scholarly journals Weather Classification Using an Automotive LIDAR Sensor Based on Detections on Asphalt and Atmosphere

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4306
Author(s):  
Jose Roberto Vargas Rivero ◽  
Thiemo Gerbich ◽  
Valentina Teiluf ◽  
Boris Buschardt ◽  
Jia Chen
Keyword(s):  
Background Radiation ◽  
Weather Conditions ◽  
Autonomous Driving ◽  
Field Of View ◽  
Weather Types ◽  
Surface Reflection ◽  
Background Radiations ◽  
Weather Information ◽  
System A ◽  
Parking Lot

A semi-/autonomous driving car requires local weather information to identify if it is working inside its operational design domain and adapt itself accordingly. This information can be extracted from changes in the detections of a light detection and ranging (LIDAR) sensor. These changes are caused by modifications in the volumetric scattering of the atmosphere or surface reflection of objects in the field of view of the LIDAR. In order to evaluate the use of an automotive LIDAR as a weather sensor, a LIDAR is placed outdoor in a fixed position for a period of 9 months covering all seasons. As target, an asphalt region from a parking lot is chosen. The collected sensor raw data is labeled depending on the occurring weather conditions as: clear, rain, fog and snow, and the presence of sunlight: with or without background radiation. The influence of different weather types and background radiations on the measurement results is analyzed and different parameters are chosen in order to maximize the classification accuracy. The classification is done per frame in order to provide fast update rates while still keeping an F1 score higher than 80%. Additionally, the field of view is divided into two regions: atmosphere and street, where the influences of different weather types are most notable. The resulting classifiers can be used separately or together increasing the versatility of the system. A possible way of extending the method for a moving platform and alternatives to virtually simulate the scene are also discussed.

scholarly journals Limited Visibility Aware Motion Planning for Autonomous Valet Parking Using Reachable Set Estimation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1520
Author(s):  
Seongjin Lee ◽  
Wonteak Lim ◽  
Myoungho Sunwoo ◽  
Kichun Jo
Keyword(s):  
Coming Out ◽  
Planning Process ◽  
Autonomous Driving ◽  
Field Of View ◽  
Automated System ◽  
Automation System ◽  
Worst Case ◽  
Parking Lot ◽  
Reachable Set Estimation ◽  
Limited Visibility

Autonomous driving helps drivers avoid paying attention to keeping to a lane or keeping a distance from the vehicle ahead. However, the autonomous driving is limited by the need to park upon the completion of driving. In this sense, automated valet parking (AVP) system is one of the promising technologies for enabling drivers to free themselves from the burden of parking. Nevertheless, the driver must continuously monitor the automated system in the current automation level. The main reason for monitoring the automation system is due to the limited sensor range and occlusions. For safety reasons, the current field of view must be taken into account, as well as to ensure comfort and to avoid unexpected and harsh reactions. Unfortunately, due to parked vehicles and structures, the field of view in a parking lot is not sufficient for considering new obstacles coming out of occluded areas. To solve this problem, we propose a method that estimates the risks for unobservable obstacles by considering worst-case assumptions. With this method, we can ensure to not act overcautiously while moving safe. As a result, the proposed method can be a proactive approach to consider the limited visibility encountered in a parking lot. In the proposed method, occlusion can be efficiently reflected in the planning process. The potential of the proposed method is evaluated in a variety of simulations.

scholarly journals Reshaping Field of View and Resolution with Segmented Reflectors: Bridging the Gap between Rotating and Solid-State LiDARs

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3388
Author(s):  
Atle Aalerud ◽  
Joacim Dybedal ◽  
Dipendra Subedi
Keyword(s):  
Super Resolution ◽  
Weather Conditions ◽  
Autonomous Driving ◽  
Field Of View ◽  
Optical Simulation ◽  
Sample Standard Deviation ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Simulation Results ◽  
Pattern Simulation

