Foggy Conditions Research Articles

Back-propagation neural network model to predict visibility at a road link-level

Fog and rain influence the ability of the drivers to see other vehicles, pedestrians, bicyclists, and fixed objects, and, hence, increase the likelihood of getting involved in a crash on a road. Resource constraints limit installing weather monitoring sensors at regular intervals (for example, every 1, 2, 3, or 4 km) on a road. Therefore, the objective of this paper is to develop a feed-forward back-propagation neural network (BPNN) model to predict fog / low visibility condition, and, apply at a road link-level. Five years of meteorological data were collected from 238 weather monitoring stations in and around North Carolina to develop and validate the BPNN visibility model. The predicted visibility using meteorological data was compared with visibility from the weather monitoring sensor installed at five geographically distributed locations in North Carolina. The BPNN visibility model has better visibility prediction capability during a normal foggy condition when compared to visibility during thick/dense fog condition.

Comparison of ambient air pollution levels of Amritsar during foggy conditions with that of five major north Indian cities: multivariate analysis and air mass back trajectories

In the present study, winter fog events (Nov. 2017–Feb. 2018) in Amritsar city were compared with other major cities of North India. Multivariate data analysis, along with air mass trajectory analysis, was used to explain the complex behaviour of ambient air quality during winter fog. Average particulate matter (PM) during fog events was PM2.5 (77 μg m−3), PM10 (162 μg m−3) above the 24 h average National Ambient Air Quality Standards (NAAQS) of PM2.5 (60 μg m−3) and PM10 (100 μg m−3), respectively prescribed by Government of India. Wind speed and visibility during fog events were studied along with prevailing wind direction for major PM episodes. Amritsar’s PM2.5 comparison with Ludhiana, Delhi, Kanpur, Lucknow, and Jaipur showed a clear link between Amritsar with Ludhiana (r = 0.807), a North Indian industrial hub. Lucknow and Kanpur had a strong correlation (r = 0.826) due to their proximity. Box-plot of PM2.5 to PM10 ratio revealed a lower contribution of PM2.5 in Amritsar as compared to other cities. Dimensionality reduction using factor analysis of ambient air quality and meteorological parameters grouped the data in order of their variance explained. The first principal component (PC-1) was PM2.5 and PM10, followed by an antagonist correlation of humidity with wind velocity and visibility in Amritsar city. Factor analysis of ambient air quality of six cities, grouped Delhi, Kanpur, and Lucknow into PC-1, followed by Ludhiana and Amritsar as PC-2 which could be due to their proximity signifying the similar ambient air quality of the sites. In order to determine the origin of air mass, 24 h backward trajectories were studied and corroborated with wind rose profile. The results revealed the transport of air masses from the west to the source location.

Simple Fabrication of Water Harvesting Surfaces Using Three-Dimensional Printing Technology

A biomimetic surface for water collection was successfully engineered using three-dimensional (3D) printing technology. The fused deposition modeling-type 3D printing was used to create a reusable mold. This was used to cast waveform microstructures on a hydrophobic polymer surface, which was induced by using stacked filaments. The etching was performed on the printed mold by using a chemical solvent to generate nano/micro pores, which enhanced the rolling-off motion of water droplets. To create a hydrophilic region on the hydrophobic surface, the metal deposition was achieved using a 3D-printed mask and the self-masking effect of the tilted tips of waveform microstructures. The metal array served as seeding points for the growth of water droplets in foggy conditions. As a result, the fabricated biomimetic surface exhibited the highest water-collecting performance (average 0.77 g for 10 min) compared with the other four different surfaces. This study demonstrates the use of 3D printing technology to rapidly and simply fabricate engineered (hybrid) surfaces for various applications involving facile control of wettability.

Using a multi-user driving simulator system to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits

Vehicle fleet rear-end collisions (FRECs) are an extremely fatal type of traffic collisions on freeway and they usually occur in foggy weather. This study aimed to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits on freeway. A multi-user driving simulator system was used to conduct the experiment and the driving behavior data were collected from eight participants. The experimental results showed that as the fog density increased, the length of vehicle fleet decreased significantly, and drivers tended to keep a more stable car-following distance. The fog weather and short vehicle gap prompted drivers to react faster and brake harder in respond to the leading vehicle’s brake. In spite of the compensational behaviors, more FRECs were observed under heavy fog condition. Lowering speed limit can significantly reduce the FRECs under foggy conditions. As the speed limits reduced, drivers’ brake response time and speed variance significantly reduced. The study also found that drivers’ brake response time was negatively correlated with their positions in the fleet. Drivers in the front positions of the fleet had a longer response time than drivers in the back positions and thus were more likely to encounter collisions. The study generated a better understanding of drivers’ behavioral pattern in a vehicle fleet and the patterns of vehicle fleet rear-end collisions occurrence. The findings also shed lights on the design of driver assistance system for complex driving situations such as freeway driving under adverse weather.

