In the prior post we catalogued the functions in the Iron HUD. Today we examine the 1st-person display.
When we first see the HUD, Tony is donning the Iron Man mask. Tony asks, JARVIS, “You there?” To which JARVIS replies, “At your service sir.” Tony tells him to Engage the heads-up display, and we see the HUD initialize. It is a dizzying mixture of blue wireframe motion graphics. Some imply system functions, such as the reticle that pinpoints Tonys eye. Most are small dashboard-like gauges that remain small and in Tonys peripheral vision while the information is not needed, and become larger and more central when needed. These features are catalogued in another post, but we learn about them through two points-of-view: a first-person view, which shows us what Tony’s sees as if we were there, donning the mask in his stead, and second-person view, which shows us Tony’s face overlaid against a dark background with floating graphics.
This post is about that first-person view. Specifically it’s about the visual design and the four awarenesses it displays.
In the Augmented Reality chapter of Make It So, I identified four types of awareness seen in the survey for Augmented Reality displays:
- Sensor display
- Location awareness
- Context awareness
- Goal awareness
The Iron Man HUD illustrates all four and is a useful framework for describing and critiquing the 1st-person view.
When looking through the HUD “ourselves,” we can see that the HUD provides some airplane-like heads up instruments: Across the top is a horizontal compass with a thin white line for a needle. Below and to its left is a speed indicator, presented in terms of MACH. On the left side of the screen is a two-part altimeter with overlays indicating public, commercial, military, and aerospace layers of atmosphere, with a small blue tick mark indicating Tonys current altitude.
There are just-in-time status indicators like that cyan text box on the right with its randomized rule line. The content within is all N W RNG EL, so, hard to tell what it means, but Tony’s a maker working with a prototype. It’s no surprise he takes some shortcuts in the interface since it’s not a commercial device. But we should note that it would reduce his cognitive load to not have to remember what those cryptic letters meant.
The exact sensor shown depends on the context and goal at hand.
Periphery and attention
A quick sidenote about peripheral vision and the detail of these gauges. Looking at them, it’s notable that they are small and quite detailed. That makes sense when he’s looking right at them, but when he’s not, given the amount of big, swirling graphics he“s got vying for his attention in the main display, the more those little gauges have to compete. And when it comes to your peripheral vision, localized detail and motion is not enough, owing to the limits of our foveal extent. (Props to @pixelio for the heads-up on this one.)
You see, your brain tricks you into thinking that you can see really well across your entire field of vision. In fact, you can only see really well across a few dozen degrees of that perceptual sphere, corresponding to the tiny area at the back of your eye called the fovea where all the really good photoreceptors concentrate. As your eyes dart around the scene before you, your brain puts all the snippets of detailed information together so it feels like a cohesive, well-detailed whole, but it’s ultimately just a hack. Take a look at this demonstration of the effect.
So, having those teeny little guages dancing around as a signal of troubles ahead won’t really get Tony’s attention. He could develop habits of glancing at these things, but that’s a weak strategy, since this data is so mission-critical. If he misses it and forgets to check the gauges, he’s Iron Toast. Fortunately, JARVIS is once again our deus ex machina (in so many senses) because he is able to track where Tony is looking, and if he’s not looking at the wiggling gauge, JARVIS can choose to escalate the signal: Hide the air traffic data temporarily and show the problem in the main screen. Here, as in other mission critical systems, attention management is crisis management. Now, for those of us working with pre-JARVIS tech, it’s rare today for a system to be able to
- Track perceptual details of its users
- Monitor a model of the user’s attention
- Make the right call amongst competing priorities to escalate the right one
But if you could, it would be the smart and humane way to handle it.
As Tony prepares for his first flight, JARVIS gives him a bit of x-ray vision, displaying a wireframe view of the Santa Monica coastline with live air traffic control icons of aircraft in the vicinity. The overhead map updates of course in real time.
Very quickly after we meet the HUD it shows its object recognition capabilities. As Tony sweeps his glance across his garage, complex reticles jump to each car. Split-seconds afterwards, the car’s outline is overlaid and some adjunct information about it is presented.
This holds true as he’s in flight as well. When Tony passes by the Santa Monica pier, not only is the Pacific Wheel identified (as the Santa Monica Ferriswheel), but the interface shows him a Wikipedia-esque article for the thing as well.
While JARVIS might be tapping into location databases for both the car and the ferris wheel recognition, it’s more than that. In one scene we see him getting information on the Iron Patriot as it rockets away, and its location wouldn’t be on any real-time record for him to access.
Too much detail
While this level of object detail is deeply impressive, it’s about as useful as reading Wikipedia pages hard-printed to transparencies while driving. The text is too small, too multilayered, and just pointless considering that JARVIS can tell him whatever he needs to know without even asking. Maybe he could indulge in pop-up pamphlets if he was on a long-haul flight from, say, Europe back home to the Malibu RV Park (see above), but wouldn’t Tony rather watch a movie while on Autopilot instead?
Of course JARVIS is aware of Tony’s goals, and provides graphics customized to the task, whether that task is navigating flight through complex obstacle courses…
…taking down a bad guy with the next hit…
…saving innocent bystanders who are freefalling from a plane…
…or instantly analyzing problems in an observed (and complicated) piece of machinery…
…JARVIS is there with the graphics to help illustrate, if not solve, the problem at hand. Most impressively, perhaps, is JARVIS’ ability to juggle all of these graphics and modes seamlessly to present just the right thing at the right time in real time. Tony never asks for a particular display, it just happens. If you needed no other proof of its strong artificial intelligence, this would be it.