Simon Weckert, a german artist living in Berlin, has used 99 second-hand smartphones to generate a fake traffic jam in Google Maps. In his website, Google Maps hacks, you can see the different experiments and their results.
Simon Weckert is an artist known by his work related to the digital world, with the goal to make us think about the technology we use in our everyday lifes and how this is impacting our world and culture. One of his latest activities, which took him about 2 years to prepare, has gone live in the early 2020. You can read an interview from the german newspaper Frankfurter Allgemeine about it (in German).
Here, as always, we are interested in the technology behind it. How did the Google Maps hack manage to achieve this fake traffic jam?
The Google Maps hack
99 smartphones in a small trolley. That’s all it took Simon Weckert to hack the google maps traffic algorithm to generate a fake traffic jam in the streets of Berlin (by the way, just in front of the Google office in the German capital).
The smartphones were all connected to the cellular network and with location services activated. The mobiles were connected to google maps in driving mode, i.e. simulating that they were on board of driving vehicles. The artist pushed the trolley along the streets of the city, walking on a slow pace and stopping every now and then. See the image above, on the right side.
For the regular person passing by, they would just see a man carrying a trolley full of phones, as if he was walking his dog. However, Google maps saw differently. For the Google maps navigation algorithm, this smartphone-full trolley appeared as 99 cars, almost not moving at all. Thus, the algorithm decided the street must be collapsed and the fake traffic jam became alive.
Google maps navigation algorithm
Google maps is a very popular application among drivers. Its navigation algorithm has very precise real time traffic information, in most cases more up to date than most of the car’s built-in navigators. At the core of this accuracy resides the crowdsourcing algorithm: the data from all the users of the app is being collected and used real-time to identify the congestion of the roads.
With its powerful crowdsourcing-based navigation algorithm, Google maps can outperform the car built-in navigation application, especially if the latter is not connected to the Internet. However, the crowdsourcing is precisely what Simon Weckert used to exploit for his Google maps hack.
Each of the 99 smartphones is collecting its motion information, with the help of GNSS, Inertial Measurement Units, cellular network positioning technologies and other positioning sources. The motion information includes the current position of the mobile phone, the direction of the motion and the speed.
This information is transmitted to the Google maps’ navigation algorithm. However, Google maps does not see, as the reader does, that this information is coming from a bunch of smartphones put together in a trolley. Google maps thinks these are 99 independent users and their corresponding motion information is used for the crowdsourcing.
The conclusion (from Google maps point of view) is straight-forward: if these 99 users are almost not moving, there must be a traffic jam in this street. And thus, Google maps turns the street from green (light traffic) to red (heavy / not moving traffic), as it has been shown in the Google maps hack website.
Of course, there is a trick to all of this: the street selected by Simon Weckert is probably not the most crowded street in Berlin. Otherwise, Google maps would be collecting contradicting information from other users circulating on the same road at normal speeds and detected some foul play. However, once the fake traffic jam made it into Google maps, its navigation algorithm re-directs the drivers through alternative routes to avoid the congestion, helping the deception to last longer.
The Google maps hack is definitely a curious example on how technology influences our lives today and how someone can use it to manipulate other people. Of course, in this case the artist’s intention was just to make society aware of his point. But someone could also exploit similar technological weak points with other mischievous intentions.
Location determinations is also often based on crowd sourcing wifi access point database. These databases are continuously updated based on Wifi and public Bluetooth information collected by the phones. Can this information be compromised ? These are definitely possible concerns that will need to be addressed.
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