Degradation of light carrying orbital angular momentum by ballistic scattering

Structured light can enhance the functionality of optical communication and sensing systems. Dense scattering environments such as those experienced in coastal water or foggy conditions result in degradation of structured optical fields. We present findings that characterise the degradation of the phase structure of ballistic scattered light carrying Orbital Angular Momentum (OAM) propagated through a dense scattering medium over distances of up to 20m. We present a numerical channel modelling approach that can predict the scattering behaviour at extended distances, which indicates that there is a strong mode dependent variance in crosstalk from the interaction of beams that carry OAM with randomly displaced scattering particles. These results present a novel effect that could allow the use of OAM modes to enhance particulate size sensors and could potentially lead to the development of novel tools for monitoring particles in underwater or free-space optical channels.

Development of Legibility Distance Models for Each Color according to Luminance under Foggy Condition

Development of Legibility Distance Models for Each Color according to Luminance under Foggy Condition

Deformation Time Series and Driving-Force Analysis of Glaciers in the Eastern Tienshan Mountains Using the SBAS InSAR Method.

Glacier melting is one of the important causes of glacier morphology change and can provide basic parameters for calculating glacier volume change and glacier mass balance, which, in turn, is important for evaluating water resources. However, it is difficult to obtain large-scale time series of glacier changes due to the cloudy and foggy conditions which are typical of mountain areas. Gravity-measuring satellites and laser altimetry satellites can monitor changes in glacier volume over a wide area, while synthetic-aperture radar satellites can monitoring glacier morphology with a high spatial and temporal resolution. In this article, an interferometric method using a short temporal baseline and a short spatial baseline, called the Small Baseline Subsets (SBAS) Interferometric Synthetic-Aperture Radar (InSAR) method, was used to study the average rate of glacier deformation on Karlik Mountain, in the Eastern Tienshan Mountains, China, by using 19 Sentinel-1A images from November 2017 to December 2018. Thus, a time series analysis of glacier deformation was conducted. It was found that the average glacier deformation in the study region was −11.77 ± 9.73 mm/year, with the observation sites generally moving away from the satellite along the Line of Sight (LOS). Taking the ridge line as the dividing line, it was found that the melting rate of southern slopes was higher than that of northern slopes. According to the perpendicular of the mountain direction, the mountain was divided into an area in the northwest with large glaciers (Area I) and an area in the southeast with small glaciers (Area II). It was found that the melting rate in the southeast area was larger than that in the northwest area. Additionally, through the analysis of temperature and precipitation data, it was found that precipitation played a leading role in glacier deformation in the study region. Through the statistical analysis of the deformation, it was concluded that the absolute value of deformation is large at elevations below 4200 m while the absolute value of the deformation is very small at elevations above 4500 m; the direction of deformation is always away from the satellite along the LOS and the absolute value of glacier deformation decreases with increasing elevation.

Investigating rear-end collision avoidance behavior under varied foggy weather conditions: A study using advanced driving simulator and survival analysis

Previous studies have focused on the impact of visibility level on drivers’ behavior and their safety in foggy weather. However, other important environmental factors such as road alignment have not been considered. This paper aims to propose a methodology in investigating rear-end collision avoidance behavior under varied foggy conditions, with focusing on changes in visibility and road alignment in this study. A driving simulator experiment with a mixed 2 × 4 × 6 factor design was conducted using an advanced high-fidelity driving simulator. The design matrix includes two safety-critical conditions, four visibility conditions, and six road alignment situations (in terms of the road curve and slope). Behavior variables from different dimensions were identified and compared under varied conditions. To estimate the safety of drivers, a time-based measurement, speed reduction time, is selected among the variables as a measure of safety. The survival analysis approach was introduced to model the relationship between environmental factors and driver safety, using speed reduction time as the survival time. Both the Kaplan-Meier method and the COX model were applied and compared. Results generally suggest that reduced visibility leads to more dangerous rear-end collision avoidance behavior from different aspects. Though findings are mixed regarding the road alignment, the impact of the road alignment was found to be significant. Interestingly, conditions of downward slope were found to be safer. Overall, the COX model outperformed the Kaplan-Meier method in understanding the impact of environmental factors, and it can be applied to investigate other contributing factors for freeway safety under foggy weather conditions.

