62 research outputs found

    Video-based raindrop detection for improved image registration

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    Driving in the Rain: A Survey toward Visibility Estimation through Windshields

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    Rain can significantly impair the driver’s sight and affect his performance when driving in wet conditions. Evaluation of driver visibility in harsh weather, such as rain, has garnered considerable research since the advent of autonomous vehicles and the emergence of intelligent transportation systems. In recent years, advances in computer vision and machine learning led to a significant number of new approaches to address this challenge. However, the literature is fragmented and should be reorganised and analysed to progress in this field. There is still no comprehensive survey article that summarises driver visibility methodologies, including classic and recent data-driven/model-driven approaches on the windshield in rainy conditions, and compares their generalisation performance fairly. Most ADAS and AD systems are based on object detection. Thus, rain visibility plays a key role in the efficiency of ADAS/AD functions used in semi- or fully autonomous driving. This study fills this gap by reviewing current state-of-the-art solutions in rain visibility estimation used to reconstruct the driver’s view for object detection-based autonomous driving. These solutions are classified as rain visibility estimation systems that work on (1) the perception components of the ADAS/AD function, (2) the control and other hardware components of the ADAS/AD function, and (3) the visualisation and other software components of the ADAS/AD function. Limitations and unsolved challenges are also highlighted for further research

    Influence of Rain on Vision-Based Algorithms in the Automotive Domain

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    The Automotive domain is a highly regulated domain with stringent requirements that characterize automotive systems’ performance and safety. Automotive applications are required to operate under all driving conditions and meet high levels of safety standards. Vision-based systems in the automotive domain are accordingly required to operate at all weather conditions, favorable or adverse. Rain is one of the most common types of adverse weather conditions that reduce quality images used in vision-based algorithms. Rain can be observed in an image in two forms, falling rain streaks or adherent raindrops. Both forms corrupt the input images and degrade the performance of vision-based algorithms. This dissertation describes the work we did to study the effect of rain on the quality images and the target vision systems that use them as the main input. To study falling rain, we developed a framework for simulating failing rain streaks. We also developed a de-raining algorithm that detects and removes rain streaks from the images. We studied the relation between image degradation due to adherent raindrops and the performance of the target vision algorithm and provided quantitive metrics to describe such a relation. We developed an adherent raindrop simulator that generates synthetic rained images, by adding generated raindrops to rain-free images. We used this simulator to generate rained image datasets, which we used to train some vision algorithms and evaluate the feasibility of using transfer-learning to improve DNN-based vision algorithms to improve performance under rainy conditions.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/170924/1/Yazan Hamzeh final dissertation.pdfDescription of Yazan Hamzeh final dissertation.pdf : Dissertatio

    Visibility Estimation of Traffic Signals under Rainy Weather Conditions for Smart Driving Support

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    Abstract-The aim of this work is to support a driver by notifying the information of traffic signals in accordance with their visibility. To avoid traffic accidents, the driver should detect and recognize surrounding objects, especially traffic signals. However, when driving a vehicle under rainy weather conditions, it is difficult for drivers to detect or to recognize objects existing in the road environment in comparison with fine weather conditions. Therefore, this paper proposes a method for estimating the visibility of traffic signals for drivers under rainy weather conditions by image processing. The proposed method is based on the concept of visual noise known in the field of cognitive science, and extracts two types of visual noise features which ware considered that they affect the visibility of traffic signals. We expect to improve the accuracy of visibility estimation by combining the visual noise features with the texture feature introduced in a previous work. Experimental results showed that the proposed method could estimate the visibility of traffic signals more accurately under rainy weather conditions

    A Flight Evaluation and Analysis of the Effect of Icing Conditions on the ZPG-2 Airship

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    A series of test flights was conducted by the U. S. Navy over a 3- year period to evaluate the effects of icing on the operation of the ZPG-2 airship. In supercooled. clouds, ice formed only on the forward edges of small protuberances and wires and presented no serious hazard to operation. Ice accretions of the glaze type which occurred in conditions described as freezing drizzle adversely affected various components to a somewhat greater extent. The results indicated, a need for protection of certain components such as antennas, propellers, and certain parts of the control system. The tests showed that icing of the large surface of the envelope occurred only in freezing rain or drizzle. Because of the infrequent occurrence of these conditions, the potential maximum severity could not be estimated from the test results. The increases in heaviness caused by icing in freezing rain and drizzle were substantial, but well within the operational capabilities of the airship. In order to estimate the potential operational significance of icing in freezing rain, theoretical calculations were used to estimate: (1) the rate of icing as a function of temperature and rainfall intensity, (2) the climatological probability of occurrence of various combinations of these variables, and (3) the significance of the warming influence of the ocean in alleviating freezing-rain conditions. The results of these calculations suggest that, although very heavy icing rates are possible in combinations of low temperature and high rainfall rate, the occurrence of such conditions is very infrequent in coastal areas and virtually impossible 200 or 300 miles offshore

    Bluff-body aerodynamics and transfer functions for non-catching precipitation measurement instruments.