This paper describes the first simulations and experimental results of a novel segmented Light Detection And Ranging (LiDAR) reflector. Large portions of the rotating LiDAR data are typically discarded due to occlusion or a misplaced field of view (FOV). The proposed reflector solves this problem by reflecting the entire FOV of the rotating LiDAR towards a target. Optical simulation results, using Zemax OpticStudio, suggest that adding a reflector reduces the range of the embedded LiDAR with only 3.9 %. Furthermore, pattern simulation results show that a radially reshaped FOV can be configured to maximize point cloud density, maximize coverage, or a combination. Here, the maximum density is defined by the number of mirror segments in the reflector. Finally, a prototype was used for validation. Intensity, Euclidean error, and sample standard deviation were evaluated and, except for reduced-intensity values, no significant reduction in the LiDAR’s performance was found. Conversely, the number of usable measurements increased drastically. The mirrors of the reflector give the LiDAR multiple viewpoints to the target. Ultimately, it is argued that this can enhance the object revisit rate, instantaneous resolution, object classification range, and robustness against occlusion and adverse weather conditions. Consequently, the reflector design enables long-range rotating LiDARs to achieve the robust super-resolution needed for autonomous driving at highway speeds.

scholarly journals Performance of an Advanced Intelligent Control Strategy in a Dynamic Positioning (DP) System Applied to a Semisubmersible Drilling Platform

2021 ◽  
Vol 9 (4) ◽  
pp. 399
Author(s):  
Mohamad Alremeihi ◽  
Rosemary Norman ◽  
Kayvan Pazouki ◽  
Arun Dev ◽  
Musa Bashir
Keyword(s):  
Oil And Gas ◽  
Weather Conditions ◽  
Dynamic Positioning ◽  
System Failures ◽  
Oil Drilling ◽  
System A ◽  
Advanced Control ◽  
Safety And Reliability ◽  
Drilling Operations ◽  
Shallow Seas

Oil drilling and extraction platforms are currently being used in many offshore areas around the world. Whilst those operating in shallow seas are secured to the seabed, for deeper water operations, Dynamic Positioning (DP) is essential for the platforms to maintain their position within a safe zone. Operating DP requires intelligent and reliable control systems. Nearly all DP accidents have been caused by a combination of technical and human failures; however, according to the International Marine Contractors Association (IMCA) DP Incidents Analysis, DP control and thruster system failures have been the leading causes of incidents over the last ten years. This paper will investigate potential operational improvements for DP system accuracy by adding a Predictive Neural Network (PNN) control algorithm in the thruster allocation along with a nonlinear Proportional Integral derivative (PID) motion control system. A DP system’s performance on a drilling platform in oil and gas deep-water fields and subject to real weather conditions is simulated with these advanced control methods. The techniques are developed for enhancing the safety and reliability of DP operations to improve the positioning accuracy, which may allow faster response to a critical situation during DP drilling operations. The semisubmersible drilling platform’s simulation results using the PNN strategy show improved control of the platform’s positioning.

scholarly journals Practical limitations of lane detection algorithm based on Hough transform in challenging scenarios

2021 ◽  
Vol 18 (2) ◽  
pp. 172988142110087
Author(s):  
Qiao Huang ◽  
Jinlong Liu
Keyword(s):  
Hough Transform ◽  
Detection Rate ◽  
Real Life ◽  
Weather Conditions ◽  
Autonomous Driving ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Search Range ◽  
Range Restriction ◽  
Lighting Conditions

The vision-based road lane detection technique plays a key role in driver assistance system. While existing lane recognition algorithms demonstrated over 90% detection rate, the validation test was usually conducted on limited scenarios. Significant gaps still exist when applied in real-life autonomous driving. The goal of this article was to identify these gaps and to suggest research directions that can bridge them. The straight lane detection algorithm based on linear Hough transform (HT) was used in this study as an example to evaluate the possible perception issues under challenging scenarios, including various road types, different weather conditions and shades, changed lighting conditions, and so on. The study found that the HT-based algorithm presented an acceptable detection rate in simple backgrounds, such as driving on a highway or conditions showing distinguishable contrast between lane boundaries and their surroundings. However, it failed to recognize road dividing lines under varied lighting conditions. The failure was attributed to the binarization process failing to extract lane features before detections. In addition, the existing HT-based algorithm would be interfered by lane-like interferences, such as guardrails, railways, bikeways, utility poles, pedestrian sidewalks, buildings and so on. Overall, all these findings support the need for further improvements of current road lane detection algorithms to be robust against interference and illumination variations. Moreover, the widely used algorithm has the potential to raise the lane boundary detection rate if an appropriate search range restriction and illumination classification process is added.

