l4 aimsun overview and algorithms
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AIMSUN
Advanced Interactive Microscopic
Simulator for Urban and Non-urban
Networks
Adopted from Clara Fang/ Ondrej Pribyl
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Outline
Introduction
Practical Applications
Capabilities
Simulation Requirements Simulation Inputs
Simulation Outputs
Function Limitations
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Introduction
Developer Transportation Simulation Systems (TSS), Barcelona, Spain
www.aimsun.com
AIMSUN Ver 4 is integrated with GETRAM SimulationEnvironment
Generic Environment for TRaff ic Analysis and Model ing
Traffic Network Graphic Editor (TEDI)
AIMSUN
AIMSUN 3D
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GETRAM
External Applications
ShortestRoutes
Component
Network
Database
TEDI
GraphicalEditor
Costs
Routes
GETRAM
AIMSUN
-
User Interface
AIMSUN2
KernelGETRAM
Extensions
Simulated
Data
Control &
Management
Actions
EMME/2
TRANSYT
SCATSInterfaces
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Capabilities
Urban networks, freeways, highways, ring roads,interchanges, roundabouts, arterials and anycombination of them
Public transportation
Traffic incidents Vehicle types
cars,buses, trucks, trains or user-defined
Fixed vs.Dynamic route choice models
Interfaces EMME/2
TRANSYT
3D visualization
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Capabilities
Traffic Control and Management
Traffic signals (NEMA controllers)
fixed-time, semi-actuated, fully-actuated
Adaptive control
Signs
Ramp metering
Green time, flow, delay
VMS
Different message and Starting time
All kinds of detectors
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Simulation Requirements
(1) Network Geometry Vehicles data
(2) Traffic Demand
(3) Traffic Control Plan
(4) Public Transportation (optional)
(5) GETRAM Extensions (optional)
Modelling parameters (Default values areprovided)
Scenario
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Simulation Inputs
(1) Network Geometry
Sections (links)
length, width, number of lanes, speed limits, grade, etc.
Nodes (Junctions and Joins)
turning movements for junctions
Centroids
traffic source, sink or both
Vehicles type, size, vehicle characteristics
Detectors, VMS, etc.
Map of the area (optional)
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TEDI: a user friendly graphic interface for building models
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Network Model
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Examples of Sections and Polysections
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Section Properties
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Examples of Joins
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Intersection - Turning Movements
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Centroids
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Vehicle Types
Transfer between Library and Model
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Importing backgrounds as .jpg, .bmp, .tif ,...files
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Simulation Inputs
(2) Traffic Demand
Result Based - Traffic Flows & Turning
Proportions
generated at origin centroids and input into the network
through the sections connected to the centroid distributed around the network in accordance to the
turning proportions defined in each section of the
network.
Route Based - O/D matrix and Shortest Paths
generated at origin centroids and input into the networkthrough the sections connected to the centroid
distributed following shortest paths from input section
to destination centroid.
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Traffic Flows and Turning Proportions
Define State
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Simulation Inputs
Signal
Signal types
Signal groups (turning movements are grouped)
Phases sequences and associated signals groups
Duration of each phase Offset
Actuated parameters
Unsignalized
Priority rules - Yield and Stop sign Parameters that affect the Gap-acceptance model
Ramp metering
Control parameters (green time, flow or delay time)
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OD Matrix
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Traffic Generation
Arrival Distributions
Exponential
Route based modeling
Uniform
Result based modeling
Normal
Constant
Other Arrival Models ASAP (as soon as possible)
External (GETRAM Extensions)
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Simulation Inputs(3) Traffic Control
Signal
Signal types
Signal groups (turning movements are grouped)
Phases sequences and associated signals groups
Duration of each phase Offset
Actuated parameters
Unsignalized
Priority rules - Yield and Stop sign Parameters that affect the Gap-acceptance model
Ramp metering
Control parameters (green time, flow or delay time)
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Typical signal plan
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Uncontrolled
Fixed
External Actuated
SCATS
Traffic Signal Control Types
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Traffic Signal Control Plan
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Simulation Inputs(4) Public Transport (Optional)
Public transport lines
Routs
Reserved lanes
Bus stops
Vehicle type
Timetables
Departure frequency
Fixed schedule
PT Plan
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Simulation Inputs
(5) GETRAM Extensions (Optional)
Application Programming Interface (API)
Develop external applications (traffic control
systems) Access to the statistical data produced by
simulated detectors, VMS or ramp metering
Keep track of a guided vehicle throughout the
network and directly control a vehicle movement Programming in C/C++,or using Python scripting
language
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GETRAM extensions
Principle of data exchange
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Simulation Inputs(6) Modelling parameters
Global Reaction time, queue up speed and queue leaving
speed, etc.
