Human Factors in Simulation

June 11, 2013

Medical mannequin simulator (photo: US Navy)

Human factors are extremely important in simulation, as this 2009 book points out. Human-factors expertise is important both in simulating human beings and in the use of simulations by human beings.

Physical human limits (image: AnyBody public repository)

Issues involved in simulating human beings include physical and ergonomic factors, as well as human behaviour modelling (the subject of this workshop). In training simulations, it is important to fully understand the human process which is to be improved by simulator training. This can include subtle issues such team interaction, as well the more obvious factors.

Pilot landing cues? (screenshot from FlightGear)

There is also a plethora of human-factors issues in the development, design, conduct, debriefing, and debugging of simulations relating to the use of simulators by human beings. Negative training, for example, occurs when users of a training simulation learn the wrong knowledge, skills, or behaviours. This can be the result of low-fidelity representation of important decision or feedback cues, of timing delays, of incorrect or incomplete problem representations, or of other simulator design flaws. It is impossible to build a simulator with 100% fidelity, and even 99% fidelity would be prohibitively expensive. To achieve the required outcomes, where is high fidelity necessary? Human-factors expertise is essential in answering that question.

Simulator sickness affects many users of flights and vehicle simulators, and limits the potential benefits of such simulators. See this 2005 study for an overview of research in this area.

In training simulations, a variety of cognitive-psychology factors also come into play. Likewise, in decision-support simulations, it is important to understand the limits of the conclusions that can be drawn. Which results tell us meaningful things about the problem at hand, and which results simply reflect characteristics of the simulation?

Simulation is an extremely valuable tool for both training and decision support. Yet, for the best results, it is important to take into account human factors in both the design and the use of the simulation.

Vehicle simulator (photo: US Army)

– Tony

Human Behaviour Modelling Workshop – 16 Sept

June 3, 2013

My interest in human behaviour modelling is no secret, so it’s no surprise that I’m excited to be running a half-day workshop on the subject at this year’s SimTecT conference in Brisbane.

The workshop will cover key issues and major steps in human behaviour modelling, including practical “how to” advice, data collection issues, verification & validation, and some common pitfalls. Applications to Defence, Mining, and Health industries will be covered (depending on the participants). Some practical examples written in NetLogo will be given, although the techniques presented will be relevant to any simulation system.

Update: Unfortunately this workshop has been cancelled.

– Tony

Human Social Research: The Lively Science?

May 9, 2013

Michael Agar of has just written a book provocatively titled The Lively Science: Remodeling Human Social Research.

Having heard Mike speak, it’s sure to be an interesting book, and the online sample chapters confirm that belief. It’s kind of ironic that, even though I’m originally a mathematician, what Mike says about inappropriate quantification really resonates with my experience. For a complete view of human activity, numbers, pictures, and stories are all important. And if they disagree, something is surely wrong.

– Tony

“Where’s the tea?” – Simulating human behaviour

May 3, 2013

The tea

In Douglas Adams’ famous The Hitchhiker’s Guide to the Galaxy, some of the characters discuss the replacement of Arthur Dent’s brain by an electronic one:

‘Yes, an electronic brain,’ said Frankie, ‘a simple one would suffice.’
‘A simple one!’ wailed Arthur.
‘Yeah,’ said Zaphod with a sudden evil grin, ‘you’d just have to program it to say What? and I don’t understand and Where’s the tea? – who’d know the difference?’

But is that true? Can simple computer models adequately simulate human behaviour?

How will a crowd of panicked humans flow down this fire escape?

In fact, it depends on the goal of the simulation. In models of pedestrian flow, work by Dirk Helbing and others has shown that quite simple models can perform very well, particularly in simulating evacuation dynamics and similar panic-driven scenarios. In these situations, simulations not much more sophisticated than simple fluid-dynamics models can reveal the benefits of, for example, zigzag designs for evacuation routes. See Helbing & Johansson, “Pedestrian Crowd and Evacuation Dynamics” (Encyclopedia of Complexity and Systems Science, 2009).

Adding more sophisticated decision-making allows us to build agent-based models of economic behaviour. Will people purchase a particular product from a particular vendor? Will vendors alter their prices up or down to match other vendors? Alison Heppenstall, Andrew Evans & Mark Birkin provide a nice example of such modelling, by simulating the spatial variability in petrol (gasoline) prices in “Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets” (Journal of Artificial Societies and Social Simulation, 2006). Relatively simple models of behaviour also suffice for epidemiological models (which were discussed at the 2012 Workshop on Verification and Validation of Epidemiological Models in Washington D.C.).