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    Starting from the old and trivial technique of using a graduated cylinder to collect and manually measure precipitation, numerous advances were made for in-situ precipitation gauges. After decades of scarce innovation, a new family of in-situ precipitation gauges was developed. They are called Non-Catching Gauges (NCG) since they can measure precipitation and its microphysical and dynamic characteristics without the need to collect hydrometeors. The attention that NCGs are gathering today is quite notable, even if they represent only a small fraction of the total precipitation gauges deployed. Their use in the field is bound to continuously grow in time, due to several advantages, discussed in this work, that such instruments present over more traditional ones. However, their major disadvantage is their increased complexity, the effects of which are highlighted by the literature through evidence of calibration and correction issues. Various field intercomparison experiments showed the evidence of significant biases in NCGs measurements. The goal of this work is to investigate two main sources of bias, producing the largest impact on precipitation measurements. The first source of bias evaluated in this work is due to instrument calibration. Several attempts at developing a calibration procedure are presented both in the scientific literature and from the manufacturers. Nevertheless, those methods are hardly traceable to international standards and, in most cases, lack a suitable reference measure to compare against the instrumental output. In this work, a fully traceable calibration procedure is proposed, in analogy with the one already existing for catching type gauges. This requires drops of know diameter and fall velocity to be released over the instrument sensing area. For this reason, the Calibrated Rainfall Generator (CRG) is developed, able to release single drops on demand and measure them independently just before they reach the instrument sensing area. Detachment of drops is obtained by using an electrostatic system, while the measure of their diameter and fall velocity is performed by means of a photogrammetric approach. The Thies Laser Precipitation Monitor (LPM) was tested using the CRG considering two different output telegrams. The first one provides the raw measure of each drop sensed by the instrument while the second one provides the Particle Size and fall Velocity Distribution (PSVD) matrix. Both telegrams show a tendency to underestimate the drop diameter that increases with decreasing the drop size, while errors in the fall velocity measurements have a less definite trend. Furthermore, tests also show a large standard deviation of the measurements, significantly higher than the one of the reference measurements. The underestimation of drop size and fall velocity is also reflected into the RI measurements provided by the instrument, with a resulting underestimation that decreases with increasing the precipitation intensity. The difference between the two telegrams considered is large and may only be explained by differences in the instrument internal processing for the two telegrams. The second instrument tested using the CRG is the Biral VPF-750, a light scatter gauge. Results show a tendency to underestimate both the drop diameter and fall velocity. In the first case, the error decreases with increasing the drops size, similarly to the Thies LPM. However, the error in the fall velocity is considerably higher and instead increases with increasing the drop sizes. In terms of Rainfall Intensity (RI), the instrument shows a strong underestimation that, due to the opposite trend observed for drop diameter and fall velocity, is almost constant with the precipitation intensity. Both instruments show significant biases, corroborated by field intercomparison results from the literature, that is often larger than 10% for the investigated variables. This means that both gauges cannot be classified according to the guidelines proposed in this work for the development of a standard calibration procedure, derived from those already existing for CGs. The second source of bias is wind, a well-established source of environmental error for traditional Catching-type Gauges (CG) but also affecting NCGs. The wind-induced bias is investigated using a numerical approach, combining Computational Fluid Dynamics (CFD) and Lagrangian Particle Tracking (LPT) models. Two different CFD models were tested, the first providing a time-independent steady state solution, while the other is fully time-dependent. Both were compared against wind tunnel results, showing a good agreement with the experimental data, and proving their ability to capture the complex aerodynamic response of instruments when impacted by the wind. The Thies Laser Precipitation Monitor (LPM) is first chosen as a test instrument, being representative of the typical NCGs that are currently deployed in the field. CFD simulations show that wind direction is the primary factor determining the aerodynamic disturbance close to the instrument sensing area. Similar results were