Robust Intensity-Based Localization Method for Autonomous Driving on Snow-Wet Road Surface

金沢大学新学術創成研究機構Autonomous vehicles are being developed rapidly in recent years. In advance implementation stages, many particular problems must be solved to bring this technology into the market place. This paper focuses on the problem of driving in snow and wet road surface environments. First, the quality of laser imaging detection and ranging (LIDAR) reflectivity decreases on wet road surfaces. Therefore, an accumulation strategy is designed to increase the density of online LIDAR images. In order to enhance the texture of the accumulated images, principal component analysis is used to understand the geometrical structures and texture patterns in the map images. The LIDAR images are then reconstructed using the leading principal components with respect to the variance distribution accounted by each eigenvector. Second, the appearance of snow lines deforms the expected road context in LIDAR images. Accordingly, the edge profiles of the LIDAR and map images are extracted to encode the lane lines and roadside edges. Edge matching between the two profiles is then calculated to improve localization in the lateral direction. The proposed method has been tested and evaluated using real data that are collected during the winter of 2016-2017 in Suzu and Kanazawa, Japan. The experimental results show that the proposed method increases the robustness of autonomous driving on wet road surfaces, provides a stable performance in laterally localizing the vehicle in the presence of snow lines, and significantly reduces the overall localization error at a speed of 60 km/h. © 2005-2012 IEEE

High-performance inverted planar heterojunction perovskite solar cells based on lead acetate precursor with efficiency exceeding 18%

Organic-inorganic lead halide perovskites are emerging materials for the next-generation photovoltaics. Lead halides are the most commonly used lead precursors for perovskite active layers. Recently, lead acetate (Pb(Ac)2) has shown its superiority as the potential replacement for traditional lead halides. Here, we demonstrate a strategy to improve the efficiency for the perovskite solar cell based on lead acetate precursor. We utilized methylammonium bromide as an additive in the Pb(Ac)2 and methylammonium iodide precursor solution, resulting in uniform, compact and pinhole-free perovskite films. We observed enhanced charge carrier extraction between the perovskite layer and charge collection layers and delivered a champion power conversion efficiency of 18.3% with a stabilized output efficiency of 17.6% at the maximum power point. The optimized devices also exhibited negligible current density-voltage (J-V) hysteresis under the scanning conditions

Light and oxygen induced degradation limits the operational stability of methylammonium lead triiodide perovskite solar cells

Here, we demonstrate that light and oxygen-induced degradation is the main reason for the low operational stability of methylammonium lead triiodide (MeNH3PbI3) perovskite solar cells exposed to ambient conditions. When exposed to both light and dry air, unencapsulated MeNH3PbI3 solar cells rapidly degrade on timescales of minutes to a few hours. This rapid degradation is also observed under electrically bias driven current flow in the dark in the presence of O2. In contrast, significantly slower degradation is observed when the MeNH3PbI3 devices are exposed to moisture alone (e.g. 85% relative humidity in N2). We show that this light and oxygen induced degradation can be slowed down by the use of interlayers that are able to remove electrons from the perovskite film before they can react with oxygen to form O2−. These observations demonstrate that the operational stability of electronic and optoelectronic devices that exploit the electron transporting properties of MeNH3PbI3 will be critically dependent upon the use of suitable barrier layers and device configurations to mitigate the oxygen sensitivity of this remarkable material

Critical analysis of stability and performance of organometal halide perovskite solar cells via various fabrication method ( Review

Organometal halide perovskite solar cells (Omh-PSCs) have attracted attention due to its unique electrical and optical properties. Ideally, the Omh-PSCs should remain free from degradation under normal operating conditions for several years, preferably tens of years. In order to produce high power conversion efficiency with low potential of degradation, different fabrication methods have been developed. The reported stability of perovskite films can vary significantly and reported to decay substantially up to 20% of its original performance. A thorough understanding of fabrication process upon the stability of the device is regarded as crucial to pave the way for future endeavors. This review summarized and highlighted the recent research of fabrication methods that gave an impact to the stability of perovskite devices

تطوير منهجية تحليلية وتصميمية لقواعد البيانات متعددة الأبعاد الخاصة بمستودعات البيانات

لقد ازداد تعقيد الأعمال في المؤسسات، كما ازدادت كمية البيانات التي تتعامل معها هذه المؤسسات، ولم تعد أنظمة قواعد المعطيات العادية قادرةً على تلبية متطلبات متخذ القرار من حيث السرعة والدقة وحجم البيانات الذي تستطيع التعامل معه، لذلك ظهرت فكرة مستودعات البيانات، والتي تعد من أقوى أدوات نظم دعم القرارDecision Support Systems (DSS)، وبرزت الحاجة الملحة إليها في الشركات الكبرى، حيث أن كل قسم من هذه الشركات يدير قواعد بيانات مستقلة خاصة به (تسويق، مالي...)، والتي تتضمن كثيراً من البيانات المشتركة، وتتطلب حاجة الشركات حالياً إيجاد كامل البيانات المتعلقة بموضوع محدد، كالزبائن مثلاً، من خلال البحث في قاعدة واحدة، بدلاً من البحث في القواعد المختلفة. نبحث في هذه الورقة تطوير منهجية تحليلية وتصميمية لبناء مستودعات البيانات، حيث نحدد المراحل والأسئلة الأساسية الواجب طرحها في كل مرحلة للوصول إلى مستودع بيانات يلبي حاجة المؤسسة، ويسمح بالإجابة على الاستعلامات المطلوبة. بينت النتائج أن اتباع المنهجية المطروحة في البحث قد أدى إلى اختصار الزمن اللازم لبناء مستودع البيانات وتقليل زمن وحجم التعديلات المطعلالوبة للوصول إلى النتيجة النهائية.

