Real-time automotive night-vision system for drivers to inhibit headlight glare of the oncoming vehicles and enhance road visibility

Mandal, Gouranga; Bhattacharya, Diptendu; De, Parthasarathi

doi:10.1007/s11554-021-01104-z

Cited by 15 publications

(7 citation statements)

References 42 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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“…where a is a constant, I denotes luminance, and Se denotes human eye response. Equation (3) shows the correspondence between luminance and human eye response, indicating that the human eye is more sensitive to changes in darkness. The simulated human response to light has also appeared in various image processing [34,35].…”

Section: Related Workmentioning

confidence: 99%

“…Each algorithm has its own implementation and varying effects. Notably, Mandal G. et al [3] have employed frame region segmentation combined with localized enhancement techniques, effectively highlighting enhancement information. However, while their approach achieves good overall visual enhancement and glare suppression, it involves more complex image processing.…”

Section: Introductionmentioning

confidence: 99%

GS-AGC: An Adaptive Glare Suppression Algorithm Based on Regional Brightness Perception

Li,

Wei,

Pan

et al. 2024

Applied Sciences

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Existing algorithms for enhancing low-light images predominantly focus on the low-light region, which leads to over-enhancement of the glare region, and the high complexity of the algorithm makes it difficult to apply it to embedded devices. In this paper, a GS-AGC algorithm based on regional luminance perception is proposed. The indirect perception of the human eye’s luminance vision was taken into account. All similar luminance pixels that satisfied the luminance region were extracted, and adaptive adjustment processing was performed for the different luminance regions of low-light images. The proposed method was evaluated experimentally on real images, and objective evidence was provided to show that its processing effect surpasses that of other comparable methods. Furthermore, the potential practical value of GS-AGC was highlighted through its effective application in road pedestrian detection and face detection. The algorithm in this paper not only effectively suppressed glare but also achieved the effect of overall image quality enhancement. It can be easily combined with the embedded hardware FPGA for acceleration to improve real-time image processing.

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“…These systems, mostly for cars, automatically change the intensity of the headlight beams to improve road safety [8]. Research has indicated that these systems have a critical role in lowering accidents caused by glare, especially at night [9]. Light-dependent resistors (LDRs) are one type of sensor that can detect cars coming and modify light intensity accordingly [10].…”

Section: Review Related Literaturementioning

confidence: 99%

“…The goal is to use inexpensive parts without sacrificing the system's functionality so that adaptive headlamp technology can benefit more cars than just luxury ones [18]. A fascinating study area could involve adapting similar bicycle technologies in the future [19]. Adaptive headlights on bicycles have the potential to greatly increase biker safety, particularly in urban areas with changing lighting conditions [20].…”

Section: Review Related Literaturementioning

confidence: 99%

Automatic Headlight Intensity Controller for Motorcycle

Calma

2023

AIR

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Developing a technology that can enhance nighttime driving by minimizing the use of high beams is the main objective of this research development. A system that complied with the requirements was constructed using the Inputs Processes Output paradigm. The technology is quite helpful in comfort driving—a common problem for drivers behind you who get a sudden glare in their eyes. We came up with the concept to build an automated headlamp intensity controller. An automatic headlight intensity high beam light controller that is affordable and easy to install. All the necessary hardware and components for the suggested design were used. Experiments indicate that when facing other drivers, the controller automatically switches on and off the high and low beam lights to give the driver the proper command. The system's ability to detect light from the opposite direction—quantified in intensity and distance—was found upon testing. Consequently, the user rate and assessed the system, and the system and the automated headlight functioned as intended. The user gave the system a Strongly Agree rating in intetion to uses 4.86.

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Real-time automotive night-vision system for drivers to inhibit headlight glare of the oncoming vehicles and enhance road visibility

Cited by 15 publications

References 42 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

GS-AGC: An Adaptive Glare Suppression Algorithm Based on Regional Brightness Perception

Automatic Headlight Intensity Controller for Motorcycle

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