Computer simulations and models use mathematical representations to imitate and gain insight into real-world systems. Good models rely on feedback loops between inputs, processes, and outputs. Creating accurate simulations involves gathering data, developing algorithms to generate outputs from inputs, validating results, and addressing complexity and assumptions. Traffic and demographic models help analyze transportation networks and population trends over time. Both have benefits like testing scenarios safely but also challenges regarding data accuracy, access, and reliability over long periods.

1. Computer Modeling
and Simulations

2. Computer Simulations
and Models
A simulation is basically an attempt to
imitate reality. Simulation is used in many
contexts, including the modeling of natural
systems or human systems in order to gain
insight into their functioning. A computer
model is the mathematical representation of
the functioning of a process, concept or
system, presented in the form of a computer
program.

3. Feedback Loops
Good computer models are dependent of
feedback loops. Essentially, feedback loops
are the part of the system model that, based
on the current output, allows for response
and / or self-correction to achieve the
desired output.

4. Feedback Loop
Input Process Output
Feedback
Feedback - the response to the output, which
inputs new information into the model to the
desired effect

5. Steps involved in
creating simulations
• Gather and prepare accurate data to reflect the
real world.
• Create mathematical formulas (algorithms) to
generate output data from that which is input.
• Create animations, graphs or other output displays
for the information.
• Verify and validate the data by re-testing the
scenarios to ensure that the same result occurs.

6. Advantages of modeling and simulations
• Safety - able to test or experiment without harming the person
or environment.
• Economic savings from the use of models to design and test
new products before prototypes or the final product is made.
• Projection - can look into the future and highlight potential
impacts and address them before they occur.
• Visualisation - can see and understand relationships. Can speed
up or slow down time.
• Replication - able to look at things under a variety of different
scenarios

7. Disadvantages of modeling and simulations
• The mathematical (computational) calculations are very
complex, maybe too complex, to simulate 'real life'
situations or activities. Therefore, simulations really
identify possible trends.
• Faulty or hidden assumptions
• Extent and effect of the simplification of reality
• Processing power needed to create complex models
• Can be costly to purchase the processing power and
labour

8. Complexity and Assumptions
• Mathematical models are built on assumptions, many of
which are difficult to verify.
• Possibility for the assumptions to be faulty, the creators of
the model to overlook things (hidden assumptions) and
also clerical errors can be made with the programming.
• Daily weather report - to be 100% accurate is too difficult.
Usually, the report is 55-65% accurate.
• Errors with computer models can have disastrous results.

9. Weather Forecasting and Climate Models
• The importance of the weather and the
need to predict it accurately is illustrated
by the fact that every local news show
includes weather forecasts.
• People need to know what the weather will
be like–either where they are or where
they are going–so that they can plan their
activities accordingly.

10. A brief history
Weather forecasting is no new trend. As far
back as 650 BC, there is evidence of early
humans attempting to read the weather.
• Observing cloud patterns
• Colour of the sunset e.g. red
These forecasting methods proved to be
primitive and unreliable.

11. A brief history
1837 did real weather forecasting truly
begin. With the creation of the telegraph,
people could now begin to draw more or
less accurate reports of weather conditions.
In the 1840s, the telegraph allowed people to
record weather conditions over a much
larger area.

12. A brief history
1922 when Lewis Fry Richardson proposed
his idea of using numerical weather
prediction to forecast the weather.
“Numerical weather prediction used
mathematical models of the atmosphere to
predict the weather.” This new idea was not
used until 1955.

13. Five basic steps of
weather forecasting
• Data collection (observations from surface,
stratosphere or satellite)
• Data assimilation - production of a model
• Numerical weather prediction
• Model processing - adds human
observations
• Presentation of a forecast

14. Stakeholders
• General public
• Air traffic
• Military / Navy
• Farmers
• Utility companies e.g. Origin Energy
• Private companies

15. Issues - Reliability
• Not always accurate; extent of situation
could be overestimated
• Better safe than sorry or don’t provide
warnings

16. Issues - Integrity
• Accuracy of the data and the instruments
collecting the data

17. Equality of Access
• Quite easy to translate forecasts because of
visual information
• Not everyone has access to radio, TV,
Internet for emergency warnings

18. Issues - Control
• The weather forecast may control our day
• Companies respond to forecasts - potential
economic cost

19. Issues - People and
Machines
• Requires people to interpret the
information produced by the models
• Need for human observation to be added
to the forecast
• Future weather forecasts may be able to be
delivered without the aid of humans.

20. Digital Experimentation
• Digital Experimentation is the act of conducting
experiments on a computer without ever physically
touching the test subject.
• For example, engineers can create digital models to
crash-test a car to observe how the crash-test dummies
would react to the impact.
• Another way to digitally experiment is by using image-
enhancing programs like Photoshop. Let’s say you’re
wondering what you would look like with purple hair but
you don’t actually want to dye it: by using certain tools
and techniques on Photoshop, you can!

