Four of the largest automakers – BMW, Ford, Renault and General Motors have recently announced that they are working together to get blockchain technology into your car.
They are among the 30 companies in the Mobility Open Blockchain Initiative, with the mission to speed up the adoption of blockchain, and make sure the industry is on the same page with use cases ranging from autonomous payments to ride-sharing. With the integration of blockchain to automobiles imminent, here are just some ways in which disruptive technology could transform your driving experience.
The popularity of cars that use mobile internet technology to control key functions remotely via a smartphone, smartwatch, tablet device or computer have risen in recent years. The benefits of a connected car seem to be endless – from the monitoring of your car’s maintenance schedule, fuel and oil levels, to tracking your car remotely in case of theft.
Renting a car will be made so much easier with the adoption of blockchain technology. Blockchain would allow the rental company to attach insurance contracts, along with a history of the car’s drivers, services, MOTs and other relevant events to the micro-loan. Once the car has been rented, a log of your own journey – such as interactions with toll gates and CCTV cameras – is automatically added to the car’s audit trail.
Blockchain technology could lead to cheaper insurance due to its clear traceability. As the technology is capable of storing all the driver’s data, as well as the car’s modifications and details, this could eventually enable several users to share the same car. Blockchain registers the number of times each person drives the car and the length of time they are driving it. This historical car user data could provide in-depth analysis of car modifications as well as a driver’s conduct and driving style. This will make it possible to customize insurance premiums on a “pay-as-you-drive” basis.
Following the fatal crash of Uber’s self driving car in March, A.I. is said to be the solution to training self-driving cars to identify their surroundings in a manner similar to human drivers. A.I. would be pivotal in helping self-driving cars make the right decisions in situations like manoeuvring through construction zones, moving over for emergency vehicles, and making room for cars that are parallel parking. This is done by feeding the system examples based on observed real-world situations.