Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction

Online lane graph construction is a promising but challenging task in autonomous driving. Previous methods usually model the lane graph at the pixel or piece level, and recover the lane graph by pixel-wise or piece-wise connection, which breaks down the continuity of the lane. Human drivers focus on and drive along the continuous and complete paths instead of considering lane pieces. Autonomous vehicles also require path-specific guidance from lane graph for trajectory planning. We argue that the path, which indicates the traffic flow, is the primitive of the lane graph. Motivated by this, we propose to model the lane graph in a novel path-wise manner, which well preserves the continuity of the lane and encodes traffic information for planning. We present a path-based online lane graph construction method, termed LaneGAP, which end-to-end learns the path and recovers the lane graph via a Path2Graph algorithm. We qualitatively and quantitatively demonstrate the superiority of LaneGAP over conventional pixel-based and piece-based methods on challenging nuScenes and Argoverse2 datasets. Abundant visualizations show LaneGAP can cope with diverse traffic conditions. Code and models will be released at \url{https://github.com/hustvl/LaneGAP} for facilitating future research

VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene

High-definition (HD) map serves as the essential infrastructure of autonomous driving. In this work, we build up a systematic vectorized map annotation framework (termed VMA) for efficiently generating HD map of large-scale driving scene. We design a divide-and-conquer annotation scheme to solve the spatial extensibility problem of HD map generation, and abstract map elements with a variety of geometric patterns as unified point sequence representation, which can be extended to most map elements in the driving scene. VMA is highly efficient and extensible, requiring negligible human effort, and flexible in terms of spatial scale and element type. We quantitatively and qualitatively validate the annotation performance on real-world urban and highway scenes, as well as NYC Planimetric Database. VMA can significantly improve map generation efficiency and require little human effort. On average VMA takes 160min for annotating a scene with a range of hundreds of meters, and reduces 52.3% of the human cost, showing great application value

A hybrid approach to power system voltage security assessment

Ph.D.APS Meliopoulo

Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer

Learning Bird's Eye View (BEV) representation from surrounding-view cameras is of great importance for autonomous driving. In this work, we propose a Geometry-guided Kernel Transformer (GKT), a novel 2D-to-BEV representation learning mechanism. GKT leverages the geometric priors to guide the transformer to focus on discriminative regions and unfolds kernel features to generate BEV representation. For fast inference, we further introduce a look-up table (LUT) indexing method to get rid of the camera's calibrated parameters at runtime. GKT can run at $72.3$ FPS on 3090 GPU / $45.6$ FPS on 2080ti GPU and is robust to the camera deviation and the predefined BEV height. And GKT achieves the state-of-the-art real-time segmentation results, i.e., 38.0 mIoU (100m$\times$100m perception range at a 0.5m resolution) on the nuScenes val set. Given the efficiency, effectiveness, and robustness, GKT has great practical values in autopilot scenarios, especially for real-time running systems. Code and models will be available at \url{https://github.com/hustvl/GKT}.Comment: Tech report. Work in progres

A retrospective study of hepatitis B vaccination in preterm birth and low birth weight infants born to hepatitis B surface antigen-positive mothers: Time to close the policy-practice gap

National Immunization Program-version 2016 (ISIV-NIP-v2016) recommended a 4-dose hepatitis B vaccine (HepB) schedule for preterm birth (PTB) and low birth weight (LBW) infants born to HBsAg-positive mothers. However, the implementation of this immunization strategy in the past five years has not been fully evaluated in China. We reviewed the data of pregnant women and live-born infants from 24 hospitals between 2016 and 2021 in Lu’an, Anhui province, to estimate the prevalence of PTB, LBW, and hepatitis B virus (HBV) infected pregnant women. We analyzed the vaccination status of HepB and HBIG among PTB and LBW infants born to HBsAg-positive mothers. A total of 160 222 pregnant women and 159 613 live-born infants were included in this study. The estimated prevalence of PTB, LBW and HBV-infected pregnant women was 3.86% (range: 3.28%-5.10%), 2.77% (range: 2.12%-3.66%), and 3.27% (range: 3.03%-3.49%), respectively. We screened 340 PTB and LBW infants born to HBsAg-positive mothers between 2016 and 2020. We found that the coverage of HepB and HBIG among them was 100% and 99.39%. However, the timely vaccination rate of the HepB birth dose was only 78.59% and only four children (1.22%) received the 4-dose HepB as recommended by ISIV-NIP-v2016. The 4-dose of HepB for PTB and LBW infants born to HBsAg-positive mothers recommended by ISIV-NIP-v2016 was not fully implemented. A strong public health intervention should be taken to close the policy-practice gap in China in the future

Photocatalytic Membrane Reactor (PMR) for Virus Removal in Drinking Water: Effect of Humic Acid

