In efforts to establish automated driving technologies to realise a collision free society, Honda R&D Co., Ltd., the R&D subsidiary of Honda Motor Co., Ltd., has signed a 5-year joint research and development contract with SenseTime Group Limited, a China-based IT company with strengths in the area of AI technologies.
SenseTime is highly regarded globally as a company that excels in image recognition technologies, in particular the recognition of moving objects, powered by deep learning technology, one of the most advanced AI technologies.
In this joint research project, combining SenseTime’s moving object recognition technologies with Honda’s AI algorithms for scene understanding, risk prediction and action planning, the two companies will develop highly-sophisticated automated driving technologies which will enable complex automated driving in urban areas.
Moreover, this joint research will not be limited to automated driving, as the two companies plan to expand the joint activities into the area of robotics.
Areas of Honda-SenseTime joint research and development
l AI algorithms to be applied for automated driving systems
- Scene understanding: Estimating the driving environment and the behaviors and intentions of pedestrians and vehicles
- Risk prediction: Predicting the future position of pedestrians and vehicles based on the results of estimating the driving environment and the intentions of pedestrians and vehicles
- Action planning: Deciding on the actions taken by the vehicle such as stopping, starting and avoiding, and then generating driving trajectory based on the results of risk prediction
l Large-scale computing technologies necessary to learn AI algorithms
l Technologies to package AI programs with on-board controllers
- Official company name: SenseTime Group Limited
- Head office: Hong Kong, China
- Business: Planning, development and operation of services powered by deep learning technologies
- Representative: Xu Li/ CEO
- Established: October 2014
- Proven technological strength: SenseTime has a track record of winning first place in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a competition to evaluate algorithms for object detection and image classification on a large scale, for two consecutive years (2015 and 2016).