Flexible Modeling of High-Definition Matrix Headlights

Waldner, Mirko; Müller, Nathalie; Bertram, Torsten

doi:10.1109/aim52237.2022.9863399

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…80 Similarly, in 2021, of the eight (8) sampled authors who conducted a study on intelligent headlight beam intensity control and design of intelligent headlight, five (5) authors representing 62.5% used the sensor-based headlight beam intensity control approach, 5,43,81,82 and the remaining three (3) authors representing 37.5% used the machinelearning-based intensity control approach in the design of the intelligent headlight. 31,83,84 In 2022 out of the ten (10) sampled authors who conducted a study into the design of intelligent headlights, seven (7) authors representing 70% adopted the machine-learning-based headlight beam intensity control approach, 75,83,[85][86][87][88] , two (2) authors representing 20% utilized the sensor-based headlight beam intensity control approach, 40 and the remaining one (1) author representing 10% used the pulse width modulation approach for the design of the intelligent headlight. 89 Figure 4 illustrates that the predominant approaches for controlling intelligent headlight beams are machinelearning-based and sensor-based intensity control methods.…”

Section: The Utilization Rate Surveymentioning

confidence: 99%

A review of automotive intelligent and adaptive headlight beams intensity control approaches

Nkrumah,

Cai,

Jafaripournimchahi

2024

Advances in Mechanical Engineering

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The automotive headlight stands out as a critical vehicle component, particularly emphasized during nighttime driving. The high beam, designed for optimal driver visibility on long-distance roads, traditionally relies on manual control by the driver. However, this manual control poses challenges, particularly when the high beam light temporarily blinds oncoming drivers. The resultant dazzle for drivers of opposing vehicles is a significant concern. In response to these issues, there is a growing demand for adaptive and intelligent headlights that can autonomously adjust beam intensity. The intelligent headlight system takes on the responsibility of modifying the beam intensities without requiring explicit input from the drivers. This study aims to systematically review various approaches to controlling intelligent headlight beam intensity. The paper identifies four prominent approaches to intelligent headlight beam intensity control, recognized as widely used techniques. Furthermore, the study uncovers intriguing connections between some of these intensity control approaches. A survey on utilization rates indicates that sensor-based and machine learning (ML)-based intensity control approaches are the most commonly employed methods by automotive headlight designers. The paper concludes by providing insights into the future prospects of intelligent headlight technology, offering guidance for future researchers in this field.

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Section: The Utilization Rate Surveymentioning

confidence: 99%

A review of automotive intelligent and adaptive headlight beams intensity control approaches

Nkrumah,

Cai,

Jafaripournimchahi

2024

Advances in Mechanical Engineering

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“…Due to a Non-Disclosure Agreement (NDA) the setup cannot be explained in detail. In addition to the basic illumination directly in front of the vehicle, the matrix headlight in this paper has a modeled light module using the flexible modeling approach in [14]. The headlight module has a horizontal beam angle of ±20°, a vertical beam angle of ±5°, the aspect ratio is 4:1, similar to [15], and has 256 pixel rows and 1024 columns for a total amount of 262,144 pixels.…”

Section: Selective 3d Illumination Of Objectsmentioning

confidence: 99%

Energy-Efficient Illumination by Matrix Headlamps for Nighttime Automated Object Detection

Waldner

Müller

Bertram

2022

IJECER

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The contribution at hand presents a novel approach to generate dynamic energy-optimized illumination by matrix headlamps designed for automated driving. The approach consists of a novel basic minimal illumination adapted to the current road environment with minimum brightness and a light pixel control strategy to adjust the illumination of potential objects uniformly and selectively only. The approach was developed and optimized by considering the impact of other lighting functions such as Glare-Free High Beam and marker light on the quality of object detection and possible alternatives such as symbol projection with structured light. The concept achieves a similar quality of object detection as conventional high beam, but requires only around 16% of the energy. This shows the energy saving potential of automated vehicles in combination with novel headlight control strategies.

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Improving Computer Vision by Virtual Optimization of Matrix Headlights Using Surface Properties

Müller,

Waldner,

Bertram

2024

2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)

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Flexible Modeling of High-Definition Matrix Headlights

Cited by 4 publications

References 6 publications

A review of automotive intelligent and adaptive headlight beams intensity control approaches

A review of automotive intelligent and adaptive headlight beams intensity control approaches

Energy-Efficient Illumination by Matrix Headlamps for Nighttime Automated Object Detection

Improving Computer Vision by Virtual Optimization of Matrix Headlights Using Surface Properties

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