AI-based light distribution optimization for adaptive control of automotive headlamps in road traffic

• Applicant: Professor Dr.-Ing. Tran Quoc Khanh
• Subject Area: Human Factors, Ergonomics, Human-Machine Systems ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing ; Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 450942921

The research project deals with the development of an AI-based control of the automotive light distribution to generate situationally optimized, dynamic light distributions. The aim of this research project is to break away from the conventional division of light distributions into low beam and high beam and to present holistic light distributions. In order to develop these light distributions, extensive studies will be carried out to record the current traffic area. Here, representative data for the German traffic area will be recorded first. The aim of the planned drives is to record the German traffic area in its entirety, taking into account different road classes analogous to their real occurrence. For the evaluation, the latest algorithms for the recognition of objects are trained individually and geometric distributions of different objects, cars, trucks, buses (each driving and parking), traffic signs (depending on class), pedestrians, cyclists are created. From these object distribution data as well as other recorded data such as speed, road class, road conditions etc. different traffic situations are automatically created.In addition to the recording of the German traffic area, contrast investigations and luminance analyses in the different road classes are carried out. These serve to determine the safety-relevant light requirements for motor vehicle drivers and to record the current light conditions in the German traffic area. Not only the recognizability distance and the necessary contrast are considered, but also the perception of brightness and homogeneity of the foreground illumination. This is essential, since in addition to an objective increase in safety, the subjective perception of safety also has a strong influence on the driver's well-being and behavior. The results of these investigations are also incorporated into the optimization of the situation-dependent light distributions.In addition, a further study records the gaze behavior of the drivers and calculates optimized light distributions by combining the object distributions and the gaze behavior in road traffic.These theoretical light distributions are then validated. In a first step, the various light distributions are displayed in a driving simulator, independent of the technology used, in the various virtually generated traffic situations. The acceptance and the feeling of safety of the test persons is tested virtually when using the different light distributions. In addition, a further study will test the extent to which drivers' visibility changes as a result of the newly generated light distributions.

• DFG Programme: Research Grants