We are providing the technology to build a car that is incapable of causing a crash, regardless of the skill or condition of the driver.
We are developing automated driving technology to allow driverless cars, providing mobility for those who cannot drive including the elderly and individuals with special needs.
We are creating a platform and ecosystem for robots that can partner with humans and help with key tasks, allowing people to extend their independence.
We are using artificial intelligence to discover new methods for discovering advanced materials.
Toyota views the relationship between a driver and the car as teammates working together to ensure a safe, comfortable, and fulfilling journey. TRI is applying this philosophy to automated driving by pursuing technology that makes vehicles safer and driving both more fun and convenient.
The three components of automated driving are perception, prediction and planning, and TRI is making significant advances in each area.
TRI is developing two different automated driving modes in parallel – Guardian and Chauffeur – which gives drivers a choice. Guardian mode uses technology to constantly monitor the human’s driving task, intervening only when necessary to protect the vehicle from a potential crash. In Chauffeur mode, the technology takes all responsibility for driving and vehicle occupants are strictly passengers. The underlying technology for both modes is the same, and it further forges the collaboration between human and machine.
Future mobility is not just about creating new ways to move people across town. The technology being developed could also be applied to moving people and objects throughout the home.
Government estimates show a significant upswing in the population share of elderly adults in the United States and Japan over the coming decade, and TRI is developing service robots that can assist with in-home care. TRI is making breakthroughs in situational awareness and manipulation that will allow robots to detect, grasp and lift objects of all different shapes, like groceries, and put them away.
Artificial intelligence(AI) and machine learning(ML) are the backbone of TRI’s work in advancing technology. TRI is making strong advances in deep learning computer perception models, which is core to its work in automated vehicles and robotics.
For automated vehicles, this allows the system to have greater situational awareness of the vehicle surroundings, detecting objects and roadways, and predicting a safe driving route. TRI has made its new architectures faster, more efficient and more highly accurate.
In robotics, TRI is applying computer vision and artificial intelligence, which allows robots to detect the physical presence of humans and objects, note their locations, and retrieve objects for humans when prompted. Further, TRI is advancing an AI concept that can detect objects, track a person’s skeletal pose and eye gaze, is capable of depth and thermal perception, and can understand its surroundings in order to engage with humans and help keep them safe, and comfortable.
TRI is applying AI to accelerate scientific discovery of advanced materials for future mobility. This approach enables TRI to develop tools and processes that can help identify new advanced battery materials and fuel cell catalysts for use in future zero-emissions and carbon-neutral vehicles and reduce the time scale for new materials development. We are collaborating with research entities, universities and companies on materials discovery research, investing approximately $35 million over the next four years.See Our Recent Materials Discovery News
As TRI advances technology for automated driving and human assist robots, special emphasis is being placed on the user experience(UX), which is the interaction between human and machine. When researching conceptual approaches, TRI follows a user-centric design model, a process that invites feedback from human users at every phase from initial idea to development.
For automated vehicles, TRI is probing effective methods of transferring vehicle control between the human driver and the autonomous system in a range of challenging scenarios. In robotics, TRI is exploring methods for how robots engage with humans.