In the actual water environment, the health risk of waterborne viruses is evaluated to be 101–104 times higher at a similar level of exposure compared with bacteria and has aroused strong concern in many countries in the world. Photocatalytic membrane reactor (PMR), a new process for virus inactivation in water, has gradually become one of the main tools to inactivate pathogenic organisms in water. However, there is relatively little attention to the effect of natural organic matters (NOMs) on the PMR system, which actually exists in the water environment. In this paper, the TiO2-P25, a common type in sales and marketing, was selected as the photocatalyst, and humic acid was regarded as the representative substance of NOMs for investigating thoroughly the influence of humic acid on virus removal by the PMR system. It was found that competitive adsorption between the virus and humic acid occurred, which markedly reduced the amount of virus adsorbed on the surface of the photocatalyst. Moreover, with humic acid, the direct contact behavior between the virus and the photocatalyst was blocked to some extent, and the disinfection of phage f2 by the active free radicals produced by photocatalysis was furthermore badly affected. Meanwhile, the special structure of humic acid, which made humic acid be able to absorb light of 270–500 nm, led to the reduction of photocatalytic efficiency. Further experiments showed that when there was a certain concentration of humic acid in water, intermittent operation mode or higher membrane flux (>40 L/(m2·h)) was selected to partly alleviate the adverse effects of humic acid

Clonally related visual cortical neurons show similar stimulus feature selectivity.

A fundamental feature of the mammalian neocortex is its columnar organization. In the visual cortex, functional columns consisting of neurons with similar orientation preferences have been characterized extensively, but how these columns are constructed during development remains unclear. The radial unit hypothesis posits that the ontogenetic columns formed by clonally related neurons migrating along the same radial glial fibre during corticogenesis provide the basis for functional columns in adult neocortex. However, a direct correspondence between the ontogenetic and functional columns has not been demonstrated. Here we show that, despite the lack of a discernible orientation map in mouse visual cortex, sister neurons in the same radial clone exhibit similar orientation preferences. Using a retroviral vector encoding green fluorescent protein to label radial clones of excitatory neurons, and in vivo two-photon calcium imaging to measure neuronal response properties, we found that sister neurons preferred similar orientations whereas nearby non-sister neurons showed no such relationship. Interestingly, disruption of gap junction coupling by viral expression of a dominant-negative mutant of Cx26 (also known as Gjb2) or by daily administration of a gap junction blocker, carbenoxolone, during the first postnatal week greatly diminished the functional similarity between sister neurons, suggesting that the maturation of ontogenetic into functional columns requires intercellular communication through gap junctions. Together with the recent finding of preferential excitatory connections among sister neurons, our results support the radial unit hypothesis and unify the ontogenetic and functional columns in the visual cortex

Developments of Space Debris Laser Ranging Technology Including the Applications of Picosecond Lasers

Debris laser ranging (DLR) is receiving considerable attention as an accurate and effective method of determining and predicting the orbits of space debris. This paper reports some technologies of DLR, such as the high pulse repetition frequency (PRF) laser pulse, large-aperture telescope, telescope array, multi-static stations receiving signals. DLR with a picosecond laser at the Shanghai Astronomical Observatory is also presented. A few hundred laps of space debris laser-ranging measurements have been made. A double-pulse picosecond laser with an average power of 4.2 W, a PRF of 1 kHz, and a wavelength of 532 nm has been implemented successfully in DLR, it’s the first time that DLR technology has reached a ranging precision at the sub-decimeter level. In addition, the characteristics of the picosecond-pulse-width laser transmission with the advantages of transmission in laser ranging were analyzed. With a mode of the pulse-burst picosecond laser having high average power, the DLR system has tracked small debris with a radar cross-section (RCS) of 0.91 m2 at a ranging distance up to 1726.8 km, corresponding to an RCS of 0.1 m2 at a distance of 1000 km. These works are expected to provide new technologies to further improve the performance of DLR

Vision-based Uneven BEV Representation Learning with Polar Rasterization and Surface Estimation

In this work, we propose PolarBEV for vision-based uneven BEV representation learning. To adapt to the foreshortening effect of camera imaging, we rasterize the BEV space both angularly and radially, and introduce polar embedding decomposition to model the associations among polar grids. Polar grids are rearranged to an array-like regular representation for efficient processing. Besides, to determine the 2D-to-3D correspondence, we iteratively update the BEV surface based on a hypothetical plane, and adopt height-based feature transformation. PolarBEV keeps real-time inference speed on a single 2080Ti GPU, and outperforms other methods for both BEV semantic segmentation and BEV instance segmentation. Thorough ablations are presented to validate the design. The code will be released at \url{https://github.com/SuperZ-Liu/PolarBEV}