scholarly journals Autonomous driving in adverse winter weather conditions

2021 ◽  
Author(s):  
Marjo Hippi ◽  
Timo Sukuvaara ◽  
Kari Mäenpää ◽  
Toni Perälä ◽  
Daria Stepanova
Keyword(s):  
Weather Conditions ◽  
Autonomous Driving ◽  
The Arctic ◽  
Observation System ◽  
Test Track ◽  
Finnish Meteorological Institute ◽  
Driving Mode ◽  
Autonomous Cars ◽  
Road Condition ◽  
Meteorological Institute

<p>Autonomous driving can be challenging especially in winter conditions when road surface is covered by icy and snow or visibility is low due to precipitation, fog or blowing snow. These harsh weather and road conditions set up very important requirements for the guidance systems of autonomous cars. In the normal conditions autonomous cars can drive without limitations but otherwise the speed must be reduced, and the safety distances increased to ensure safety on the roads. </p><p>Autonomous driving needs very precise and real-time weather and road condition information. Data can be collected from different sources, like (road) weather models, fixed road weather station network, weather radars and vehicle sensors (for example Lidars, radars and dashboard cameras). By combining the all relevant weather and road condition information a weather-based autonomous driving mode system is developed to help and guide autonomous driving. The driving mode system is dividing the driving conditions from perfect conditions to very poor conditions. In between there are several steps with slightly alternate driving modes depending for example snow intensity and friction. In the most challenging weather conditions, automatic driving must be stopped because the sensors guiding the driving are disturbed by for example heavy snowfall or icy road.</p><p>Finnish Meteorological Institute is testing autonomous driving in the Arctic vehicular test track in Sodankylä, Northern Finland. The test track is equipped with road weather observation system network including road weather stations, IoT sensors measuring air temperature and humidity along with various communication systems. Also, tailored road weather services are produced to the test track, like precise road weather model calculations and very accurate radar precipitation observations and nowcasting. The developed weather-based autonomous driving system is tested on Sodankylä test track among other arctic autonomous driving testing.</p><p>This study presents the Sodankylä Arctic vehicular test track environment and weather-based autonomous driving mode system that is developed at the Finnish Meteorological Institute.</p>

scholarly journals SodSAR: A Tower-Based 1–10 GHz SAR System for Snow, Soil and Vegetation Studies

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6702
Author(s):  
Jorge Jorge Ruiz ◽  
Risto Vehmas ◽  
Juha Lemmetyinen ◽  
Josu Uusitalo ◽  
Janne Lahtinen ◽  
...  
Keyword(s):  
Synthetic Aperture ◽  
The Arctic ◽  
Target Range ◽  
Network Analyzer ◽  
Sar Images ◽  
Finnish Meteorological Institute ◽  
Radar Calibration ◽  
Loss Of Coherence ◽  
Better Than ◽  
Meteorological Institute

We introduce SodSAR, a fully polarimetric tower-based wide frequency (1–10 GHz) range Synthetic Aperture Radar (SAR) aimed at snow, soil and vegetation studies. The instrument is located in the Arctic Space Centre of the Finnish Meteorological Institute in Sodankylä, Finland. The system is based on a Vector Network Analyzer (VNA)-operated scatterometer mounted on a rail allowing the formation of SAR images, including interferometric pairs separated by a temporal baseline. We present the description of the radar, the applied SAR focusing technique, the radar calibration and measurement stability analysis. Measured stability of the backscattering intensity over a three-month period was observed to be better than 0.5 dB, when measuring a target with a known radar cross section. Deviations of the estimated target range were in the order of a few cm over the same period, indicating also good stability of the measured phase. Interforometric SAR (InSAR) capabilities are also discussed, and as a example, the coherence of subsequent SAR acquisitions over the observed boreal forest stand are analyzed over increasing temporal baselines. The analysis shows good conservation of coherence in particular at L-band, while higher frequencies are susceptible to loss of coherence in particular for dense vegetation. The potential of the instrument for satellite calibration and validation activities is also discussed.

scholarly journals Nordic Snow Radar Experiment

2016 ◽  
Vol 5 (2) ◽  
pp. 403-415 ◽  
Author(s):  
Juha Lemmetyinen ◽  
Anna Kontu ◽  
Jouni Pulliainen ◽  
Juho Vehviläinen ◽  
Kimmo Rautiainen ◽  
...  
Keyword(s):  
European Space Agency ◽  
Winter Season ◽  
Test Site ◽  
Microwave Emission ◽  
The Arctic ◽  
Research Centre ◽  
Easy Access ◽  
Finnish Meteorological Institute ◽  
Meteorological Institute

