Geo-information: The ‘Oil’ for Driverless Vehicles

Geo-information: The ‘Oil’ for Driverless Vehicles


As various milestones of autonomy begin to play a determining role in the driverless vehicle industry, there develops a growing interest of stakeholders in this ecosystem. Not surprisingly, it is the geospatial industry which is at the core and is accelerating the driverless car industry because these cars rely heavily on data. Data is at the core of the success of the self-driving vehicles and is collected at four levels; In-car sensor data, base map data for navigation, vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) and commercial datasets (i.e. data from social networking sites). It is also found that these cars do not only consume data but also act as ‘on-the-move-data infrastructure’ producing vast amount of data. According to a study conducted by Intel, in 2020, the average autonomous car may process, 4,000 GB or 4TB of data. This is going to be only possible through the seamless integration of advanced multiple sensors i.e. LiDAR or Radar, GNSS/GPS, Ultrasonic sensors, High-powered cameras with the computing processor. These technologies work in conjunction with each other to successfully and safely manoeuvre the vehicle to its final destination. Along with this, space technology also helps in deciding the right moment for these cars to hand control to humans.  In addition, an available and reliable GNSS is required to increase the safety, enhance the traffic flow to provide better public mobility.

However, the most crucial requirement for the success of self-driving vehicle is that the data used in these vehicle needs to be reliable and authenticated before use. To ensure data integrity, reliability and accuracy, there needs to be set standards and structure. It is found that a central unification process for data standards becomes imperative because fundamentally different formats and structures complicate driverless vehicles. A universal data language will initiate communication with all the vehicles on the roads to live route conditions in real time. In this context, open data standards, interoperable standards, policy standards and technical standards all need to be in a uniform format to achieve the benefits of autonomous driving.

The government too plays a defining role in the success of driverless cars. The study establishes that the government needs to play a key role in establishment of an enabling and protective legal framework for safety, privacy data sharing, cyber security and liability. The government needs to also be responsible for establishment of open, or interoperable and internationally oriented data policy and governance. It is up to the government to realise that the data is crucial and the benefits so derived need to be understood and be conferred to the government and stakeholders of the self-driving vehicles.

In conclusion, 25 years from now, it is forecasted that 94.7 million vehicles with self-driving capabilities will be sold annually globally by 2035. Data, along with software platforms and infrastructure technologies (Cloud, Big Data, etc.) will transform the entire landscape of the future mobility.

The report, Self-driving vehicles and geo-information, has been conducted by Geospatial Media and Geonovum. It contains an overview of the components of the data ecosystem. The editors thank the participants of the workshops in Rotterdam and Hyderabad for their very valuable inputs.