VCSEL chip structure and packaging optimization design for high-power VCSEL light source modules

Lifetime prediction of a multi-chip high-power LED light source based on artificial neural networks

Intelligent Automation (IA) in automobiles combines robotic process automation and artificial intelligence, allowing digital transformation in autonomous vehicles. IA can completely replace humans with automation with better safety and intelligent movement of vehicles. This work surveys those recent methodologies and their comparative analysis, which use artificial intelligence, machine learning, and IoT in autonomous vehicles. With the shift from manual to automation, there is a need to understand risk mitigation technologies. Thus, this work surveys the safety standards and challenges associated with autonomous vehicles in context of object detection, cybersecurity, and V2X privacy. Additionally, the conceptual autonomous technology risks and benefits are listed to study the consideration of artificial intelligence as an essential factor in handling futuristic vehicles. Researchers and organizations are innovating efficient tools and frameworks for autonomous vehicles. In this survey, in-depth analysis of design techniques of intelligent tools and frameworks for AI and IoT-based autonomous vehicles was conducted. Furthermore, autonomous electric vehicle functionality is also covered with its applications. The real-life applications of autonomous truck, bus, car, shuttle, helicopter, rover, and underground vehicles in various countries and organizations are elaborated. Furthermore, the applications of autonomous vehicles in the supply chain management and manufacturing industry are included in this survey. The advancements in autonomous vehicles technology using machine learning, deep learning, reinforcement learning, statistical techniques, and IoT are presented with comparative analysis. The important future directions are offered in order to indicate areas of potential study that may be carried out in order to enhance autonomous cars in the future.

The transmission of light through tissue is used in noninvasive monitoring, in particular photoplethysmography. Investigations involving the transmission of wavelengths absorbed by bilirubin (short wavelength visible light) have been limited, due to strong absorption by haemoglobin. Achieving transmission of these wavelengths through tissue may advance noninvasive monitoring of substances like bilirubin. This work investigates the use of high power light sources together with improvements in signal-to-noise ratio as a means of enabling the transmission of strongly absorbed light through tissue. A custom device using multiple high-power short-wavelength visible light sources together with low power red and infrared sources, and background light cancellation to improve signal-to-noise ratio, was constructed. Transmission of 454-1200 nm light through tissue was achieved, with pulsations present in measured signals. The transmission through tissue of multiple wavelengths of strongly absorbed light can be achieved by using high power light sources in conjunction with cancelling the effect of background light. Use of these techniques may allow investigations into the noninvasive monitoring of substances such as bilirubin using photoplethysmography.

The sensitivity is an important performance for a polarisation maintaining fibre (PMF) loop mirror (PM-FLM) sensor based on voltage demodulation. This paper investigates the method of improving the strain sensitivity of a PM-FLM based on voltage demodulation, including the demodulation principle, the derivation of the output light power equation, and experimentally studies on the strain sensitivity of a PM-FLM with different narrow-band input light source. The results show that the PM-FLM using a high-power light source as input has a high strain sensitivity but a small linear range of strain measurement, and the PM-FLM using a low-power light source as input has a low strain sensitivity but a large linear range of strain measurement. Hence, a high-power narrow-band light source as input can be chosen to improve the strain sensitivity, and the authors can also reduce the input light source power to enlarge the linear range of strain measurement.