Abstract. The objective of the Nordic Snow Radar Experiment (NoSREx) campaign was to provide a continuous time series of active and passive microwave observations of snow cover at a representative location of the Arctic boreal forest area, covering a whole winter season. The activity was a part of Phase A studies for the ESA Earth Explorer 7 candidate mission CoReH2O (Cold Regions Hydrology High-resolution Observatory). The NoSREx campaign, conducted at the Finnish Meteorological Institute Arctic Research Centre (FMI-ARC) in Sodankylä, Finland, hosted a frequency scanning scatterometer operating at frequencies from X- to Ku-band. The radar observations were complemented by a microwave dual-polarization radiometer system operating from X- to W-bands. In situ measurements consisted of manual snow pit measurements at the main test site as well as extensive automated measurements on snow, ground and meteorological parameters. This study provides a summary of the obtained data, detailing measurement protocols for each microwave instrument and in situ reference data. A first analysis of the microwave signatures against snow parameters is given, also comparing observed radar backscattering and microwave emission to predictions of an active/passive forward model. All data, including the raw data observations, are available for research purposes through the European Space Agency and the Finnish Meteorological Institute. A consolidated dataset of observations, comprising the key microwave and in situ observations, is provided through the ESA campaign data portal to enable easy access to the data.

Sampling, filtering and analyzing procedures for thermal-optical OCEC analysis to determine black carbon, organic carbon and total carbon concentrations in Arctic snow, ice and water samples

2020 ◽  
Author(s):  
Outi Meinander ◽  
Enna Heikkinen ◽  
Minna Aurela
Keyword(s):  
Organic Carbon ◽  
Black Carbon ◽  
Water Samples ◽  
Total Carbon ◽  
Light Transmittance ◽  
The Arctic ◽  
Arctic Circle ◽  
Finnish Meteorological Institute ◽  
Center Of Excellence ◽  
Meteorological Institute

<p>Seemingly small amounts of black carbon (BC) in snow, of the order of 10–100 parts per billion by mass (ppb), have been shown to decrease its albedo by 1–5 %. Due to the albedo-feedback mechanism, surface darkening accelerates snow and ice melt and contributes to Arctic warming.</p><p>Here we present the most recent procedures we use for sampling, filtering and analysis of Arctic snow, ice and water samples, to determine their black carbon (BC), organic carbon (OC) and total carbon (TC) contents. For the purpose, we apply the OCEC analyzer of the Finnish Meteorological Institute’s aerosol laboratory, Helsinki, Finland (60°12 N). Particles are collected on a quarz-fiber filter and subjected to different temperature ramps following the protocols (NIOSH-870, EUSAAR2, or IMPROVE). Pyrolysis correction is by laser transmittance. Light transmittance through the filter is monitored during the collection phase to quantify BC. The OCEC thermal-optical method is the current European standard method for determination of atmospheric BC.  </p><p>Our Arctic samples include surface snow and snow profile samples collected north of the Arctic Circle at the Finnish Meteorological Institute Arctic Space Center in Sodankylä, Finland (67◦37 N, 26◦63 E), which is also a World Meteorological Institute’s Global Atmospheric Watch station (WMO GAW). In addition, samples from H2020 EU-Interact stations of Faroes FINI, Iceland Sudurnes and UK Cairngorms, and elsewhere from Iceland and Finland, including Helsinki Kumpula SMEAR-III station (60°12 N, 24°57 E, Station for Measuring Ecosystem-Atmosphere Relations, https://www.atm.helsinki.fi/SMEAR/index.php/smear-iii) and the most northern research catchment area of Pallas (68°N, about 130 km north from the Arctic Circle, https://blogs.egu.eu/divisions/hs/2019/06/19/featured-catchment-series-pallas/), have been sampled and analyzed. The BC concentrations have been detected to vary according to the origin of the air masses and as a result of the seasonal snow melt process.</p><p><em>Acknowledgements. We gratefully acknowledge support from the EU-Interact-BLACK-project Black Carbon in snow and water (H2020 Grant Agreement No. 730938); the Academy of Finland NABCEA-project of Novel Assessment of Black Carbon in the Eurasian Arctic (No. 296302), Ministry for Foreign Affairs of Finland IBA-project Black Carbon in the Arctic and significance compared to dust sources (No. PC0TQ4BT-25); the Academy of Finland Center of Excellence program The Centre of Excellence in Atmospheric Science - From Molecular and Biological processes to The Global Climate (No. 272041), and The Nordic Center of Excellence CRAICC Cryosphere–Atmosphere Interactions in a Changing Arctic Climate.</em></p><p> </p><p> </p>

