Aimsun Next Tutorials Guide

We’re launching a new series of free video tutorials for using Aimsun Next mobility modeling software. No experience is necessary – these tutorials are designed for total beginners to follow. In this introduction to the series, Dimitris Triantafyllos outlines which topics we will be covering.

New to Aimsun Next?

Let’s get started! In this video, we’ll show you how to download the software and take you on a guided tour around the welcome page and user interface. For a step-by-step guide to installing Aimsun Next, go here: www.aimsun.com/aimsun-next-installation-guide/

Create a complete network from scratch: learn how to open Aimsun Next and create a new project, then import a map from OpenStreetMap and apply background images.

Learn how to create the geometry of a road network.

The goal of these model-building exercises is to start from zero and create a complete traffic-network model with all the data you need to run a microscopic simulation.

• Base a model on a template and a background image.
• Build network elements including sections, nodes, lines, detectors, variable message signs (VMS), and public transport stops.
• Define the following key elements: a control plan for traffic lights, public transport lines and timetables, reserved lanes for buses, a traffic state, centroids, OD matrices, and traffic demand.
• Create a scenario and an experiment to use to run the simulation.

The goal of these model-building exercises is to start from zero and create a complete traffic-network model with all the data you need to run a microscopic simulation.

• Base a model on a template and a background image.
• Build network elements including sections, nodes, lines, detectors, variable message signs (VMS), and public transport stops.
• Define the following key elements: a control plan for traffic lights, public transport lines and timetables, reserved lanes for buses, a traffic state, centroids, OD matrices, and traffic demand.
• Create a scenario and an experiment to use to run the simulation.

In Aimsun Next there are two ways to represent demand: one is through traffic states and the other is through origin-destination matrices (often shortened to ‘OD matrices’). In this video we will look at creating traffic states.

The goal of these model-building exercises is to start from zero and create a complete traffic-network model with all the data you need to run a microscopic simulation.

• Base a model on a template and a background image.
• Build network elements including sections, nodes, lines, detectors, variable message signs (VMS), and public transport stops.
• Define the following key elements: a control plan for traffic lights, public transport lines and timetables, reserved lanes for buses, a traffic state, centroids, OD matrices, and traffic demand.
• Create a scenario and an experiment to use to run the simulation.

The goal of these model-building exercises is to start from zero and create a complete traffic-network model with all the data you need to run a microscopic simulation.

• Base a model on a template and a background image.
• Build network elements including sections, nodes, lines, detectors, variable message signs (VMS), and public transport stops.
• Define the following key elements: a control plan for traffic lights, public transport lines and timetables, reserved lanes for buses, a traffic state, centroids, OD matrices, and traffic demand.
• Create a scenario and an experiment to use to run the simulation.

The goal of these model-building exercises is to start from zero and create a complete traffic-network model with all the data you need to run a microscopic simulation.

• Base a model on a template and a background image.
• Build network elements including sections, nodes, lines, detectors, variable message signs (VMS), and public transport stops.
• Define the following key elements: a control plan for traffic lights, public transport lines and timetables, reserved lanes for buses, a traffic state, centroids, OD matrices, and traffic demand.
• Create a scenario and an experiment to use to run the simulation.

The goal of these model-building exercises is to start from zero and create a complete traffic-network model with all the data you need to run a microscopic simulation.

• Base a model on a template and a background image.
• Build network elements including sections, nodes, lines, detectors, variable message signs (VMS), and public transport stops.
• Define the following key elements: a control plan for traffic lights, public transport lines and timetables, reserved lanes for buses, a traffic state, centroids, OD matrices, and traffic demand.
• Create a scenario and an experiment to use to run the simulation.

How to visualise results in Aimsun Next, from viewing data for a single vehicle to creating thematic maps to present results with different labels and diagrams.

Using the example of a football match in Barcelona, we’ll observe the impact of spectators leaving the stadium after the game on traffic in the network, then we’ll find traffic management actions to mitigate that impact.

Crating post-event mitigation strategies in the simulation

• Create policies for changing the destinations of vehicles in response to network conditions and events.

• Define strategies and policies to divert traffic, close turns, and reduce congestion. These strategies will involve police actions, VMS signs, traffic control plans, and conditional triggers.

• Create periodic incidents in a road section.

• We’ll use the example of a football match in Barcelona, where departing spectators impact traffic between 20:00 and 21:00h. Our task is to observe if all vehicles can leave in a timely manner and how we can mitigate their impact on traffic in the network.

How to use strategic modeling tools in Aimsun Next.

The basic macroscopic modeling tools in Aimsun Next

Run a microscopic simulation that contains embedded pedestrians.

• Scenario Data Comparison

• Network Attributes Override

• Scenario Revision

• Geometry Configuration

• Using a Static Assignment to Verify Real and Simulated Data

• Defining a Subnetwork Study Area and Running a Static Traversal

• Checking Detector Coverage

• Extending the OD Matrices Based on Traffic Measurements

• Adjusting the Subnetwork OD Matrices

• Creating a Profiled Demand with a Static OD Departure Adjustment

• Running a Dynamic User Equilibrium (DUE) Experiment

• Running a Microscopic Stochastic Route Choice (SRC) Scenario

• Running a Meso-micro Hybrid SRC Scenario

• Running a Macro-meso Hybrid Simulation

• Priority

• Actuated Control

• Priority

• Actuated Control