DBL: Driver Behaviour Learning
Natural Sciences and Engineering Research Council of Canada
- Grant type: Collaborative Research and Development Grants
- Years: 2018/19 to 2019/20
- Total Funding: $348,511
University of Waterloo
The project goal is to develop machine learning technology to mimic driver behaviour under normal driving conditions in North America. Such learnt models would be applicable to improve the functionality of a variety of different features including, but not limited to Adaptive Cruise Control (ACC), Lane Change Assist, automated driving (SAE L1 to L4).*Furthermore the project goal is to develop machine learning technology that supports updating while the driver is operating the vehicle. The application is to allow deploying basic models in vehicles at the point of sales, and then later have the vehicles adapt to driving behaviour of the owner.*The project challenges are to identify base technology in machine learning suitable for the problem, then adapt it to the specific needs of the automotive industry and driving, and finally actually validating the technical feasibility, viability, and efficacy of the technology with real world data.*
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