aimsun Next 8.4.4},
address = {Barcelona, Spain},
year = {2021. [In software]},
month = {Accessed on: Month, Day, Year},
url = {qthelp://aimsun.com.aimsun.8.4/doc/UsersManual/Intro.html},
}
Aimsun Next 20
TY – COMP
T1 – Aimsun Next 20 User’s Manual
A1 – Aimsun
ET – Aimsun Next Version 20.0.3
Y1 – 2021
Y2 – Accessed on: Month, Day, Year
CY – Barcelona, Spain
PB – Aimsun
UR – [In software]. Available: qthelp://aimsun.com.aimsun.20.0/doc/UsersManual/Intro.html
Aimsun Next 8.4
TY – COMP
T1 – Aimsun Next 8.4 User’s Manual
A1 – Aimsun
ET – Aimsun Next Version 8.4.4
Y1 – 2021
Y2 – Accessed on: Month, Day, Year
CY – Barcelona, Spain
PB – Aimsun
UR – [In software]. Available: qthelp://aimsun.com.aimsun.8.4/doc/UsersManual/Intro.html
