Driver assistance systems have an enormous potential for reducing injuries and property damage in the urban context. In an urban accident prevention scenario, the optimal maneuver could involve braking, steering support, or a combination of swerving and braking. Research activities in this sub-project are focused on designing algorithms and functions that are suitable for determining which maneuver has the best chance of reducing the risk posed by a collision threat in an urban setting. Key variables defining the operation of the system involve the level and intensity of support provided by the assistance function as well as the timing of possible interventions.
An alert driver with a good overview of a potential accident situation will take multiple factors into account in deciding whether to swerve or brake, such as relative speed, heading, and projected degree of overlap with an object or road user in conflict. Similarly, intelligent assistance functions will need to consider all relevant factors for optimal support and intervention timing.
Automatic emergency braking systems taking driver swerving into account
In this research, the intensity of support provided by a function is not specified from the outset, but is considered as a variable to be optimized in the course of function design. This strategy for functional optimization accounts for the situations in which a warning or stimulus for evasive driver action may be effective. Assessment of more intense interventions, right up to automatic braking or swerving, requires comparison of the consequences of different functional designs.
Additionally, close coordination with the UR:BAN project “Human Factors in Traffic” will ensure that the assistance systems developed in this subproject will be targeted precisely to the requirements of drivers in an urban environment. This targeting is particularly important for the design of the human machine interface (HMI).