Autonomy and Responsibility in Hybrid Systems

2017 ◽  
Author(s):  
Wulf Loh ◽  
Janina Loh
Keyword(s):  
Hybrid Systems ◽  
Hybrid System ◽  
Moral Dilemma ◽  
Autonomous Driving ◽  
Shared Responsibility ◽  
Driving System ◽  
Autonomous Cars ◽  
Self Driving Cars ◽  
Trolley Cases ◽  
Autonomous Driving System

In this chapter, we give a brief overview of the traditional notion of responsibility and introduce a concept of distributed responsibility within a responsibility network of engineers, driver, and autonomous driving system. In order to evaluate this concept, we explore the notion of man–machine hybrid systems with regard to self-driving cars and conclude that the unit comprising the car and the operator/driver consists of such a hybrid system that can assume a shared responsibility different from the responsibility of other actors in the responsibility network. Discussing certain moral dilemma situations that are structured much like trolley cases, we deduce that as long as there is something like a driver in autonomous cars as part of the hybrid system, she will have to bear the responsibility for making the morally relevant decisions that are not covered by traffic rules.

scholarly journals Modules and Techniques for Motion Planning: An Industrial Perspective

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 420
Author(s):  
Stefano Quer ◽  
Luz Garcia
Keyword(s):  
Data Fusion ◽  
Autonomous Driving ◽  
Random Trees ◽  
Approximation Techniques ◽  
Main Research ◽  
Autonomous Cars ◽  
Critical Issues ◽  
Relative Errors ◽  
Path Planner ◽  
Many Core

Research on autonomous cars has become one of the main research paths in the automotive industry, with many critical issues that remain to be explored while considering the overall methodology and its practical applicability. In this paper, we present an industrial experience in which we build a complete autonomous driving system, from the sensor units to the car control equipment, and we describe its adoption and testing phase on the field. We report how we organize data fusion and map manipulation to represent the required reality. We focus on the communication and synchronization issues between the data-fusion device and the path-planner, between the CPU and the GPU units, and among different CUDA kernels implementing the core local planner module. In these frameworks, we propose simple representation strategies and approximation techniques which guarantee almost no penalty in terms of accuracy and large savings in terms of memory occupation and memory transfer times. We show how we adopt a recent implementation on parallel many-core devices, such as CUDA-based GPGPU, to reduce the computational burden of rapidly exploring random trees to explore the state space along with a given reference path. We report on our use of the controller and the vehicle simulator. We run experiments on several real scenarios, and we report the paths generated with the different settings, with their relative errors and computation times. We prove that our approach can generate reasonable paths on a multitude of standard maneuvers in real time.

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.

scholarly journals An exemplary case of a bromine explosion event linked to cyclone development in the Arctic

2016 ◽  
Vol 16 (3) ◽  
pp. 1773-1788 ◽  
Author(s):  
A.-M. Blechschmidt ◽  
A. Richter ◽  
J. P. Burrows ◽  
L. Kaleschke ◽  
K. Strong ◽  
...  
Keyword(s):  
Numerical Models ◽  
Weather Conditions ◽  
Conveyor Belt ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Blowing Snow ◽  
Air Stream ◽  
Combined Use ◽  
Arctic Sea ◽  
Development Duration

Abstract. Intense, cyclone-like shaped plumes of tropospheric bromine monoxide (BrO) are regularly observed by GOME-2 on board the MetOp-A satellite over Arctic sea ice in polar spring. These plumes are often transported by high-latitude cyclones, sometimes over several days despite the short atmospheric lifetime of BrO. However, only few studies have focused on the role of polar weather systems in the development, duration and transport of tropospheric BrO plumes during bromine explosion events. The latter are caused by an autocatalytic chemical chain reaction associated with tropospheric ozone depletion and initiated by the release of bromine from cold brine-covered ice or snow to the atmosphere. In this manuscript, a case study investigating a comma-shaped BrO plume which developed over the Beaufort Sea and was observed by GOME-2 for several days is presented. By making combined use of satellite data and numerical models, it is shown that the occurrence of the plume was closely linked to frontal lifting in a polar cyclone and that it most likely resided in the lowest 3 km of the troposphere. In contrast to previous case studies, we demonstrate that the dry conveyor belt, a potentially bromine-rich stratospheric air stream which can complicate interpretation of satellite retrieved tropospheric BrO, is spatially separated from the observed BrO plume. It is concluded that weather conditions associated with the polar cyclone favoured the bromine activation cycle and blowing snow production, which may have acted as a bromine source during the bromine explosion event.

