Theory of Collision Avoidance Capability in Automated Driving Technologies

To evaluate that automated vehicle is as safe as a human driver, a following question is studied: how does an automated vehicle react under extreme conditions close to collision? In order to understand the collision avoidance capability of an automated vehicle, we should analyze not only such post-extreme condition behavior but also pre-extreme condition behavior. We present a theory to analyze the collision avoidance capability of automated driving technologies. We also formulate a collision avoidance equation on the theory. The equation has two types of solutions: response driving plans and preparation driving plans. The response driving plans are supported by response strategy on which the vehicle reacts after detection of a hazard and they are highly efficient in terms of travel time. The preparation driving plans are supported by preparation strategy on which the vehicle simulates each hazard before detecting hazards and they are safer than the response driving plans but it is not always efficient. The theory suggests that applicative driving plan of automated vehicle is as follows: 1) the automated vehicle takes the response driving plan when there is a switchable preparation driving plan, 2) the automated vehicle takes the preparation driving plan that is safe but low-efficient compared with the response driving plan, otherwise. The theory also shows that any driving plan need to assume the upper limit of hazard growing speed of traffic environment in order to achieve the practical application of automated vehicles. How to determine the upper limit is a remaining problem, which is a social problem rather than a technical problem.