PhD student for PhD in adaptive headlight sensor systems

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Number: MER0003WK3 In Group Research & Mercedes-Benz Cars Development (RD), we design the automotive generations of the future. We mean innovative products with the highest quality and efficient development processes. We are already working on vehicles that will secure the technology leadership of Mercedes-Benz in the future. In the light systems department, we are responsible for the components of the exterior lighting systems for all Mercedes-Benz cars. Our stated goal is to develop the best solutions that can be measured by the factors of functionality, quality, cost and time. We always focus on customer benefits. In the field of automotive lighting technology, Mercedes-Benz is the world leader with the innovative DIGITAL LIGHT lighting systems. Problem: Nightly traffic represents a significant challenge for the safety and performance of both human drivers and automated driving functions. Wrong and badly adjusted headlights can lead to a glare of the counter traffic. In addition, You restrict the functionality of adaptive light systems and can lead to a reduction in the visibility range. The aim of the work: the development of an adaptive, integrative system for optimal networking between vehicle sensors and intelligent headlights, this is intended to make a decisive contribution to increasing driving safety and the further development of automated light functions. Research focuses: In the context of this work, innovative approaches to the implementation of the stated objective are to be explored and developed. These challenges include: Possible research priorities include, but are not limited to: Precise headlight adjustment and vehicle position detection: Examination of methods for the precise determination of the headlight adjustment by the evaluation of camera images, inertial sensor data (IMU) and potentially further sensors - this also includes the precise detection of the vehicle position relative to the roadway (e.g. by means of horizon detection, direction of movement) as an input for adaptive light range regulation and topography compensation (e.g. in addition to card data)

Real-time light adaptation and range increase: Development of dynamic algorithms for synchronizing the light distribution of headlight settings based on available sensor data to optimize contrasts, minimize glare and maximize the detection range of objects

Pattern Projection (PP): Research and development of camera-exclusive projection patterns for enhanced environmental perception and feature extraction

Potential applications include the vehicle position, headlight adjustment detection, detection of ''Lost Cargo' or improved classification of objects

Predictive light and object detection: Development of predictive algorithms for a predictive partial beam and an anticipate object detection, in particular in complex driving situations such as narrow curves, in order to be able to react early on to potential hazards

Foreseen steps and methodology: The processing of research questions takes place in several successive steps

Scientific foundations and state of the art: Comprehensive analysis of the current scientific literature and the technological state of the art in vehicle lighting, computer vision, sensor fusion and machine learning

Concept development and prototypical implementation: Development of detailed solutions. In the first step digital protection and subsequent construction of prototypical systems from camera, sensor and light modules in the laboratory

Concept presentation and validation: Implementation of the findings from the digital and prototype phase into a ready-to-use test carrier

Validation of the integrated overall system under real and simulated test conditions

Adjustment requirement is the support of the doctoral project by a university lecturer. The selection of a corresponding person is the responsibility of the doctoral student. The activity can begin from April 2026.

Graduate degree in engineering, electrical engineering, information system technology, vehicle technology, mechatronics, physics or the like

German and English skills

MS Office Knowledge (PowerPoint, Excel, Word)

Programming languages: Python, C++

Experience with AI advantageous, for example with Tensorflow, Pytorch

Knowledge of Computervision (machine vision), control systems, sensor fusion, vehicle electronics

Ideal experience in vehicle development

Embossed communication and team skills

Responsibility

High level of commitment, initiative and commitment

Quick conception and fun to penetrate complex topics

driving licence class B

Additional information: Doctorate in the Mercedes-Benz Group! Benefit from our know-how, an international expertise network, research materials, work insights and personal support by mentors – in addition to your university. Further information can be found here. We look forward to your online application with CV, Letters and Certificates. Please do not forget to mark your documents as ''relevant for this application' in the online form and note the maximum file size of 5 MB. Disabled and equalized applicants are welcome! The severely disabled representative (SBV-Sindelfingen@mercedes-benz.com) is happy to support you in the application process. HR Services will be happy to help you with questions about the application process. You can reach us by email via myhrservice@mercedes-benz.com or by phone at 0711/17-99000 (Mo-Fr 10-12am & 13-15am).

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