This article from Caradisiac highlights the impact that autonomous cars could have on urban data management in the future. In the United States, the first autonomous cars to be put into operation in cities such as Phoenix, San Francisco and Austin have already been used several times by the police, who in some cases are collecting images filmed by their cameras.
Source : Espaces-Mobilités
This demonstrates the evolution that we are about to experience with the gradual deployment of driverless vehicles that operate using a combination of different technologies, in particular cameras, radar and lidar. These sensors will enable robotaxi operators to collect a phenomenal amount of information in real time, creating a kind of real-time digital twin of our cities.
Source : Waymo
They will be able to tell whether a road sign has been damaged, find out about the weather conditions in a particular area, analyse street usage (demonstrations, parties, police intervention) or update their 3D database of the city.
Source : Waymo
This is obviously one of the reasons why companies such as Google and Baidu are deploying fleets of robotaxis themselves, as part of a 3D mobile mapping strategy. In a few years' time, we can expect to see a fully dynamic version of Google Maps with a series of real-time metrics.
Source : Google
Google has already demonstrated the benefits of measuring air quality in real time as part of its Air View project.
Source : Google
Once again, this raises the question of how public authorities will be able to compete with this development when they are dependent on a series of fixed sensors that are difficult to deploy in cities for regulatory and budgetary reasons. Are cities going to buy real-time data from future robotaxis, as they do with GPS data (Floating Car Data) or mobile phone data (Floating Mobile Data)?
Source : Espaces-Mobilités
Yet cities have undeniable advantages, because they could equip their public fleets (buses, trams, waste collection vehicles, scancars for parking management) to collect this type of data themselves and develop standards for the use of this technology.
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