found for the OTT Parsivel2, that is another widely diffused NCG. For wind flow parallel to the laser beam, strong disturbance close to the gauge sensing area is observed. Meanwhile, wind coming perpendicular to the laser beam produces minimal flow disturbance. The wind-induced bias is also investigated for the Vaisala WXT-520, an impact disdrometer. This gauge is smaller ad has a more regular shape if compared to the optical disdrometers, but its measuring principle is based on the detection of the drop kinetic energy, while the size and fall velocity are indirectly obtained. CFD simulations show limited disturbance close to the sensing area of the instrument and a negligeable dependency on the wind direction (due to a more radially symmetric geometry). The instrument body further provide minimal shielding of the sensing area. Strong updraft however occurs upstream of the instrument for all wind directions, significantly affecting the fall velocity of the smaller and lighter drops. Using these results, three different LPT models are also tested. The first is an uncoupled model based on the time-independent CFD results and is used to evaluate the instrument performance for all wind speeds and directions considered. The other two models, due to their high computational requirements, are applied only to a selected number of combinations of wind speed and direction for the Thies LPM. Results show a good agreement and allow concluding that the significant increase in computational burden of the latter two models does not significantly improve the accuracy of the results. However, the one-way coupled model highlights the role of turbulence, that may have a significant impact on the instrumental performance when strong recirculation is present near its sensing area. In the case of the two other gauges, only the uncoupled LPT model in combination with the time-independent CFD model is used, this being the best compromise between numerical accuracy and computational cost. Results of the LPT model are presented in terms of variation in the retrieval of precipitation microphysical properties, Catch Ratios (CR), Collection Efficiency (CE) and Radar Retrieval Efficiency (RRE). For the three gauges considered, it is shown that smaller hydrometeors fall velocity close to the instrument sensing area is strongly affected by wind and is – in general – reduced. A significant wind-induced bias is also evident in the Drop Size Distribution (DSD) measured by the gauges. Optical gauges may report a significant lower number of small hydrometeors even at moderate wind speed. Due to the gauge body partially shielding the sensing area. Impact gauge DSD is also strongly influenced by wind, since hydrometeors with high kinetic energy are sensed as having a large diameter. The DSD is therefore shifted towards larger diameters and the instrument tends to overestimate the number of hydrometeors of all sizes. This suggests that the different shapes of the DSD function reported in the field by different instruments may be due, at least partially, to wind-induced biases. In terms of integral precipitation characteristics, the wind direction is the primary factor in determining the performance of optical gauges in windy conditions. For wind parallel to the laser beam, the instrument senses less and less precipitation with increasing the wind speed, with no hydrometeors even reaching the sensing area in some configurations . On the other hand, when the wind is perpendicular to the laser beam, the instrument performs similarly for all wind speeds, with CR and CE values close to one and only a moderate amount of overcatch being observed at high wind speed. Only for the OTT Parsivel2 a non negligeable overcatch is also evident for wind coming at a 45° angle with respect to the beam direction. For the Vaisala WXT-520 the Kinetic Catch Ratio (KCR) and Kinetic Collection Efficiency (KCE) are defined as substitutes for the CR and CE. At low wind speed, the KCR is below unity, due to the reduction in fall velocity produced by the updraft. However, with increasing wind speed, the kinetic energy of hydrometeors carried by wind increases considerably, overcoming the reduction caused by the updraft close to the gauge. For this reason, KCR values becomes much higher than unity, especially for small size hydrometeors. The increase in kinetic energy is reflected into increased KCE values, that are close to unity at low wind speed, but rapidly grow with increasing the wind speed. Wind direction has instead very limited influence on the measurements. In terms of RRE, optical gauges present limited bias for all combinations of wind speed and direction, except for the highest wind speed and flow parallel to the laser beam. This is because a large portion of the radar reflectivity factor (dBZ) is due to medium and large size hydrometeors, that are less influenced by wind. In the case of the impact disdrometer instead, RRE behaves very similarly to the CE, with values that increases with increasing wind speed. This is due to the shift toward larger diameters noted in the DSD that occurs when hydrometeors kinetic energy is increased by wind