A high-power wideband radio-frequency (RF) intensity modulated continuous wave light source is demonstrated. The high-power dual-frequency light source is obtained via a dual-frequency laser signal seeding fiber power amplifier. A diode laser pumped dual-frequency laser is built as the seed and a diode laser pumped three-stage Yb3 + doped large mode area fiber power amplifier is used to enhance the output power to 50 W. In the dual-frequency seed laser, a coupled cavity composed of the Nd:YAG gain crystal and output coupler is used as the mode selector and enforces single longitude mode to oscillate. Two quarter wave plates are inserted in the laser cavity to lift the frequency degeneration of the two orthogonally polarized modes. By changing the angle between the fast axes of the two quarter wave plates, the frequency difference between the two orthogonally polarized modes can be tuned from 30 MHz to 1.5 GHz. The standard difference of beat frequency is 1.6144 MHz and stability is 1.52% when a frequency difference of output dual-frequency laser is 250 MHz. This stable dual-frequency seed signal is amplified via a diode pumped Yb3 +-doped fiber power amplifier. In order to suppress amplified spontaneous emission and other nonlinear effects, a three-stage fiber amplification system is used. The first stage is a diode pumped fiber (5 m, 6/125 m, NA = 0.13) power amplifier. The pump power is fixed at 600 mW. The input dual frequency signal is 3.2 mW, and it is amplified to several hundred mW by the first fiber power amplifier. The second fiber amplifier is a diode laser pumped fiber (5 m, 10/125 m, NA = 0.075/0.46) amplifier. The pump power is fixed at 10 W, and the dual frequency signal is amplified to sub watts after the second fiber amplifier. A 5 m large mode area fiber (25/250 m, NA=0.065/0.46) is used in the final amplification. A maximum amplified power of 50.2 W is obtained when the pump power is 70 W in the experiment. The signal-to-noise ratio of the beat note increases from 25 dB to 40 dB via amplification. The output power fluctuation of the amplified signal at 50 W is smaller than 0.1 W during 30 min. The RF frequency stability is well maintained during the amplification, and the beat-note frequency instability is 1.777 MHz. This high-power dual-frequency light source with wide beat note frequency bandwidth has potential applications in dual-frequency coherent lidar system for long distance ranging and imaging or underwater detections after the frequency has been doubled to 532 nm.

The integration of Artificial Intelligence (AI) in autonomous vehicles represents a transformative leap towards safer, more efficient, and technologically advanced transportation systems. This abstract provides a comprehensive overview of the dynamic landscape where AI converges with autonomous vehicles, examining the synergies, challenges, and far-reaching implications of this groundbreaking integration AI-Powered Perception and Decision-Making: Delving into the technological core, the abstract explores how AI empowers autonomous vehicles with sophisticated perception systems, such as computer vision and sensor fusion. It discusses the role of machine learning algorithms in real-time decision-making, enabling vehicles to adapt to dynamic road conditions and unforeseen circumstances. Challenges in Autonomy: Recognizing the complexity of autonomous systems, the abstract addresses challenges such as handling edge cases, ensuring robustness against adversarial attacks, and navigating regulatory and ethical considerations. It emphasizes the importance of addressing these challenges to foster public trust and acceptance of autonomous vehicles. Human-AI Interaction in Autonomous Vehicles: Examining the interface between humans and AI-driven vehicles, the abstract discusses the importance of designing intuitive and trustworthy communication channels. It explores advancements in natural language processing and gesture recognition, fostering seamless collaboration between humans and autonomous systems. Regulatory Landscape and Ethical Considerations: Recognizing the pivotal role of regulations, the abstract discusses the evolving regulatory landscape for autonomous vehicles. It delves into ethical considerations surrounding AI decisions in critical situations, underscoring the need for a harmonized approach to ensure responsible AI deployment in autonomous driving scenarios.

Wavelength or light intensity demodulation method for a polarization maintaining fiber loop mirror (PM-FLM) sensor is not only expensive but also unsuitable for vibration monitoring. This paper studies the voltage demodulation principle and explores theoretically the influence of light source on the sensitivity. Then a PM-FLM sensor is applied to vibration monitoring. A low-power narrow-band light source reflected from FBG and a high-power laser light source are used respectively as input. The time domain voltage signals of vibration from a photo-detector are collected by a data acquisition card and converted via a fast Fourier transform algorithm. The experimental result shows that a PM-FLM sensor using a high-power narrow-band light source as input has a higher sensitivity to vibration than the one using a low-power narrow-band light source. In practical application, we can choose a high-power narrow-band light source as input to improve the sensitivity to vibration.