RISK ASSESSMENT OF ARCTIC NAVIGATION BY USING IMPROVED FUZZY-AHP APPROACH

2021 ◽  
Vol 157 (A4) ◽  
Author(s):  
B Sahin ◽  
S Kum
Keyword(s):  
Fuzzy Ahp ◽  
Weather Conditions ◽  
Risk Identification ◽  
The Arctic ◽  
Risk Levels ◽  
Global Logistics ◽  
Geographical Position ◽  
Arctic Navigation ◽  
Hull Damage ◽  
Hierarchy Process

In this study, navigational risk factors of the Arctic Ocean are defined and numerical weights of each risk are obtained by using Improved Fuzzy Analytical Hierarchy Process (IF-AHP) method after conducting expert consultations. The Northern Sea Route shortens the maritime distance approximately 7000 nautical miles comparing to the conventional Suez Canal route. Therefore, it takes a significant role of being economic and time advantage for global logistics. Its geographical position, presence of ice, heavy weather conditions, strong currents and winds are some risks for Arctic transportation. There always have the possibility of unpredictable catastrophes such as a collision, grounding, hull damage and etc. in this region. Reflections of such unwanted incidents might be very costly for economic, political, environmental and safety concerns. Due to there are limited academic studies regarding to analytical and systematical risk identification and determination of risk levels, this study contributes to complete this academic gap.

scholarly journals Sodankylä manual snow survey program

2016 ◽  
Vol 5 (1) ◽  
pp. 163-179 ◽  
Author(s):  
Leena Leppänen ◽  
Anna Kontu ◽  
Henna-Reetta Hannula ◽  
Heidi Sjöblom ◽  
Jouni Pulliainen
Keyword(s):  
Snow Water Equivalent ◽  
Measurement Techniques ◽  
Liquid Water Content ◽  
The Arctic ◽  
Research Centre ◽  
Future Research ◽  
Forest Zone ◽  
Finnish Meteorological Institute ◽  
Snow Properties ◽  
Snow Water

Abstract. The manual snow survey program of the Arctic Research Centre of the Finnish Meteorological Institute (FMI-ARC) consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (HS) and snow water equivalent (SWE). In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day snow pit measurements include observations of HS, SWE, temperature, density, stratigraphy, grain size, specific surface area (SSA) and liquid water content (LWC). Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

scholarly journals Ice fog monitoring near Fairbanks, AK

2021 ◽  
Author(s):  
Dragos Vas ◽  
Steven Peckham ◽  
Carl Schmitt ◽  
Martin Stuefer ◽  
Ross Burgener ◽  
...  
Keyword(s):  
Power Generation ◽  
Environmental Conditions ◽  
Weather Conditions ◽  
Cold Weather ◽  
The Arctic ◽  
Local Power ◽  
Environmental Complexity ◽  
Ice Fog ◽  
Innovative Methods ◽  
Generation Facility

Ice fog events, which occur during the Arctic winter, result in greatly decreased visibility and can lead to an increase of ice on roadways, aircraft, and airfields. The Fairbanks area is known for ice fog conditions, and previous studies have shown these events to be associated with moisture released from local power generation. Despite the identified originating mechanism of ice fog, there remains a need to quantify the environmental conditions controlling its origination, intensity, and spatial extent. This investigation focused on developing innovative methods of identifying and characterizing the environmental conditions that lead to ice fog formation near Fort Wainwright, Alaska. Preliminary data collected from December 2019 to March 2020 suggest that ice fog events occurred with temperatures below −34°C, up to 74% of the time ice fog emanated from the power generation facility, and at least 95% of ice particles during ice fog events were solid droxtals with diameters ranging from 7 to 50 μm. This report documents the need for frequent and detailed observations of the meteorological conditions in combination with photographic and ice particle observations. Datasets from these observations capture the environmental complexity and the impacts from energy generation in extremely cold weather conditions.

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