Mapping smiles and stumbles

By Gordon Rugg

In a previous article, I looked at ways of systematically recording indicators of problems and successes with a design. In that article, I focused on the indicators, with only a brief description of how you could record them.

Today’s article gives a more detailed description of ways of recording those indicators, using the worked example of a building entrance.

The worked example is, ironically, the Humanitarian Building. Here’s the Wikipedia image for its entrance.

http://commons.wikimedia.org/wiki/File:MSU_III_Humanitarian_Building_Entrance.jpg

When you look at it from a task analysis viewpoint, you soon spot potential trouble. Here’s a close-up that shows one source of possible complications.

The ground outside the building slopes slightly. The entrance design tackles this by having a flat surface immediately outside the entrance, and then having a small step (indicated by the red arrows) between that flat surface and the sloping approach routes.

The phrase “small step” is usually a synonym for “stumbles and swearwords waiting to happen”. However, that doesn’t necessarily mean that the designer got it wrong. The easiest alternative would be to handle this problem via a change of slope, but the phrase “change of slope” is also usually a synonym for “stumbles and swearwords waiting to happen”. Another option would be some significant re-working of ground levels, which would probably entail a whole batch of new problems. It’s a non-trivial design problem, without a single perfect solution.

If you superimpose likely pedestrian flight paths over this image, plus the door footprint for when the door opens, you get something like this.

I’ve shown three flight paths that are particularly likely to be used, and omitted the others, for clarity. One flight path goes to the left, along the path to the left. Another goes to the main pavement, heading left, and cutting as close as possible to the flower bed; the third goes to the main pavement, heading right, and again cutting as close as possible to a flower bed. There’s also a significant flight path along the path to the right, but I haven’t shown that in the image above, to avoid visual clutter.

All three of these flight paths either go over the small step, or go next to it. It’s a pretty fair bet that this will end in tears before long. Either someone will not notice the step and will stumble over it, or someone will avoid the step, but will have a collision with someone who has missed it and has stumbled.

That’s what is likely to happen. As for what actually happens, you can record that systematically with a variant of the task analysis method I described in the previous article.

I’ll use the same icons that I used in the previous article, for simplicity. Here are the icons.

Sources of original images are given at the end of this article.

One simple way of using them is to observe the place in question, and to record what happens by drawing the relevant icons on a photo of the place. This is classic “observation with a clip board and pen” and involves the usual points about getting ethical clearance if you’re a student, getting permission from the relevant authorities about being on the premises, letting Security know what you’re doing so you don’t get arrested for loitering suspiciously, etc. If you’re not familiar with these issues, it’s wise to pick the brains of someone knowledgeable.

Here’s a hypothetical example of what you might get from this approach, showing only the “stumble” yellow triangles, for clarity. I’ve copied and pasted the icon; if you were doing this with a clipboard and photo, you could just draw triangles with a pen or highlighter, or you could use small sticky labels; whatever works well for you.

This hypothetical image shows several clusters of triangles, where each triangle represents a stumble or a change of gait from walking smoothly. If you need quantitative as well as qualitative data, you can count the triangles, and/or count the triangles in each cluster.

The image below shows how these map on to the predicted flight paths. This time, I’ve included the flight path towards the footpath to the right, for completeness.

The clusters and the flight paths map onto each other as neatly as you might expect from a hypothetical example. (Ironic smile…) However, there’s plenty of empirical evidence from fields such as architecture to show that this type of identification of trouble spots is practical, useful, and able to produce unexpected insights. There’s been a lot of research, for instance, into pedestrian traffic flow in built environments, with particular regard to preventing bottlenecks and other hazards that can lead to crowd crushes in emergency evacuations of a building.

In this example, I’ve only shown records of stumbles. You can do exactly the same with the other icons. If your recording sheet starts to get cluttered, then you can record the time when you stop using it, and start using a new recording sheet; you can collate the results from the various sheets afterwards, when you’re back in the office.

Here’s another hypothetical example, showing multiple icons – stumbles, puzzled scowls where someone is deciding which route to take, and swearwords after stumbling. I’ve used bigger icons in this image, for clarity.

Finally, on a note of sympathy for the designer faced by a tricky problem, here’s an image showing the positive side of this solution. Whatever its other limitations, at least this design includes a route to the entrance for people with wheelchairs, child buggies, and other forms of wheels. If you search for images of building entrances, you’ll probably be surprised by how many entrances are at the top of a set of steps, with no provision for wheeled access. So, as a token of appreciation, here are some smiling icons as a positive closing note.