Anasazi ruins, Southwest USA

One of the most well known examples of agent-based modelling using this approach is the insightful study, by Robert Axtell et al., of ancient Anasazi population dynamics in the Southwest USA. In this case, behaviour in the model was synthesised from archaeological evidence, anthropological data, and rational decision-making – households will pack up and move out if they’ve seen too many bad harvests in a row. See “Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley” (PNAS, 2002), and “Understanding Artificial Anasazi” (M.A. Janssen, Journal of Artificial Societies and Social Simulation, 2009).

Related modelling methods are used in studies of land use. Will farmers switch the crops they’ve been planting? Will they fell trees in the neighbouring forest? Will they abandon farming altogether and move to the city? Alex Smajgl and others discuss approaches to such modelling in “Empirical characterisation of agent behaviours in socio-ecological systems” (Environmental Modelling & Software, 2011). Grace Villamor, Meine van Noordwijk, Klaus Troitzsch & Paul Vlek, in their paper “Human decision making for empirical agent-based models: construction and validation” (International Congress on Environmental Modelling and Software, 2012), compare the strength and weaknesses of heuristic versus optimal decision-making in models. It may be difficult to accurately capture human heuristics, but it cannot necessarily be assumed that humans will always make the “best” decision.

The emotions of fear and joy: The Rescue by John Everett Millais

The choice between heuristic and optimal decision-making in models is complicated further when the humans being modelled make decisions on emotional grounds. Stacy Marsella and his team at the University of Southern California have had considerable success in modelling human emotion. One very successful use of their approach has been the tactical language training software marketed by Alelo, which also incorporates game technology. For details, see Johnson & Valente, “Tactical language and culture training systems: Using AI to teach foreign languages and cultures” (AI Magazine, 2009). Further development of this approach is likely to have several interesting applications.

For practical purposes, then, we can simulate human brains by electronic ones. But they will not necessarily be simple.

A significantly expanded version of this post will appear as an article in the Summer 2013 issue of the Society for Modeling & Simulation International (SCS) Magazine.

Are Security Questions a Joke? Or is the way the Systems are Designed the Real Joke?

August 9, 2012
Security questions

Security questions (Photo credit: janetmck)

I read a great article the other day on the threat posed by the use of password security questions as a Computer security issue.

I too have been quite amused by the poorly designed questions which purport to help you if you forget your login information for a site.  Frank Voisin suggests a few ideas to make them more applicable.

However, the second item jarred with me – Applicable: the question should be possible to answer for as large a portion of users as possible (ideally, universal).


I would have thought that the primary (and only) function was to have something which was individual to the person involved.

Now I’m only a human factors scientist, but my training suggests that we ask the individual to design their own questions.  Sure, give them some advice and make the process as intuitive as possible, but give them the ability to make it as individual as they like – surely that‘s the whole point!  After all, this information is only kept in a secure database to be accessed as needs permit.

Is it more that the systems designer was trying to make his or her job easier?  Sort of fitting the human to the system rather than designing it to the individual’s explicit needs?  Did this save them a few lines of code?

Obviously some human science input into this area is sorely needed.  This raises the question of whether someone who is a computer scientist first and has cross-trained into the human interface is the best person for this role, or someone with a psychology or social science background.
My suggestion is that in this case, you really need some cross disciplinary interaction to arrive at an optimal solution.

Was Steve Jobs the Commercial Mesiah?

August 9, 2012

English: Steve Jobs shows off the white iPhone...

I recently viewed a Simon Sinek presentation on TED:

He used Apple as an example of a business which uses the why or underlying belief system as its primary corporate message which then leads into the how and what they do.

This brings to mind an article reflecting on the Steve Jobs legacy that I read after he passed away.  Steve insisted that the design of a product be the key factor.  This then informed the subsequent engineering process and marketing.  As Sinek notes, he did the opposite of what other technology companies typically do.

In doing so he not only made Apple a premier company but also made it a leader in its field.  If imitation is the sincerest form of flattery, the design of competition mobile phones, entertainment devices and tablets signal that Apple’s business method is the one to follow.This is a simple diagram known as a Business O...

How does all this relate to Human Factors Science and Human Science generally?

I believe that we provide the why based on our knowledge of the end user – the human.  Unfortunately, all too often the technical and marketing areas dictate what is produced without any input or thought of the human interface, reflecting some of Sinek’s assertions.  If the end user does not find the product intuitive or empowering to their human experience (informed by our scientific approach to this aspect) the product will probably fail as a commercial success.

So really the challenge is not a real challenge at all.  Get professionals to handle matters at each stage of the process.  However, start with the Human Factors Scientists to provide the why, then let the engineers and technicians loose to produce what they’re good at, the how and what.