Flip-chip VCSELs with backside emission revolutionize 3D sensing systems. Etching lenses directly into the GaAs substrate is the most compact way to integrate optics with the VCSEL. Various lens structures can be implemented enabling collimation as well as the uniform illumination of a defined field of view. Superior to separate optical elements the integrated optics avoids the need for individual alignment of laser die and optics and makes them an irremovable part of the chip, which is beneficial for long-term laser safety. The realization of both contacts on the epitaxy side enables flip-chip assembly without the need for wire bonds. This facilitates thermal management compared to top-emitting VCSELS and reduces system impedance. Individually addressable zones can be easily implemented, contacting is done via fine-pitch copper pillars. Backside emitting VCSELs can be designed for a large emission area thus enabling a very high active area of the array. This is especially useful for operating schemes with low duty-cycle enabling ultra-high pulse power output per chip area. VCSEL chips with integrated flood illumination optics for time-of-flight applications with narrow or broad field of view will be presented. Addressability of multiple zones on a chip can be implemented for enhanced illumination and sensing schemes. The ViBO technology platform allows for a wide variation of VCSEL chip properties and a significant miniaturization of illumination systems.

Artificial Intelligence (AI) has become a cornerstone in advancing autonomous vehicles, enabling realtime decision making, object detection, and automation in driving systems. This study aims to explore key AI innovations, including Machine Learning (ML) algorithms, computer vision, and reinforcement learning, that contribute to the development of autonomous vehicles. A qualitative approach} was adopted to analyze both current applications and future innovations of AI in autonomous vehicles. The study highlights various current AI applications in autonomous vehicles, such as automated safety features, advanced navigation systems, and adaptive cruise control. These technologies demonstrate how AI enhances vehicle functionality and improves safety in today driving environment. Looking ahead, AI is expected to enable full autonomy in vehicles, foster integration with smart city infrastructures, and drive innovations in fleet management. These advancements are anticipated to significantly improve vehicle safety, operational efficiency, and the overall user experience, solidifying AI as the fundamental technology for the future of intelligent transportation systems.

SummaryThe recent sale of an artificial intelligence (AI)-generated portrait for $432,000 at Christie's art auction has raised questions about how credit and responsibility should be allocated to individuals involved and how the anthropomorphic perception of the AI system contributed to the artwork's success. Here, we identify natural heterogeneity in the extent to which different people perceive AI as anthropomorphic. We find that differences in the perception of AI anthropomorphicity are associated with different allocations of responsibility to the AI system and credit to different stakeholders involved in art production. We then show that perceptions of AI anthropomorphicity can be manipulated by changing the language used to talk about AI—as a tool versus agent—with consequences for artists and AI practitioners. Our findings shed light on what is at stake when we anthropomorphize AI systems and offer an empirical lens to reason about how to allocate credit and responsibility to human stakeholders.

The introduction to autonomous vehicles and intelligent transportation systems, as well as related work on autonomous vehicles and intelligent transportation systems, are described in this chapter. Aside from that, it has a chapter on autonomous intelligent vehicles and autonomous vehicles. Issues and challenges in autonomous intelligent vehicles, as well as the framework of an intelligent transportation system. In addition, the chapter discusses research opportunities in autonomous intelligent vehicles, IPv4 and IPv6 issues, and the future of IPv9 for vehicles, as well as a survey on autonomous vehicles in highway scenarios. During the last century, the automobile industry has excelled at producing cars that are both safe and affordable. Because of significant advancements in the Internet of things (IoT), the programmable logic controller (PLC), and other aspects of computing, autonomous vehicles (AVs) are becoming a reality. Cars, trucks, and other vehicles that don’t need to be plugged in to get power are referred to as self-sufficient vehicles. The multi-agent-based transportation system, which demonstrates how vehicles, drivers, roads, infrastructure, and vehicles all work together, is one of the most important intelligent transportation systems because it demonstrates how all of these things work together. To solve and manage traffic problems, an intelligent transportation systems (ITS) system employs a variety of technologies. Communication and control, vehicle sensing, and electronics are among these technologies. ITS has been used in the developed world for the past two decades. It is still a novel concept in the developing world. Sensors and computers work together in the Internet of things to store and process data, and data analytics is used to make the traffic system run more smoothly.KeywordsAutonomous vehicle (AV)Intelligent transportation system (ITS)Autonomous intelligent vehicle (AIV)Advanced driver assistance system (ADAS)Advanced driving system (ADS)

