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Visibility is a critical factor for transportation, even if we refer to air, water, or ground transportation. The biggest trend in the automotive industry is autonomous driving, the number of autonomous vehicles will increase exponentially, prompting changes in the industry and user segment. Unfortunately, these vehicles still have some drawbacks a...
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... is generated at the contact of the splashed liquid with the colder air outside the machine. The fog particles were measured with a microscope, Olympus BX51M, by impressing the fog particles first on the mirror and then on a shiny metal (Figure 3), but we concluded that the deposit surface does not cause any difference. Following this hypothesis we were able to obtain a static distribution of the fog particles that could be analyzed (in the fog cloud the particles are of different sizes and the dynamics of particle variation is extremely large). ...
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... The meteorological stations operating within ICOS are also used to study fog events (Kivalov et al., 2023). (iv) Ovesnik et al. (2012), Matus et al. (2020) and Miclea et al. (2020) published results about the improvement of sensors for detection of fog formation and density. ...
A micrometeorological fog experiment was carried out in Budapest, Hungary during the winter half year of 2020–2021. The field observation involved (i) standard meteorological and radiosonde measurements; (ii) surface radiation balance and energy budget components, and (iii) ceilometer measurements. 23 fog events occurred during the whole campaign. Foggy events were categorized based on two different methods suggested by Tardif and Rasmussen (2007) and Lin et al. (2022). Using the Present Weather Detector and Visibility sensor (PWD12), duration of foggy periods are approximately shorter (~ 9%) compared to ceilometer measurements. The categorization of fog based on two different methods suggests that duration of radiation fogs is lower compared to that of cloud base lowering (CBL) fogs. The results of analysis of observed data about the longest fog event suggest that (i) it was a radiation fog that developed from the surface upwards with condition of a near neutral temperature profile. Near the surface the turbulent kinetic energy and turbulent momentum fluxes remained smaller than 0.4 m² s–2 and 0.06 kg m–1 s–2, respectively. In the surface layer the vertical profile of the sensible heat flux was near constant (it changes with height ~ 10%), and during the evolution of the fog, its maximum value was smaller than 25 W m–2, (ii) the dissipation of the fog occurred due to increase of turbulence, (iii) longwave energy budget was close to zero during fog, and a significant increase of virtual potential temperature with height was observed before fog onset. The complete dataset gives an opportunity to quantify local effects, such as tracking the effect of strengthening of wind for modification of stability, surface layer profiles and visibility. Fog formation, development and dissipation are quantified based on the micrometeorological observations performed in suburb area of Budapest, providing a processing algorithm for investigating various fog events for synoptic analysis and for optimization of numerical model parameterizations.
... Efficient image compression can be used in systems that check whether the road tax was paid or not; in this scenario, the license plate is again a region of interest with the other ROI being a sticker on the windshield that is usually the proof of payment. Another example where a compression method could be useful is the application described in [57] where the visibility on a portion of a road during foggy weather is estimated using a laser, LIDAR, and cameras. ...
Image compression is a vital component for domains in which the computational resources are usually scarce such as automotive or telemedicine fields. Also, when discussing real-time systems, the large amount of data that must flow through the system can represent a bottleneck. Therefore, the storage of images, alongside the compression, transmission, and decompression procedures, becomes vital. In recent years, many compression techniques that only preserve the quality of the region of interest of an image have been developed, the other parts being either discarded or compressed with major quality loss. This paper proposes a study of relevant papers from the last decade which are focused on the selection of a region of interest of an image and on the compression techniques that can be applied to that area. To better highlight the novelty of the hybrid methods, classical state-of-the-art approaches are also analyzed. The current work will provide an overview of classical and hybrid compression methods alongside a categorization based on compression ratio and other quality factors such as mean-square error and peak signal-to-noise ratio, structural similarity index measure, and so on. This overview can help researchers to develop a better idea of what compression algorithms are used in certain domains and to find out if the presented performance parameters are of interest for the intended purpose.
... As a result, instruments for visibility measuring were developed to replace the traditional human eye observation [12,13]. Currently, common instruments used for visibility measurement include transmissometers [14], optical scatterometers [15], and visibility LiDARs [16]. ...
Calibration of the imaging environment is an important step in computational imaging research, as it provides an assessment of the imaging capabilities of an imaging system. Visibility is an important quantity reflecting the transparency of the atmosphere. Currently, transmissometers and optical scatterometers are the primary methods for visibility measurement. Transmissometers measure visibility along a single direction between the transmitter and receiver but encounter challenges in achieving optical alignment under long baseline conditions. Optical scatterometers measure the visibility within a localized area since they collect only a small volume of air. Hence, both transmissometers and optical scatterometers have limitations in accurately representing the visibility distribution of an inhomogeneous atmosphere. In this work, a multi-channel visibility distribution measurement via the optical imaging method is proposed and validated in a standard fog chamber. By calibrating the attenuation of infrared LED arrays, the visibility distribution over the entire field of view can be calculated based on the atmospheric visibility model. Due to the large angle of divergence of the LED, the need for optical alignment is eliminated. In further discussion, the key factors affecting the accuracy of visibility measurement are analyzed, and the results show that increasing the measurement baseline, increasing the dynamic range of the detector, and eliminating background light can effectively improve the accuracy of visibility measurement.