    Precipitation Estimation Using C-Band Dual Polarimetric Weather Radar

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    Radar Quantitative Precipitation Estimation (QPE) plays an important role in weather forecasting, especially nowcasting, and hydrology. This study evaluates the current QPE algorithm implemented by the Canadian Radar Network of Environment Canada, suggests an improved algorithm, and also evaluates the use of polarimetric radars for estimation of Snow Water Equivalent (SWE), solid snowfall, and rainfall rates. Data from the dual polarimetric C-band King City radar (CWKR) near Toronto, Ontario, SWE and solid snowfall rates from Oakville, Ontario, SWE from the CAN-Now project at Pearson International Airport (CYYZ), Toronto, Ontario, and Mount Pearl, Newfoundland were used in this project. The ground observations show that the polarimetric variables could be used to infer a few of the microphysical processes during snowfall. It is suggested that the co-polar correlation coefficient (hv) could be sensitive to the size ranges of different snow habits within the radar sampled volume. Also, higher differential reflectivity (ZDR) values were measured with large aggregates due to the Mie resonance effect, lower fluttering angles, or induced field transverse. Data from the three sites were used to develop S(ZeH)-based algorithms at 1 hr interval SWE, where ZeH is the radar equivalent reflectivity factor. Similarly, two additional algorithms were developed using SWE at 10 min intervals from CYYZ and Mt. Pearl but they were found to have less skill. A modest difference was found between S(ZeH) and the polarimetric algorithm, S(ZeH, ZDR), in estimating SWE. The 1 hr interval SWE accumulation from the three sites were combined to develop an additional S(ZeH) algorithm which had statistically better results. The results show a severe underestimation of SWE and solid snowfall rates by the current Environment Canada algorithm. The similarity of the S(ZeH) algorithms for CYYZ and Mount Pearl suggests that the same algorithm could be used for many sites. A strong correlation was found between radar reflectivity factor and ground solid snowfall measurement. Accordingly, S(ZeH) and S(ZeH, ZDR) algorithms were established to directly estimate solid snowfall rates on the ground. The S(ZeH) was found to have superior results compared to the S(ZeH, ZDR). Finally, the polarimetric variables were found to be useful in estimating rainfall rates. Thus, three rainfall algorithms (R(ZeH), R(ZeH, ZDR), R(KDP)) were established and compared against the current algorithm employed by the Environment Canada and counterpart algorithms established by Bringi et al. (2010). A logic tree was devised with certain polarimetric thresholds to choose the optimal algorithm among the three established ones. It appears that for rain, unlike for snow, the polarimetric parameters are very useful for quantitative precipitation estimation

    The role of turbulence in particle-fluid interaction as induced by the outer geometry of catching-type precipitation gauges