Guest editorial: Decision making and control for connected and automated vehicles

We present results for lattice matched (AlxGai..xAs, x=0.5 and x=0.0) and lattice mismatched (InxGai..xAs, x□0.25) growth on patterned GaAs (100) substrates. For the AlGai..xAs structures, the GaAs substrates were patterned in the form of elongated mesas parallel to [011 II with widths of approximately 3 tim. Interfacet migration effects observed on the nesas via cross-section transmission electron microscope studies are explained in terms of a ledge-ledge interaction on the vicinal surfaces formed due to growth on the mesas. InxGai..xAs (x□0.25) structures were grown on GaAs (100) substrates patterned in the form of elongated mesas parallel to [01 11 with widths of approximately 1 tim. This patterning direction was chosen since under cutting in the [0 1 1] direction eliminates inter-facet migration effects so that compositional change induced strain effects can be minimised. For x □0.15, we find a reduction in misfit dislocation densities in films upto five times the nominal critical thickness for growths on the patterned mesas as compared to the growths on the corresponding non patterned regions. For x=0.25 no such difference is observed and a large number ofthreading dislocations ( around iO cm2) are found in both the patterned and the non patterned regions. This is believed to be a consequence of the onset ofa 3-D island growth mode. Finally we present some results for the growth of InO5Gaj75As I AlAs resonant tunneling diode (RTD) structures and a 100 period InjUGaU8As (80 A) IGaAs (160 A) Multiple Quantum Well (MQW) such as suited for spatial light modulator (SLM) structures on GaAs (100) substrates patterned in both directions on a length scale of 12 to 20 tm. For the RTD structures we conclude that benefits from patterning are expected for x□0.25 provided the growth kinetics are appropriately adjusted to prevent 3D island growth mode. For the MQW -SLMstructure we demonstrate superior optical properties for the growth in the patterned region and a corresponding absence of threading dislocations in the central region of the mesas.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Autonomous vehicle is a major application of Artificial Intelligence. Artificial Intelligence systems, that use machine learning techniques to gather, analyze, and transfer data, are used in autonomous vehicles to make judgments that would normally be made by humans. Over the last decade, researchers and the car industry became very active in the deployment of driverless cars as they can greatly increase safety of the vehicle, rate of traffic accidents, and the effect of climate on automobiles. In implementing automated driving, software architecture plays a crucial function. The ability of driverless vehicles to work in real-world situations in a healthy and stable manner is currently being studied in public roads. In this paper, we have explained the background of Artificial Intelligence and how its applications are helping the world getting smarter. The role of Artificial Intelligence in autonomous vehicle industry has been discussed in this paper. Also, we tried to describe the relation of Artificial Intelligence and autonomous vehicles as well as presented the evolution of Artificial Intelligence from 1936 to 2020 with the help of a systematic review and explained how Artificial Intelligence is involved in the success of autonomous vehicles.

A new high-power blue LED light source system for portable OSL instrument is presented. High-power blue LED light source system with optical components are arrange in order to realize high radiation intensity of the stimulate light source, high-power blue LED luminous intensity are controlled by multi-channel controllable constant source. The experiment results show that the system is simple, small, blue uniform stability and high strength, as the stimulate light source for the portable OSL instruments.