... Concerning the use of state-of-the-art lidar applications for the estimation and study of atmospheric visibility, there are few examples, almost exclusively aimed at detecting and warning of fog events, which exhibit a very clear backscattering signal [15][16][17][18]. Even so, these studies focus on the detection of extreme visibility events, rather than providing constant visibility reports over a variety of conditions. ...
The estimation of visibility is of significant importance in aviation safety and forms part of the measurements routinely collected in real time to provide safety guidelines and decisions. Our work concerns the creation and implementation of a lidar-based visibility estimation system as part of the SAFETRANS research program. We created a reproducible system to (1) support standard airport equipment, (2) serve simultaneously as a visibility meter and a ceilometer reporting on cloud cover, (3) offer increased accuracy and improved capabilities compared to standardized equipment currently in use while (4) requiring minimal user training to function. This work presents the visibility estimation and cloud cover algorithms and subsequently reports on results of field tests in a number of Greek airports under various atmospheric conditions.
... From the results we presented, it appears that the sensitivity of the ambient atmospheric electric field (PG) to the presence of fog droplets, even at the haze stage before reaching saturation and a relative humidity of 100%, may offer another tool for fog monitoring, in support of, and not as replacement for, additional modern technologies such as lidar [41], satellite imagery in various spectral bands [42,43], and advanced image-analysis algorithms for evaluating visibility [44,45]. Each of the abovementioned technologies has advantages but also limitations, as they require computational resources that are not always available in real-time and rely on satellite overpasses and sensor resolution. ...
Ground-based measurements of the atmospheric electric field have been recorded continuously since 2013 at the Wise Observatory, located in the Negev Desert Highland in southern Israel. The data have been used for defining the characteristics of fair weather and to identify the signatures of dust storms, lightning activity, and clouds. We report here on new results from observations of the variability of the electric field (transformed into the potential gradient, PG) during several foggy days, along with meteorological data on wind speed and relative humidity. The results show a substantial increase in the electric field (up to 400–650 V m−1) compared with the mean fair weather values observed at the site (180–190 V m−1). This increase is especially clear during times of high relative humidity values (95%+) and low wind speed (<3 m s−1). This increase is likely a consequence of the reduction in the atmospheric conductivity at low levels, due to the attachment of charge carriers to fog droplets. Based on this discovery, it is suggested that continuously monitoring the electric field may offer an additional operational tool to alert for the onset and termination of fog at specific locations, such as airports and harbors, where this nowcasting capability is required.
... The AV system relies on photonic radars for the effective performance of most of the conveniences and hence, should be able to detect effectively under the impact of atmospheric turbulences, particularly in low-visibility conditions to achieve the extended range detection. In the transportation sector, zero visibility is referred to as visibility of less than 50 m under adverse weather conditions that may leads to accidents [57]. Consequently, the performance of the proposed photonic radar is further studied under the impact of fog and rain. ...
... conveniences and hence, should be able to detect effectively under the impact of atmospheric turbulences, particularly in low-visibility conditions to achieve the extended range detection. In the transportation sector, zero visibility is referred to as visibility of less than 50 m under adverse weather conditions that may leads to accidents [57]. Consequently, the performance of the proposed photonic radar is further studied under the impact of fog and rain. ...
Detection and tracing of multiple targets in a real-time scenario, particularly in the urban setup under adverse atmospheric conditions, has become a major challenge for autonomous vehicles (AVs). Photonic radars have emerged as promising candidates for Avs to realize via the recognition of traffic patterns, navigation, lane detection, self-parking, etc. In this work we developed a direct detection-based, frequency-modulated photonic radar to detect multiple stationary targets using four different transmission channels multiplexed over a single free space channel via wavelength division multiplexing (WDM). Additionally, the performance of the proposed photonic radar was examined under the impact of adverse weather conditions, such as rain and fog. The reported results in terms of received power and signal-to-noise ratio (SNR) showed successful detection of all the targets with bandwidths of 1 GHz and 4 GHz. The proposed system was also tested for range resolution of targets at 150 m and 6.75 cm resolution with 4 GHz bandwidth was reported, while resolution of 50 cm was reported with 1 GHz of bandwidth.
... Knowing the LiDAR's visibility under the current weather condition is critical because the short-sighted perception will delay the vehicle's response and limit the ability to respond to obstacles. We emphasize this limitation but leave the accurate calculation of the measurable range as future work because this is out of the current paper's scope and has been studied in prior works [138]. Instead, we provide a rule of thumb as follows. ...
