Automated driving is considered a key technology for
reducing traffic accidents, improving road utilization, and enhancing
transportation economy and thus has received extensive attention from academia
and industry in recent years. Although recent improvements in artificial
intelligence are beginning to be integrated into vehicles, current AD technology
is still far from matching or exceeding the level of human driving ability. The
key technologies that need to be developed include achieving a deep
understanding and cognition of traffic scenarios and highly intelligent
decision-making.
Automated Vehicles, the Driving Brain, and
Artificial Intelligenceaddresses brain-inspired driving and learning
from the human brain's cognitive, thinking, reasoning, and memory abilities.
This report presents a few unaddressed issues related to brain-inspired driving,
including the cognitive mechanism, architecture implementation, scenario
cognition, policy learning, testing, and validation.