تقليل تلوث كاش الويب في خوارزمية الكاش GDFS باستخدام مسافة غوغل المقيّسة NGD للتشابه الدلالي

إنّ الكاش هو أحد التقنيات التي تساهم بشكل فعال في تحسين كفاءة أنظمة استعادة المعلومات Information Retrieval Systemsـ، ويعتبر كاش الويب، وهو تقنية الكاش الخاصة بشبكة الويب، أحد الأدوات لتحسين زمن استجابة أنظمة المعلومات القائمة على الويبWeb-Based Information Systems (WIS) ، ويتم ذلك من خلال خوارزميات تختلف فيما بينها في عمل تابع استبدال الخوارزمية. نبحث في هذه الورقة تقليل تلوث الكاش الساخن Hot Pollution والتلوث البارد Cold Pollution والذي قد يصيب عمل خوارزمية (Greedy Dual Frequency Size) GDFS والتي تعتبر خوارزمية أساسية ومرجعية في مجال كاش الويب، وذلك من خلال تحسين تابع الاستبدال بإدخال مفهوم التشابه الدلالي بين الأغراض المخزنة في الكاش، باستخدام مسافة غوغل المقيّسة  Normalized Google Distance (NGD) إلى عمل تابع الاستبدال لهذه الخوارزمية. بينت النتائج أن إدخال مفهوم التشابه الدلالي إلى عمل هذه الخوارزمية أدى إلى تقليل تلوث الكاش، من خلال التحكم الأفضل ببقاء الأغراض في الكاش، والمساهمة مع وظيفة تابع الاستبدال الأساسية في تقييم مدة بقاء الأغراض في الكاش، وبالتالي تحسين نسبة الإصابة Hit Rate للأغراض من ذاكرة الكاش بدلاً من مصدر البيانات الأساس

Graph SLAM-Based 2.5D LIDAR Mapping Module for Autonomous Vehicles

This paper proposes a unique Graph SLAM framework to generate precise 2.5D LIDAR maps in an XYZ plane. A node strategy was invented to divide the road into a set of nodes. The LIDAR point clouds are smoothly accumulated in intensity and elevation images in each node. The optimization process is decomposed into applying Graph SLAM on nodes’ intensity images for eliminating the ghosting effects of the road surface in the XY plane. This step ensures true loop-closure events between nodes and precise common area estimations in the real world. Accordingly, another Graph SLAM framework was designed to bring the nodes’ elevation images into the same Z-level by making the altitudinal errors in the common areas as small as possible. A robust cost function is detailed to properly constitute the relationships between nodes and generate the map in the Absolute Coordinate System. The framework is tested against an accurate GNSS/INS-RTK system in a very challenging environment of high buildings, dense trees and longitudinal railway bridges. The experimental results verified the robustness, reliability and efficiency of the proposed framework to generate accurate 2.5D maps with eliminating the relative and global position errors in XY and Z planes. Therefore, the generated maps significantly contribute to increasing the safety of autonomous driving regardless of the road structures and environmental factors

Eye Shape Detection Methods Based on Eye Structure Modeling and Texture Analysis for Interface Systems

豊橋技術科学大

Graph SLAM-Based 2.5D LIDAR Mapping Module for Autonomous Vehicles

This paper proposes a unique Graph SLAM framework to generate precise 2.5D LIDAR maps in an XYZ plane. A node strategy was invented to divide the road into a set of nodes. The LIDAR point clouds are smoothly accumulated in intensity and elevation images in each node. The optimization process is decomposed into applying Graph SLAM on nodes’ intensity images for eliminating the ghosting effects of the road surface in the XY plane. This step ensures true loop-closure events between nodes and precise common area estimations in the real world. Accordingly, another Graph SLAM framework was designed to bring the nodes’ elevation images into the same Z-level by making the altitudinal errors in the common areas as small as possible. A robust cost function is detailed to properly constitute the relationships between nodes and generate the map in the Absolute Coordinate System. The framework is tested against an accurate GNSS/INS-RTK system in a very challenging environment of high buildings, dense trees and longitudinal railway bridges. The experimental results verified the robustness, reliability and efficiency of the proposed framework to generate accurate 2.5D maps with eliminating the relative and global position errors in XY and Z planes. Therefore, the generated maps significantly contribute to increasing the safety of autonomous driving regardless of the road structures and environmental factors