AI Blog

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.

What is a digital twin?

The phrase “digital twin” has become ubiquitous in the field of transportation, but what does it really mean?

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.

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.

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.

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Cite Aimsun Next

 

Aimsun Next 23

Aimsun (2023). Aimsun Next 23 User's Manual, Aimsun Next Version 23.0.0, Barcelona, Spain. Accessed on: July. 19, 2023. [Online].
Available: https://docs.aimsun.com/next/23.0.0/

 


 

Aimsun Next 20.0.5

Aimsun (2021). Aimsun Next 20.0.5 User's Manual, Aimsun Next Version 20.0.3, Barcelona, Spain. Accessed on: May. 1, 2021. [In software].
Available: qthelp://aimsun.com.aimsun.20.0/doc/UsersManual/Intro.html
 

Aimsun Next 23

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Aimsun Next 20.0.5

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CY  - Barcelona, Spain
PB  - Aimsun
UR  - [In software]. Available: https://docs.aimsun.com/next/23.0.0/


Aimsun Next 20.0.5

TY  - COMP
T1  - Aimsun Next 20.0.5 User's Manual
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