DBL: Driver Behaviour Learning

该项目的目标是开发机器学习技术，以模拟北美正常驾驶条件下的驾驶员行为。这些学习到的模型将适用于改善各种不同功能的功能，包括但不限于自适应巡航控制（ACC）、变道辅助、自动驾驶（SAE L1至L4）。

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.