21. Car Crash
Simulators
Car Crash simulations offer a
way to gain information about
the causes of the accidents and
how to improve the safety of the
car bodies.

22. How car crash
test simulators
work
They use the finite element
method - grid superimposed on
the object and numerical data is
entered to each corresponding
square of the to provide
information on density, strength
and elasticity.

23. Calculating the effect of
a head-on collision
• Data can be initialised to represent a crash
into a wall at a specified speed.
• The program computes the force,
acceleration and displacement of each grid
square, plus the stress and strain of each
element of the model.
• Program relies on intense computation and
highly dependent of graphics programs.

24. Benefits
• Can look at a variety of designs before
building the prototype.
• Saves several design being built and having
to be crash-tested. Each crash test costs
between A$ 100,000 to 1.6 million.
• Saves on material waste.

25. Issues - Reliability
• Good understanding of the physics
involved, especially force and acceleration.
• Material properties are relatively well
known.
• Behaviour of the materials under abrupt
acceleration e.g. high speed impact and at
near breaking point are less understood

26. Issues - Reliability
• Simplification involved in the model. Cars
are smooth and a grid does not replicate
this.You can produce smaller grids but such
a model requires far more processing
power and cost.
• Comparison with real-life situation is,
arguably, good. Use of video cameras on
actual crash tests with data, such as
displacement points, fed back into the
computer model.

27. Issues - Integrity
• Incorrect entry of data
• Hackers changing data

28. Issues - Equality of
Access
• Small companies looking to break into the
car market would need a lot of money to
compete with big corporations such as GM.

29. Issues - Policy and
Standards
• Saves on environment in terms of materials
used
• Economic savings
• Saves time

30. Traffic Simulation Models
Definition:
A computer program that uses mathematical
models to conduct experiments with traffic
events on a transportation facility or system
over extended periods of time.

31. Complex Networks
Network traffic simulation is a process used
in telecommunications engineering to
measure the efficiency of a communications
network. Telecommunications systems are
complex real-world systems, containing many
different components, which interact, in
complex interrelationships.

32. Determining the efficiency of a road netwrok
• Most obvious efficiency factor - the pattern
of roads that currently exist
In addition, consider first the travel behaviour -
• Number of trips (data loggers)
• Origin and destination of trips
• Transport mode
• Route taken

33. Use of zones
• Models incorporates zoning e.g. some 542
zones across the Greater Dublin area.
• Zones define the demand for travel in
terms of origins and destinations.
• Need to consider external zones for trips
into and out of the area.

34. Increasing efficiency
Once the ‘general’ efficiency is found, control measures that may
assist improve the efficiency of the model may be incorporated:-
• Speed limits
• Overtaking bans for trucks, especially at uphill or downhill sections
• Restrictions for lane changing, especially before or at merging
regions
• Traffic flow control at on on-off ramps at intersections

35. Improving Efficiency
Traffic simulation models can also be used to look at future scenarios:-
• To simulate the effect of new infrastructure before it has been build.
• To simulate the influence of vehicles with adaptive cruise-control systems. If
an increasing percentage of vehicles has such systems, does traffic become
more stable? Can the traffic flow per lane be increased?
• Finally one can even simulate different or new traffic rules. For example,
allowing overtaking on freeways at either side combined with a speed limit.

36. Advantages of traffic simulation
models
• It is possible to easily compare alternative designs so as to select
the optimal system
• The actual process of developing the simulation can itself provide
valuable insights into the inner workings of the network which can
in turn be used at a later stage
• Time and money saving
• Possible to test new traffic rules without putting humans into
dangerous situations and comparing the results of different types of
traffic rules

37. Disadvantages of traffic simulations
• Data can be incorrectly input
• Accurate simulation model development
requires extensive resources
• The simulation results are only as good as
the model and as such are still only
estimates
• It is very costly to develop a good, reliable
and realistic simulation

38. Issues - Reliability and Integrity
• Data can be incorrectly input
• Data becomes out of date quickly
• Vast networks difficult to survey
• Need for accurate for casting e.g. number
trips determined by population projections
and level of car ownership or even
environmental consciousness

39. Issues - Security
• Need to protect the simulation from those
who may wish to tamper with it.

40. Issues - Equality of
Access
• Costly and extremely difficult to do in
developing countries

41. Demographic Models
Demographics refers to certain population
characteristics such as race, age, gender,
income, disabilities, literacy rate, home
ownership, employment status, and location.
It is useful for the government of a country,
coming up with marketing strategies, and for
economic research.

42. Population Pyramids