The Mobile Office: What we do, what we want, and what we need
As vehicles get better and more reliable forms of automation, drivers might start working on other, non-driving related tasks. But what are those tasks? This article describes what we do, what we want, and what we need in the automated car.
What we do
Drivers already perform various non-driving tasks in their non-automated cars. Dingus and colleagues (2016) collected data on 3,500 drivers in their own cars through video capture. Of the non-driving activities, drivers mostly interact with other passengers. However, they also interact with their cell phones, in-car devices, and in-vehicle equipment. Some drivers reach to other objects, including to children on the rear seat. Others eat, drink, conduct personal hygiene, or dance in their seat (the latter one is familiar to me..). The same paper also demonstrates that most of these activities increase the risk of being involved in a car crash.
What we want
Arguably, when automation improves and becomes more reliable, it might become safe to perform at least some non-driving activities in the car. Fully automated cars are not commercially available at the moment, and therefore we cannot just observe what people do. Instead, Pfleging, Rang, and Broy (2016) asked drivers what they would want to do in future automated cars. The activities that most people report that they’d want to do frequently are similar to those that Dingus et al (2016) observed in today’s cars.
However, other activities are also included. Some of the more frequently reported tasks include using the internet, using social media, and performing office tasks. In other words: people do want to use their car as a mobile office.
They also would like to do other task, such as watching movies, or playing video games.
What we need
Unfortunately, people are not so good at looking into the future. Robert J. Szczerba (2015) of Forbes, for example, made an interesting list of 15 poor tech predictions over the last 150 years. My interpretation of a couple of those terrible predictions is that people projected the status quo onto the future. They thought that the introduction of a new technology would not change how the associated tasks are done. This seems to be inaccurate (see also Bainbridge, 1983, on the irony of automation).
The same might hold for the automated car: we project what we want to do now as the same thing that we need in the future.
But is this really the case? I do not know the answer to that. Perhaps other are better than me in predicting the future. Or perhaps we can figure it out collaboratively. Therefore, I’m looking very much forward to discuss this with other researchers at our workshop at Auto-UI 2018 in Toronto.
What I do predict: Safety research still matters
One thing I do predict, is the following: whatever technological developments happen, researchers do need to keep thinking about human safety. Automated cars are great machines, but they are not perfect (yet), and people’s understanding of automated cars is not perfect (yet). Various researchers have reported so-called “mode confusions” in which drivers are confused about what the car is and isn’t doing, and about what their own responsibilities then are. For example, they are confused about whether the car brakes on its own or whether they should press the brake themselves when approaching another car in front of them.
I would like to think about how we can design cars such as to avoid, or at least significantly reduce, such confusion. Some of my latest thoughts on this topic can be found in this article: Janssen, Boyle, Kun, Ju, Chuang (in press 2018).
If you want to know even more about my own research, you can check out my website for my written work, or my Youtube channel for short video clips on my research, like this one:
References
Bainbridge, L. (1983). Ironies of automation. In Analysis, Design and Evaluation of Man–Machine Systems 1982 (pp. 129–135). [link]
Dingus, T. A., Guo, F., Lee, S., Antin, J. F., Perez, M., Buchanan-King, M., & Hankey, J. (2016). Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proceedings of the National Academy of Sciences, 113(10), 2636–2641. [link]
Janssen, C. P., Boyle, L., Kun, A., Ju, W., & Chuang, L. (in press 2018). A Hidden Markov Framework to Capture Human-Machine Interaction in Automated Vehicles. International Journal of Human Computer Interaction. [link]
Pfleging, B., Rang, M., & Broy, N. (2016, December). Investigating user needs for non-driving-related activities during automated driving. In Proceedings of the 15th international conference on mobile and ubiquitous multimedia (pp. 91–99). ACM. [link]
Szczerba, R.J. (2015, jan 5) 15 Worst Tech Predictions of All Time. Forbes [link]