As Autonomous Vehicle (AV) development has progressed, concerns regarding the safety of passengers and agents in their environment have risen. Each real world traffic collision involving autonomously controlled vehicles has compounded this concern. Open source autonomous driving implementations show a software architecture with complex interdependent tasks, heavily reliant on machine learning and Deep Neural Networks (DNN), which are vulnerable to non deterministic faults and corner cases. These complex subsystems work together to fulfill the mission of the AV while also maintaining safety. Although significant improvements are being made towards increasing the empirical reliability and confidence in these systems, the inherent limitations of DNN verification create an, as yet, insurmountable challenge in providing deterministic safety guarantees in AV. We propose Synergistic Redundancy (SR), a safety architecture for complex cyber physical systems, like AV. SR provides verifiable safety guarantees against specific faults by decoupling the mission and safety tasks of the system. Simultaneous to independently fulfilling their primary roles, the partially functionally redundant mission and safety tasks are able to aid each other, synergistically improving the combined system. The synergistic safety layer uses only verifiable and logically analyzable software to fulfill its tasks. Close coordination with the mission layer allows easier and early detection of safety critical faults in the system. SR simplifies the mission layer's optimization goals and improves its design. SR provides safe deployment of high performance, although inherently unverifiable, machine learning software. In this work, we first present the design and features of the SR architecture and then evaluate the efficacy of the solution, focusing on the crucial problem of obstacle existence detection faults in AV.
... Signal attenuation due to scattering, reflection, and absorption of light and the reduction of detection distance are identified [26] Analysis of the effects of fog conditions on the lidar system for visibility distance estimation for autonomous vehicles on roads ...
... Therefore, an algorithm was developed to reject signals reflected from dust particles by filtering data according to radar. Fog conditions have a similar effect on lidar performance [26,27]. In [28], an algorithm based on the Kalman filter and nearby point cloud denoising was developed to improve the reconstruction of 3D lidar measurements from autonomous vehicles in adverse weather conditions. ...
The development of light detection and ranging (lidar) technology began in the 1960s, following the invention of the laser, which represents the central component of this system, integrating laser scanning with an inertial measurement unit (IMU) and Global Positioning System (GPS). Lidar technology is spreading to many different areas of application, from those in autonomous vehicles for road detection and object recognition, to those in the maritime sector, including object detection for autonomous navigation, monitoring ocean ecosystems, mapping coastal areas, and other diverse applications. This paper presents lidar system technology and reviews its application in the modern road transportation and maritime sector. Some of the better-known lidar systems for practical applications, on which current commercial models are based, are presented, and their advantages and disadvantages are described and analyzed. Moreover, current challenges and future trends of application are discussed. This paper also provides a systematic review of recent scientific research on the application of lidar system technology and the corresponding computational algorithms for data analysis, mainly focusing on deep learning algorithms, in the modern road transportation and maritime sector, based on an extensive analysis of the available scientific literature.
... Sallis et al. [234] thought of using vehicular LiDAR's backscatter effect to detect air pollution and fog intensity, but visibility are not considered at that time. Miclea et al. [235] came up with a creative way by setting up a 3-meter-long model chamber with a "toy" road and model cars in it which can be easily filled with almost-homogeneous fog. They successfully identified the correlations between the decrease of the optical power and the decrease of the visual acuity in a scaling fog condition. ...
Automated Driving Systems (ADS) open up a new domain for the automotive industry and offer new possibilities for future transportation with higher efficiency and comfortable experiences. However, autonomous driving under adverse weather conditions has been the problem that keeps autonomous vehicles (AVs) from going to level 4 or higher autonomy for a long time. This paper assesses the influences and challenges that weather brings to ADS sensors in an analytic and statistical way, and surveys the solutions against inclement weather conditions. State-of-the-art techniques on perception enhancement with regard to each kind of weather are thoroughly reported. External auxiliary solutions like V2X technology, weather conditions coverage in currently available datasets, simulators, and experimental facilities with weather chambers are distinctly sorted out. By pointing out all kinds of major weather problems the autonomous driving field is currently facing, and reviewing both hardware and computer science solutions in recent years, this survey contributes a holistic overview on the obstacles and directions of ADS development in terms of adverse weather driving conditions.
... Autonomous vehicles are reliant upon photonic radars on behalf of most of the conveniences, and hence, they should be able to deliver extended range visibility for precise recognition of the target even under severe atmospheric conditions. Usually, zero visibility in the AV segment is the visibility of fewer than 50 m under adverse atmospheric conditions such as fog, snow, or rain and may possibly lead to mishaps [35]. Therefore, the performance of the proposed photonic radar system is further studied under the effects of fog and rain. ...
In recent years, there have been plenty of demands and growth in the autonomous vehicle industry, and thus, challenges of designing highly efficient photonic radars that can detect and range any target with the resolution of a few centimeters have been encountered. The existing radar technology is unable to meet such requirements due to limitations on available bandwidth. Another issue is to consider strong attenuation while working under diverse atmospheric conditions at higher frequencies. The proposed model of photonic radar is developed considering these requirements and challenges using the frequency-modulated direct detection technique and considering a free-space range of 750 m. The result depicts improved range detection in terms of received power and an acceptable signal-to-noise ratio and range under adverse climatic situations.
