Twelve Concepts in Autonomous Mobility


I recently met with the advanced design team of a Japanese client to discuss how autonomous mobility could play out. The following are behavioral musings/predictions based on research into practices across markets as diverse as the US, China, Japan and India.

The elasticity of a vehicle: its preferred physical distance to its owner, place or other vehicle, ultimately measured in pick-up times, perceived and actual risk of the environment by the person and the vehicle.

The shy-distance by which your vehicle instinctively avoids, shies away from other vehicles on the road and stationary objects. For example the shy-distance in Shanghai today is very low, if a driver leaves a two inch gap another driver will take it. China is an interesting market not least because of the volume of cars, the quality of the (often newly built) infrastructure, but also because the majority of cars are bought by first-time buyers who are both proud of their new investment and learning how to drive. Assuming that an autonomous vehicle needs to compete with other human-driven vehicles for road space how would the vehicular shy distance differ from country to country? What are the personal, contextual, cultural factors that affect the shy distance: such as the kind of vehicle; the speed; who’s inside? Who will override or tweak their vehicles shy distance to gain a competitive edge on the road?

The practice of what we currently call parking will obviously change when your vehicle is able to park and drive itself. Think of your vehicle autonomously cruising the neighbourhood to be washed, pick-up groceries and recharge its batteries whilst you’re off having lunch. What is the optimal elasticity of your autonomous vehicle to you? What are the kinds of neighbhourhoods it likes to drive around in when you’re not using it? This is an especially pertinent question, when a vehicle is considered a sensing platform — the technology to autonomously negotiate the city can collect rich data for other uses. (Most of the data collected will be commodified, but there will be niches that will give individuals an edge).

Juddering: the ripple of a dozen or more cars in a parking lot that react and finally settle to the arrival of a new vehicle by each trying to find a new optimal shy distance. Most prevalent near borders and places where there’s a high propensity to use (internationally) stolen vehicles.

Nanny mode: vehicles that are assigned to pick up young children from school, but end up trailing them at a discreet distance because the kids prefer to walk.

Car surprise: when you come across your car somewhere where you didn’t expect it to be and witness your vehicle engaging in unexpected activities e.g. pickup up flowers at the mall: the equivalent of catching your parent or kid smoking or shoplifting. Given your cars interest in you and your family, what activities will it record that will surprise others with access to its feed? Which leads us to…

Nookie mode: ensures you don’t meet your vehicle when you’re out and about until you are ready. This is named after the behaviour of couples who share location information with one another to avoid each other on a big out when they may end up with new sexual partners for the night. When the purpose is to hook up, the vehicle will increasingly be a viable option for private time, driving around less frequented neighbourhoods with sensors turned dark, to minimise discovery. Every car is a potential love-hotel room, albeit with wet wipes rather than great bathing facilities — I would expect them to significantly impacted the shorter end of the “short-stay” market, such as highly transactional activities such as prostitution.

Jerky Driving: masturbating in an autonomous vehicle while driving will be a far more practical use case, but is not something that corporates are going to talk about any time soon. Males and females have a different propensity to masturbate, but (from conversations with both genders) the current car ergonomics for masturbation favour women.

A Highly Private Moment (HPM): the term used in corporations to describe highly private activities that take place in vehicles. Expect to see a variety of hacks to temporarily disable sensors such as internal facing cameras. As a side note, if you want to introduce discussions on taboo activities into a corporation, reduce it to a generic TLA or FLA that is open to wide interpretation. e.g. VPMC = Very Personal Media Consumption. The rise in opportunities for compelling HPMs will lead to a seismic shift in physical vehicle design, sold or more mundane pursuits.

Hedge-parking: where your vehicle overbooks a number physical parking spaces based on your preferences of timing, location, flexibility and willingness to pay, but is unable to offload the unused spaces on the open market by the time comes to actually park.

Fine-rich: the compensation your vehicle receives from other vehicles where parking spaces that you’ve booked are not yet available because other vehicles have overstayed their allotted times. As an aside, the whole notion of a fine being mediated by an authority (highway patrol, parking attendant) could go out the window when the person who commits an anti-social act (overstaying a parking space) is directly connected to a person that is impacted by that anti-social act (someone who booked that parking space).

Trailer trashing: where dodgy looking vehicles are assigned to trail an otherwise apparent owner either as a joke or to send a message e.g. a hearse sent by a debt collection agency to scare-up payment. You’ll also see this happen with more aggressive companies who send a vehicle around to their competitors to send a message, recruit staff or to gather (sensor) intelligence. Imagine Task Rabbit or San Da Ha + autonomous mobility + malicious intent. The most obvious market for this will be straight-up advertising.


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