Waiting for the Robocars, Part V
Data Everywhere — cars that watch (out for) you
After Part 1 looked at potential changes to speed the arrival of Robocars and Part 2 looked at the autonomous vehicles we’ll see before driverless cars, Part 3 continued the series by looking at how the incumbents are preparing. Part 4 examined whether those developing driverless cars should consider working together to make progress faster. Part 5 now explores the data and privacy considerations.
When you consider data in the context of self-driving cars, it’s easy to think of it purely in terms of the data the car gathers through its various sensors, interprets, and uses to determine its (hopefully safe) course of action. But modern vehicles are already themselves prolific creators of data; data that are valuable to many stakeholders, whether or not the travelling public realise it.
While driverless cars are estimated to each create up to 4TB of data per day, a contemporary car already creates up to 250GB per day. This includes obvious information such as location and speed, to more detailed logs regarding component temperatures and pedal pressures, etc. Even shared bikes and scooters collect data. In the modern world, we already know that data are valuable. So what happens these data today, and what might happen to it in the coming years?
First off, it’s important to consider the question: who is interested in travel data? The most obvious interested parties are the car manufacturers. Data about the operation of their cars are very useful in understanding vehicle performance, potentially preemptively identifying maintenance requirements based on the unique driving style of each owner. Car makers can now create virtual “digital twins” of a car based on the data received from on-board sensors and uploaded through 3G or 4G chips embedded in many cars. Insurers (and potentially authorities investigating collisions) could also be very interested in what gets logged about how you drive. What if the car’s telemetry shows you were exceeding the speed limit, or failed to apply any pressure to the brakes? This information could be vital in apportioning blame during litigation. Event recorders for vehicles are already part of the impending new EU Safety directive.
Location, Location, Location
Next up, cities are very interested in these data for planning purposes. While the move from cash to contactless travel cards (which collect data) has greatly increased the ability for transit providers to understand travel patterns, as more of the transportation in cities becomes digitised (i.e. controlled by apps that collect fine-grained location data), the urban authorities are now looking to get a broader picture of movement to include all modes of transport, not just transit/public transport.
Transportation Network Companies (TNCs) such as Uber or Lime collect vast amounts of data to help them anticipate demand and position cars, bikes or scooters where and when they are most likely needed. This has led to conflict between cities and TNCs. For example, the City of Los Angeles has created a standard method (Mobility Data Specification or MDS) of collecting data related to TNC movements, and require operators in the city to comply and provide data to them.
They had to agree to share anonymized trip data, updated every 24 hours, on where each scooter or bike trip starts, where it ends, and its route through the city.
Why Uber Is Fighting Cities Over Data on Scooter Trips, Wired, 13th May 2019
Information on where people are, and the routes they are taking through the city is valuable not only for civic planning purposes. Retailers and advertisers are also interested in these behavioural insights. If they can determine where people are, it’s easier to devise methods to advertise to them, and to better assess the value of outdoor advertising sites.
In order to operate safely, Robocars require multiple sensors which provide information about the world around them. In all cases, this involves multiple cameras (Teslas already have 8 cameras, and prototypes such as Waymo use a 360 degree camera vision system). While the purpose of these cameras is to allow the car to perceive its surroundings, anywhere you have cameras in public, you have immediate questions about privacy. As the number of systems to help drivers in human-driver cars increases, several cars that offer Advanced Driver Assistance Systems (ADAS) use cameras to enable lane detection and next generation cruise control.
In recent years, there has been a dramatic increase in the number of car drivers installing dashcams to record potential evidence for use in the event of a traffic incident. Routinely, one hears police appeals for “passing motorists who may have dashcam footage” to come forward to assist with investigations. Imagine how this will change when cameras are not an optional extra. While already it’s increasingly likely that a passing motorist or cyclist has a camera recording, if every car is eventually a mobile CCTV unit, you can have little expectation of walking down the street without being recorded.
Without waiting for Robocars, it’s a fact that data collection, including location, video and other inputs, are increasing as transportation becomes ever-more digitised. There are clear benefits for city planners as well as efficiencies for consumers looking for a ride, but awareness among consumers is low and transparency of data use is lacking. These are privacy issues that I believe most drivers, who are the owners of the data, are largely unaware of. Despite the various privacy scandals and data breaches, most people still give scant consideration to their digital trail. While regulation such as the GDPR in the EU has helped raise the bar on data protection, there remain significant questions about how these car and travel data are used.
Robocars and Data
Ultimately, when we get to a world of driverless cars, the data aspect will be even more crucial. Will the owners of RoboTaxis sell data about their passengers to advertisers or even to businesses wishing to influence the route the car chooses? Or will Robocars bring calls for a more private travel experience akin to Incognito Mode on web browsers? Whatever happens, data are not just at the heart of how driverless cars will function, but also how they’ll influence the world around them.
David Kerrigan is the author of Life As A Passenger, which is available in English and Chinese. He presents at the Stanford Continuing Studies Self Driving Cars courses and writes extensively about the social impacts of emerging technologies at https://david-kerrigan.com