Design of Mechaless LiDAR Optical System With Large FOV Using Liquid Lens and Fisheye Lens

2018 ◽  
Author(s):  
Hyun Choi ◽  
Wan-Chin Kim
Keyword(s):  
Low Cost ◽  
Autonomous Driving ◽  
Voltage Regulation ◽  
Field Of View ◽  
Fisheye Lens ◽  
Liquid Lens ◽  
Fine Spatial Resolution ◽  
Flash Lidar ◽  
Optical Phased Array ◽  
Measurable Distance

Mechaless LiDAR technology, which does not have a mechanical drive part, has been actively studied in order to increase the reliability of the LiDAR device at low cost and drive environment in order to more actively apply LiDAR technology to autonomous driving. Mechaless LiDAR technology, which has been mainly studied recently, includes 3D Flash LiDAR technology, MEMS mirror utilization method, and OPA (Optical Phased Array). However, these methods have not been developed rapidly as a key technology for achieving autonomous driving due to low stability of driving environment or remarkably low measurable distance and FOV (field of view) compared with mechanical LiDAR. In this study, we investigated the improvement of FOV by using a flux-deflecting liquid lens and a fisheye lens that can achieve fine spatial resolution through continuous voltage regulation. Based on the initial design results, it was examined that the FOV can be secured to 80 ° or more by utilizing a relatively simple fisheye lens composed of only spherical lenses.

scholarly journals Evaluation of possibilities for the climatic distribution of regions from the point of view of road construction

2015 ◽  
Vol 10 (3) ◽  
pp. 262-268 ◽  
Author(s):  
Lina Juknevičiūtė-Žilinskienė ◽  
Alfredas Laurinavičius
Keyword(s):  
Information System ◽  
Information Systems ◽  
Road Traffic ◽  
Road Construction ◽  
Weather Conditions ◽  
Frozen Ground ◽  
Weather Information ◽  
Road Pavement ◽  
The World ◽  
Pavement Structure

Seeking to reduce a negative impact of unfavourable weather conditions on road traffic, many countries introduce modern technologies allowing to objectively assessing meteorological conditions of roads. The world over, data from the automated meteorological stations of Road Weather Information System have been long ago used on a significantly larger scale than only for the organization of road maintenance works. International experience of introducing Road Traffic Information Systems in European Union and other countries of the world shows that Road Weather Information Systems give good results for increasing road safety, improving the level of road user information and solving the road construction issues. Road Weather Information System is a system of technologies and decision-making using historical and real-time data of roads and weather conditions. The collected and processed multi-year data from meteorological stations is a great assistance in designing or reconstructing road pavement structures. Road pavement structure is highly affected by a negative air temperature and frozen ground. The impact of negative temperature is expressed by the thickness of frost blanket course. The thickness of frost blanket course depends on a frost susceptibility of soil. To determine the thickness of frost blanket course it is necessary to assess the frost impact, therefore it was up to the purpose − climatic distribution of regions the territory of Lithuania according to the distribution of frost impact and the depth of frozen ground. Based on climatic maps compiled, a correction of the thickness of road pavement structure was suggested.

scholarly journals Influence of Surface Reflection (Albedo) in Simulating the Sun Drying of Paddy Rice

2020 ◽  
Vol 10 (15) ◽  
pp. 5092
Author(s):  
Ana Salvatierra-Rojas ◽  
Victor Torres-Toledo ◽  
Joachim Müller
Keyword(s):  
Field Experiments ◽  
Positive Impact ◽  
Weather Conditions ◽  
The Philippines ◽  
Paddy Rice ◽  
The Sun ◽  
Transient Model ◽  
Surface Reflection ◽  
Sun Drying ◽  
Drying Model