Car-following model
Maximum number of vehicles, maximum distance, etc.
Lane changing model Percent overtaken, percent recover, etc.
Local Speed limit, turning speed, visibility distance at
intersection, distance zone, etc.
Vehicle Attributes
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Simulation Algorithms
Vehicle Arrivals
Vehicle Attributes
Global Simulation Parameters
Car-Following Lane Changing
Gap Acceptance
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Vehicle Arrivals
User may select among the following models: Exponential
Uniform
(Truncated) Normal
ASAP Constant
External Source
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Vehicle Attributes
Length
Width (considered for graphics only)
Maximum Desired Speed
Maximum Acceleration
Normal Deceleration
Maximum Deceleration
Speed Limit Acceptance
Minimum spacing
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Global Simulation Parameters
Turning Speed Effects of Grade on Vehicle Performance
Drivers reaction time - also the simulation timestep - affects capacity!
Reaction time when vehicle is stoppedaffectsqueuing
Speed to join the queue
Speed to depart from a queue
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Models of vehicle movements
The vehicle movements is computed based onparticular sub-models such as
Car-following model
Lane changing
The vehicles are aiming to get to the desired speed
But are constrained by environment
Adjacent vehicles, speed limits, signal light,
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Principle
In every simulation step (time based triggering)are the parameters recomputed according tofollowing principle:
if (it is necessary to change lanes) then Apply Lane-Changing Model
endifif (the vehicle has not changed lanes) then Apply Car-Following Model
endif
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Car-Following
Based on Gipps Model, which is a function of: Type of Driver
Geometry of the Section
Uses a 2-lanes car-following model to consider the effects
of adjacent lanes as a function of: Area to be considered
Number of vehicles in area
C t ti f l ti d d l ti
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Computation of acceleration and deceleration (SourceAIMSUN Manual)
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Lane Changing
Uses the Gipps Lane Changing Model It is based on:
Necessity of Lane Change
Desirability
Feasibility
Algorithm asks each vehicle at every update: Isit necessary, desirable, feasible to change lanes?
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Gap-Acceptance
Used to answer the question: Is it feasible to changelanes?
Evaluates gap to both upstream and downstream vehicles.
There are segemetn sections defined in order to achieve
more representative behavior
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Gap acceptance model (Source AIMSUN Manual)
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Simulation Outputs
Statistical measures
In network, O/D matrix, stream, section,
turning, type of vehicles level
Mean Flow
Density
Mean Speed and Harmonic Mean Speed
Travel Time
Delay Time
Stop Time and Number of Stops
Queue Length (Mean and Maximum)
Total Travel Length
Fuel Consumed and Pollution Emitted
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Simulation Outputs
Storage of simulation outputs ASCII files
Database (e.g. Microsoft Access)
User- defined time interval
Multiple runs Record simulation
Comparisons of two sets of time series data(Validation)
Provides charts and statistical indicators e.g., flows measured at a detector at each interval
(5 minutes) vs. field data
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Function Limitations
No signal optimization
No control delay output
No signal phase switch information output
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Thank you !
Questions & Comments?