We present a new and independent determination of the local value of the Hubble constant based on a calibration of the tip of the red giant branch (TRGB) applied to Type Ia supernovae (SNe Ia). We find a value of H 0 = 69.8 ± 0.8 (±1.1% stat) ± 1.7 (±2.4% sys) km s−1 Mpc−1. The TRGB method is both precise and accurate and is parallel to but independent of the Cepheid distance scale. Our value sits midway in the range defined by the current Hubble tension. It agrees at the 1.2σ level with that of the Planck Collaboration et al. estimate and at the 1.7σ level with the Hubble Space Telescope (HST) SHoES measurement of H 0 based on the Cepheid distance scale. The TRGB distances have been measured using deep HST Advanced Camera for Surveys imaging of galaxy halos. The zero-point of the TRGB calibration is set with a distance modulus to the Large Magellanic Cloud of 18.477 ± 0.004 (stat) ± 0.020 (sys) mag, based on measurement of 20 late-type detached eclipsing binary stars, combined with an HST parallax calibration of a 3.6 μm Cepheid Leavitt law based on Spitzer observations. We anchor the TRGB distances to galaxies that extend our measurement into the Hubble flow using the recently completed Carnegie Supernova Project I ( CSP-I ) sample containing about 100 well-observed SNe Ia . There are several advantages of halo TRGB distance measurements relative to Cepheid variables; these include low halo reddening, minimal effects of crowding or blending of the photometry, only a shallow (calibrated) sensitivity to metallicity in the I band, and no need for multiple epochs of observations or concerns of different slopes with period. In addition, the host masses of our TRGB host-galaxy sample are higher, on average, than those of the Cepheid sample, better matching the range of host-galaxy masses in the CSP-I distant sample and reducing potential systematic effects in the SNe Ia measurements.

As a key technology of intelligent transportation system, the intelligent vehicle is the carrier of comprehensive integration of many technologies. Although vision-based autonomous driving has shown excellent prospects, there is still a problem of how to analyze the complicated traffic situation by the collected data. Recently, autonomous driving has been formulated as many tasks separately by using different models, such as object detection task and intention recognition task. In this study, a vision-based system was developed to detect and identity various objects and predict the intention of pedestrians in the traffic scene. The main contributions of this research are (1) an optimized model was presented to detect 10 kinds of objects based on the structure of YOLOv4; (2) a fine-tuned Part Affinity Fields approach was proposed to estimate the pose of pedestrians; (3) Explainable Artificial Intelligence (XAI) technology is added to explain and assist the estimation results in the risk assessment phase; (4) an elaborate self-driving dataset that includes several different subsets for each corresponding task was introduced; and (5) an end-to-end system containing multiple models with high accuracy was developed. Experimental results proved that the total parameters of optimized YOLOv4 are reduced by 74%, which satisfies the real-time capability. In addition, the detection precision of the optimized YOLOv4 achieved an improvement of 2.6% compared to the state-of-the-art.

VWorld is run by the Ministry of Land, Infrastructure, and Transport of South Korea and provides national spatial information, such as aerial images, digital elevation models, and 3D structural models. We propose herein an open platform for 3D spatial information based on WebGL using spatial information from VWorld. WebGL is a web‐based graphics library and has the advantage of being compatible with various web browsers. Our open platform is also compatible with various web browsers. Accordingly, it is easily accessible via the VWorld site and uses the three‐dimensional (3D) map program. In this study, we describe the proposed platform configuration, and the requests, management, and visualization approaches for VWorld spatial information data. Our aim is to establish an approach that will provide a stable rendering speed even on a low‐end personal computer without a graphics processing unit based on a quadtree structure. We expect that users will be able to visualize 3D spatial information through the VWorld open platform, and that the proposed platform will become the basis for various applications.

Digital tw,64’#1win technology based on building a virtual digital city similar to a real one enables the simulation of urban phenomena or the design of a city. A geospatial platform is an essential supporting component of digital twin cities. In this study, we propose a planetary-scale geospatial open platform that can be used easily in the most widely used game engine environment. The proposed platform can visualize large-capacity geospatial data in real time because it organizes and manages various types of data based on quadtree tiles. The proposed rendering tile decision method provides constant geospatial data visualization according to the camera controls of the user. The platform implemented is based on Unity3D, and therefore, one can use it easily by importing the proposed asset library. The proposed geospatial platform is available on the Asset Store. We believe that the proposed platform can meet the needs of various three-dimensional (3-D) geospatial applications.

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