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    This thesis work investigates the particle-fluid interaction of hydrometeors along the terminal part of their fall trajectories, while approaching the collector of catching-type precipitation gauges in windy conditions. Both the turbulence generated by the bluff body aerodynamics of precipitation gauges when impacted by the wind and the free-stream turbulence inherent to the natural wind are addressed to assess their role in precipitation measurements. The bluff body aerodynamics of precipitation gauges induces deviations in the trajectories of the approaching hydrometeors due to the acceleration, updraft and turbulence development upstream and above the collector of the gauge. The resulting wind-induced errors were studied in the literature using different approaches \u2013 field measurement campaigns, numerical simulations and wind tunnel experiments. In this work, the numerical approach based on Computational Fluid Dynamic (CFD) simulation, which reduces, when compared with field observations, the time and resources needed to investigate different configurations by varying the wind speed, type of precipitation and gauge geometry, is employed. A Lagrangian Particle Tracking (LPT) model provides the catch ratios as a function of the particle size and wind speed. The LPT model, already available from the literature, was adapted to simulate the trajectories of water droplets when falling through the atmosphere and approaching the gauge collector by parameterizing liquid particles with spherical shape and using suitable drag coefficient equations. The first part of the work aims to validate the numerical approach against a dedicated, innovative and robust experimental campaign obtained by means of Wind Tunnel (WT) experiments (flow velocity measurements, Particle Image Velocimetry and video tracking of water drops) conducted in the wind tunnel facilities available at DICCA and at Politecnico di Milano (within the PRIN 20154WX5NA project). The video tracking experimental setup allowed to compare observed and simulated trajectories under various wind velocity and drop size conditions, and to validate the Lagrangian Particle Tracking model, here adapted to simulate particles falling at a different vertical velocity than the terminal one. Comparison and validation of numerical simulation results against field-measured data introduce the problem of confronting this simplified approach with the natural atmospheric conditions actually affecting operational instruments in the field. Natural wind fields are indeed characterized by turbulent fluctuations, especially near to the ground where precipitation gauges are located. Dedicated CFD simulations with various turbulence generating solutions, based on imposing specific boundary conditions or inserting suitable obstacles designed to achieve the desired level of free-stream turbulence upstream of the gauge, were performed. Wind tunnel measurements were performed in the DICCA facility using, as a turbulence-generating device, a fixed solid fence with a regular square mesh inserted upstream of a calyx shaped gauge. CFD simulations were performed reproducing the same conditions and results were validated by comparison with WT measurements. The comparison between the uniform and turbulent free-stream conditions showed that the normalized updraft in the upwind part, upstream of the centre of the collector, and the downdraft in the downwind part are less accentuated in the turbulent free-stream configuration than in uniform free-stream conditions. This is ascribable to the energy dissipation induced by turbulent fluctuations. The dissipative effect of the free-stream turbulence also has a damping role on the acceleration of the flow above the collector as demonstrated by CFD results. The overall free-stream turbulence effect on the collection performance of the gauges was quantified by computing and comparing the Collection Efficiency (CE) values in uniform and turbulent free-stream conditions. Results demonstrated that the CE values are higher in turbulent free-stream conditions. The effect of the free-stream turbulence on the collection efficiency of the Hotplate\ua9 snow gauge was investigated, and the literature turbulence intensity level (from 8istad, 2015) impacting on the gauge by was obtained in the simulation by imposing a constant turbulent kinetic energy value as a boundary condition upstream of the gauge. The calculated catch ratios are larger for the free-stream turbulence condition with respect to the uniform one for all characteristic sizes of snowflakes. Consequently, the same effect was observed in the calculated CE values. In addition, in order to introduce a realistic level of turbulence at the gauge collector elevation in the simulation, wind speed measurements obtained from a 3D ultrasonic anemometer in the Nafferton Farm site (UK), recorded at high frequency (20 Hz) and at the gauge elevation, were analysed to calculate the free-stream turbulence intensity values for various wind speeds. This was used to perform a CFD simulation on a chimney shaped gauge and to calculate its effect on the collection performance. To better reproduce the decay of the turbulence intensity in space and its effect on the gauge, Large Eddy Simulations (LES) were also performed in both uniform and turbulent free-stream conditions while simulating the trajectories of solid precipitation particles, which are more sensitive than raindrops to the turbulent fluctuations. Results, in terms of the catch ratio for each characteristic size of snowflakes, show a different behaviour when compared to the uniform conditions. A larger free-stream turbulence intensity induces a more pronounced undercatch for small size particles (less than 2 mm) with respect to the uniform case, while the undercatch is reduced for larger particles. This is due to the greater aptitude of the small size particles to follow the turbulent velocity fluctuations, while larger particles are more inertial, and to the reduced velocity components that particles cross in turbulent free-stream conditions near the gauge body. The obtained CE values are higher in turbulent free-stream conditions, confirming the observations already obtained for the airflow features, where a potential overestimation of the undercatch obtained in uniform free-stream conditions was hypothesized. Based on the CFD results and on the validation provided by wind tunnel observations it is possible to conclude that accounting for the free-stream airflow turbulence in the simulation is required to avoid underestimation of the collection efficiency of precipitation gauges. A turbulent free-stream is indeed the natural atmospheric condition of the wind impacting on operational precipitation gauges in the field. This work demonstrates that numerical derivation of correction curves for use in precipitation measurements as proposed hitherto in the literature is affected by a systematic overestimation of the wind-induced error due to the simplifying assumption of uniform free-stream conditions. Finally, in order to achieve results that can be used in an operational context, suitable Collection Efficiency (CE) curves and the associated adjustment curves, which directly provide the expected undercatch as a function of the wind speed and the measured precipitation intensity, were derived for two sample measurement instruments. The first one is best suited for rainfall measurements and is characterised by the common cylindrical shape of traditional catching type gauges, therefore a numerical formulation of the CE curves as a function of rainfall intensity is proposed. The second one, the Hotplate\ua9 gauge, is best suited for snowfall measurements and is characterised by an innovative measuring principle implying a dedicated geometry of the sensor. In this case, the numerically derived CE curves are expressed as a function of snowfall intensity. For the typical cylindrical gauge, the residual dependency of the CE curves on the rainfall intensity was investigated in order to obtain a single CE expression as a function of both the rainfall intensity and wind speed. The parameters of the Particle Size Distribution (PSD) for various classes of the RI were derived by literature data from the Italian territory. Then the variation of the PSD parameters as a function of the RI was obtained, and subsequently also the parameters of the sigmoidal curves, used to fit the numerical CE values, were parametrized with the RI. As a result, easy to use adjustment curves as a function of both the measured rainfall intensity and wind speed were derived. In the case of the Hotplate\ua9 snow gauge, the shape of the CE curves differs from the typical sigmoidal one due to its complex geometry. At low wind speed, the aerodynamic response of the gauge is predominant and CE values decrease with increasing the wind speed up to a wind threshold value beyond which the geometrical effect on the collection performance starts to be relevant and the CE increases. At very high wind speeds the geometrical contribution prevails and the CE becomes even larger than one
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