The sun drying of agricultural products is a complicated process involving heat transfer, mass transfer, and variable weather conditions. Surface reflection (albedo), a crop’s radiative property, plays an essential role in energy balance, and understanding its contribution can improve the thermal analysis. In this study, field experiments were conducted in the Philippines to explore the influence of surface albedo on the sun drying of paddy rice. First, we implemented energy and mass balance equations in a transient model with the surroundings using a graphical programming language in Matlab/Simulink®. Second, we identified the influence of albedo on the sun drying model by using a sensitivity analysis. Third, we investigated the relationship of paddy rice albedo and the solar zenith angle. Lastly, we integrated the albedo function into the sun drying model. The simulation outputs were validated with field experiments. A better estimation of the measured exit temperature and instantaneous mass were obtained when a variable albedo was applied. This study makes clear that introducing a variable albedo has a positive impact on model improvement. This information is important for application in solar drying technologies, so that the drying process can be better assessed.

scholarly journals Experiments on a Snow-Patch in the Mountains of Sweden

1966 ◽  
Vol 6 (43) ◽  
pp. 135-144 ◽  
Author(s):  
I. Y. Ashwell ◽  
F. G. Hannell
Keyword(s):  
Weather Conditions ◽  
Snow Surface ◽  
Weather Types ◽  
Surface Features ◽  
Cone Formation

AbstractInvestigations into the mechanism of dirt-cone formation, and snow patterning, are described. In each case the changes in patches of various materials arranged on a snow surface, were observed over a period of three weeks in the summer, under varying weather conditions. The effects of fine rock flour on the formation of dirt cones are analysed. Two main weather types are recognized as having different, but important, effects on the surface features of the snow; föhn-type winds, and calm, sunny conditions.

scholarly journals Short-Term Associations of Fine Particulate Matter and Synoptic Weather Types with Cardiovascular Mortality: An Ecological Time-Series Study in Shanghai, China

2020 ◽  
Vol 17 (3) ◽  
pp. 1111 ◽  
Author(s):  
Qing Tian ◽  
Mei Li ◽  
Scott Montgomery ◽  
Bo Fang ◽  
Chunfang Wang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Cardiovascular Mortality ◽  
Fine Particulate Matter ◽  
Weather Conditions ◽  
Cold Weather ◽  
Short Term ◽  
Weather Types ◽  
Synoptic Weather ◽  
Fine Particulate ◽  
Pm2.5 Concentration

Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.

scholarly journals A Geostatistical Investigation into the Effective Spatiotemporal Coverage of Road Weather Information Systems in Alberta, Canada

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Xu Wang ◽  
Lian Gu ◽  
Tae J. Kwon ◽  
Tony Z. Qiu
Keyword(s):  
Information Systems ◽  
Weather Conditions ◽  
Road Maintenance ◽  
The Road ◽  
Weather Information ◽  
Geostatistical Approach ◽  
Adverse Weather ◽  
Winter Road ◽  
Winter Road Maintenance

Inclement weather acutely affects road surface and driving conditions and can negatively impact traffic mobility and safety. Highway authorities have long been using road weather information systems (RWISs) to mitigate the risk of adverse weather on traffic. The data gathered, processed, and disseminated by such systems can improve both the safety of the traveling public as well as the effectiveness of winter road maintenance operations. As the road authorities continue to invest in expanding their existing RWIS networks, there is a growing need to determine the optimal deployment strategies for RWISs. To meet such demand, this study presents an innovative geostatistical approach to quantitatively analyze the spatiotemporal variations of the road weather and surface conditions. With help of constructed semivariograms, this study quantifies and examines both the spatial and temporal coverage of RWIS data. A case study of Alberta, which is one of the leaders in Canada in the use of RWISs, was conducted to indicate the reliability and applicability of the method proposed herein. The findings of this research offer insight for constructing a detailed spatiotemporal RWIS database to manage and deploy different types of RWISs, optimize winter road maintenance resources, and provide timely information on inclement road weather conditions for the traveling public.

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