Applying Blockchain Technology to Autonomous Vehicles
As part of a five year collaboration project, Toyota Research are working with MIT’s Media Lab to build and analyse new deep-learning based perception and motion based planning technologies for autonomous vehicles. Toyota are working with a series of companies specialising in blockchain technology (a distributed database used to maintain a continuously growing list of records that powers the cryptocurrency bitcoin) and are aiming to explore how this can be applied to the industry.
@kpadisetti: Toyota is spearheading an initiative that uses blockchain to create an open platform for autonomous vehicles https://lnkd.in/gxp62UC
For a car to be fully autonomous, it needs to be able to refuel or recharge on it's own as well as park, read road signals (both physical and perceptive) and be able to pay for any facilities it uses along the way e.g. toll roads and petrol. Toyota's implementation of blockchain technology will connect all of these elements and enable the vehicle to stay in tune with all the distinct data elements.
They are hoping that not only will this software push forward their research, but it will also make the general public more comfortable with self-drive vehicles through heightened monitoring of AV behaviour and therefore improved safety and efficiency, as well as making it possible to offer attractive services such as pay as you go insurance. The data collected from human drivers will assist Toyota in creating a safe and reliable autonomous system. They will be training the vehicles to have an awareness of the driving scene from pedestrians to traffic signals and road marking and the data that each trip an autonomous vehicle takes will be shared to develop tools to help users make ride sharing easier and also to create new insurance products that are based on each use case.
Pablo Puente Guillen, Researcher ADAS from Toyota Motor Europe will be speaking at the upcoming Machine Intelligence in Autonomous Vehicles Summit in Amsterdam June 28 & 29, where we will hear more about safety and current research at Toyota.
Register now to hear from leading minds in autonomous vehicles.
Other confirmed speakers include: Jim Aldon D'Souza, Autonomous Driving Research Engineer, TomTom; Jan Erik Solem, Co-founder & CEO, Mapillary; Jasmine Kent, CEO, Daedalean; Federico Tombari, Senior Research Scientist, Technical University of Munich (TUM) and many more.
Leading the Toyota research project on the MIT side is Lex Fridman, who spoke at the Machine Intelligence in Autonomous Vehicles Summit earlier this year in San Francisco. He is currently leading a team of seven computer engineers who are ‘working on computer vision, deep learning, and planning algorithms for semi-autonomous vehicles. The application of deep learning is being used for understanding both the world around the car and human behavior inside it’. In his presentation in San Francisco he spoke about how deep neural network based approaches can contribute to each individual component of autonomous vehicles including scene perception, scene understanding, localisation, mapping, control, planning, driver sensing, and the end-to-end driving task.
Watch his presentation here.
At the upcoming Machine Intelligence in Autonomous Vehicles Summit in Amsterdam June 28 & 29, Pablo Puente Guillen will be touching on these safety issues and the challenges Toyota are facing with their AVs. His discussion will focus on the current safety needs and potential of highly automated vehicles (HAV) and the challenges to effectively assess the safety impact of HAV.
The Toyota Research project is concentrating on interactions with other vehicles and obstacles, and Guillen’s work with Toyota Motor Europe delves into these important topics, and he will be discussing the methods that they are using to train the vehicles to adopt the appropriate behaviours to coexist alongside human operated vehicles on the roads.
Toyota are hoping that following the announcement to work closely with several startups as well as MIT to implement the blockchain-connected hardware, they will attract the interest of large original equipment manufacturers (OEMs) to help the new research move into the market.
If you’re keen to learn more about the advances of deep learning and their impact on business and society, join RE•WORK at the Deep Learning Summit in San Francisco this 25 & 26 January.