The deployment of laser-based products in autonomous vehicles is advancing to enhance autonomous driving capabilities. In this special feature, we introduce the latest developments in the trends of next-generation optical fiber communication standards, the core technology of surface-emitting lasers, and the application technologies of LiDAR, a key sensor connected to the network.

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The automotive industry is currently undergoing a major transformation. With the spread of autonomous driving and advanced driver assistance systems, many vehicles are being equipped with such sensors as in-vehicle cameras, LiDAR, and radar. To stably transmit the data from these sensors, the speed of in-vehicle communication is increasing. This paper introduces trends in the standardization of in-vehicle communications and explains the high-speed communication requirements for in-vehicle optical communications that JASPAR is studying as well as multi-vendor initiatives.

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With the ever-increasing need for faster data communication in cars, electrical interconnects are beginning to show bandwidth limitations and call for optical interconnects. VCSEL-based multimode interconnects are a well proven technology in data centers and therefore a natural candidate to also enter automotive interconnects. Automotive, however, requires operation under more stringent environmental conditions such as temperature range between −40°C and 125°C. This has led to a new set of specifications for the optical links, among which is the VCSELs wavelength at 980 nm. The paper describes the properties of 980 nm VCSELs and its use in Automotive environment.

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This paper discusses the reliability of 850- and 980-nm band VCSELs for automotive applications, based on failure physics and reliability estimation methods that applied to edge-emitting semiconductor lasers used in traditional optical fiber communication systems. The current VCSELs, which are fabricated using matured crystal growth and process technology, are structurally stable and have better reliability at high temperature operation than traditional edge-emitting type lasers. The current VCSELs are promising optical sources for automotive applications.

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LiDAR has higher performance than other types of sensors in distance measurement accuracy. However, the usage of LiDAR in automotive industry is not as much as what was expected, due to its high-cost. Under these circumstances, we are developing a cost effective LiDAR that uses our unique scanning method. In addition, we are applying a cleaner system to prevent surface contamination which degrades the performance of LiDAR.

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It has been a long time since the automated driving boom was announced. However, it has not been as widespread as initially expected by society. The government is currently focusing on the widespread use of Level 4 automated EV shuttle buses in order to solve social issues. This paper reviews these situations and outlines the environment recognition methods using LiDAR (Light Detection And Ranging), one of the main sensors for automated driving. The functions required for automated driving are self-localization and obstacle recognition surrounding the vehicle, and the algorithms for realizing these functions are explained. Additionally, for research on environmental recognition by deep neural network using millimeter- wave radar, which the author is working on, examples of methods for generating the ground truth are introduced since these are very critical for deep neural networks to ensure high estimation accuracy.

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