RWR4015

Traffic Simulation Modelling

Use traffic simulation as a planning decision tool—model, test, and justify better designs.

Traffic Simulation Traffic Signal Planning Environmental Analysis Traffic Impact Study

Instructor: Ahmad Mohammadi · RoadwayVR

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Preview

Short preview of the course workflow (network → demand → signals → KPIs).

Course Overview

How the course is structured and what it prepares you to do.

Course overview

This course is organized as a series of practical planning modules. Each week introduces a key capability used in transportation planning studies—network building (GIS/OSM), demand modelling, signal control, mixed traffic/CAV scenarios, environmental assessment, ITS concepts, and 3D/VR visualization. Weekly hands-on sessions are self-contained and produce small outputs (e.g., a working model, a scenario test, or a KPI summary). In the final weeks, students assemble selected components into a mini alternatives analysis and communicate results through a short demo video and a public-facing project page.

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Course Outline

What you’ll learn and how you’ll be evaluated.

Learning Goals

  • Explain where simulation fits in transportation planning studies
  • Build/import road networks using GIS/OSM data and check model readiness
  • Define and verify traffic movement, volume, and speed assumptions
  • Design and test intersection control strategies (unsignalized, fixed-time, actuated)
  • Model mixed traffic and CAV scenarios and compare alternatives
  • Evaluate alternatives using planning KPIs (delay, queues, travel time, emissions/energy)
  • Communicate results with clear tables, plots, and evidence-based recommendations

Assessment (example)

  • In-class Deliverables (15%)
  • Transportation News Brief (each student presents once) (10%)
  • Final Project (35%)
  • Assignments (10%)
  • Midterm Examination (25%)
  • Participation (5%)

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Topics

Week-by-week topics and materials (theory + hands-on) are listed below.

Week Topic (Theory + Hands-on) Materials
1
Introduction to Traffic Simulation
Theory: What traffic simulation is, why it’s used, examples of planning studies, course overview
Hands-on: Set up the simulation software; explore files/UI; build a simple network; add traffic demand; test unsignalized vs signalized intersections
2
Traffic Flow & Driver Behavior Models
Theory: Network elements, vehicle characteristics/dynamics, car-following and lane-changing, fundamentals (flow–density–speed)
Hands-on: Create/import networks; add volumes; define vehicle types; compare behavior settings for cars, bikes, and scooters
3
Traffic Signal Planning in Simulation
Theory: Signalized vs unsignalized control, phases/cycle/lost time, fixed-time vs actuated control, basic optimization concepts
Hands-on: Build a signalized intersection; define phase programs; test fixed-time vs actuated timing
4
Network Modelling with GIS & OSM
Theory: GIS basics, why GIS matters for simulation, what network details affect results
Hands-on: Intro to QGIS; download/prepare GIS/OSM data; import/build a network from GIS/OSM layers
5
Demand Modelling & Route Assignment
Theory: Calibration basics for planning, defining movement/volume/speed assumptions
Hands-on: Create routes/flows; load volumes; verify movements and speeds in the simulation
6
Mixed Traffic Planning: AVs & Human Drivers
Theory: CAV fundamentals, automation levels, mixed-traffic impacts, how simulators represent AV behavior
Hands-on: Create manual vs AV classes; test penetration rates (0%, 25%, 50%); compare alternatives using KPIs
7
Environmental Analysis: Energy & Emissions
Theory: How operations affect energy/emissions, ICE vs EV basics, emission modelling concepts, output meaning/limits
Hands-on: Enable energy/emissions outputs; compare ICE vs EV scenarios; evaluate how signals/congestion affect results
8
Midterm (Paper-Based): Model Reasoning
In-class: Interpret printed outputs (counts, speeds, travel times, queue plots, snapshots) to:
  • Diagnose likely causes of mismatch
  • Propose calibration actions (what to change and why)
  • Justify validation decisions (what evidence is sufficient)
9
Intelligent Transportation Systems in Simulation
Theory: ITS overview, sensing/data collection, examples and use cases, AI in ITS, smart signal control concepts
Hands-on: Implement a basic data-collection workflow; prototype a smart control concept in the simulation
10
3D Traffic Simulation I
Theory: Why 3D visualization, core concepts, game engines for planning
Hands-on: Launch a game engine scene; build a basic 3D environment; visualize the simulated traffic in 3D
11
3D Traffic Simulation II: VR Applications
Theory: VR fundamentals, VR in planning, driver simulators, future directions
Hands-on: Build a more complex VR traffic scenario and run a demo
12
Portfolio & Communication
Theory: Communicating results to decision-makers (story + evidence + recommendation)
Hands-on: Final project page + demo video + screenshots + KPI tables/plots

Resources

Software

  • Traffic simulation software (microsimulation)
  • GIS tools for network building (QGIS / OSM)
  • Optional: game engine tools for 3D/VR visualization