Gbit/s ultraviolet-C diffuse-line-of-sight communication based on probabilistically shaped DMT and diversity reception.

We demonstrated a high-speed 1×2 single-input and multiple-output (SIMO) diffuse-line-of-sight (diffuse-LOS) ultraviolet-C (UVC) solar-blind communication link over a distance of 5 meters. To approach the Shannon limit and improve the spectral efficiency, we implemented probabilistically shaped discrete multitone modulation. As compared to a single-input and single-output (SISO) counterpart, we observed significant improvement in the SIMO link in terms of the angle of view of the receiver and the immunity to emulated weather condition. A wide angle of view of ± 9° is achieved in the SIMO system, with up to a 1.09-Gbit/s achievable information rate (AIR) and a minimum value of 0.24 Gbit/s. Moreover, the bit error rate of the SIMO link in emulated foggy conditions is lowered significantly when compared to that of the SISO link. This work highlights the practicality of UVC communication over realistic distances and in turbulent environments to fill the research gap in high-speed, solar-blind communication.

Performance of Opportunistic Receiver Beam Selection in Multiaperture OWC Systems Over Foggy Channels

The atmospheric foggy condition is a major bottleneck for the deployment of optical wireless communication (OWC) systems in outdoor environments. Although the attenuation coefficient in the foggy channel follows the simple Gamma distribution, the distribution of its channel state is quite complicated similar to the well-studied Gamma–Gamma turbulence channel. Furthermore, existing literature suggested schemes that require feedback of the channel state information (CSI) to improve the outage performance of the OWC system under foggy conditions. In this article, we study the average signal-to-noise ratio (SNR), ergodic rate, and energy consumption performance of OWC systems under foggy conditions. First, we show that a single-aperture OWC system suffers significantly from the fog attenuation by deriving analytical expressions on the ergodic rate and energy consumption. Then, we consider a multiaperture OWC system equipped with an opportunistic receiver beam selection (RBS) scheme. The RBS scheme is based on the simple selection combining diversity algorithm, which does not require the knowledge of CSI. We analyze the proposed scheme by deriving computable bounds on the average SNR, ergodic rate, and energy consumption using system parameters and show the performance improvement of the RBS scheme comparing the single-aperture system. We demonstrate the performance of the considered scheme and validate derived expressions using computer simulations.

Extracting features from infrared images using convolutional neural networks and transfer learning

Infrared cameras are more useful than visible light cameras in dark and foggy conditions; therefore, infrared imaging is becoming an increasingly popular subject of research. Feature extraction is an important aspect of image processing, but traditional convolutional neural networks (CNNs) trained on visible images cannot be used with infrared images. This study presents a method for retraining the Visual Geometry Group 19-layer CNN (VGG-19) to extract features from infrared images. First, a thermal image dataset was obtained from public datasets; this was then augmented by flipping, zooming, shifting, and rotating the images. Next, the architecture of the VGG-19 CNN was redesigned, and transfer learning was used to fine-tune the trainable layers. It was shown that the transfer-learned neural network could extract more information from infrared images than the original network could. To verify the validity of this method, it was also applied to the MobileNet, and the transfer-learned MobileNet also produced better results.

A real-time fast defogging system to clear the vision of driver in foggy highway using minimum filter and gamma correction

Fog is the most hindrance and unavoidable problem faced by drivers while driving. Due to foggy condition and poor visibility, especially in early morning and late-night, drivers are unable to see distant object on the road. As a result, possibility of road accident increases. In this article, a fast-real-time vision-based defogging system is proposed to clear the vision of highway during driving in the foggy environmental condition. The proposed system can remove the haziness of the driver’s vision and can present a clear view of the road within a very short span of time. Processing of each frame is comprised of four steps: calculation of atmospheric light using minimum filter, transmission map, scene radiance and finally gamma correction is applied for removing the haziness with perfect contrast adjustment. In order to reduce time complexity, instead of estimating atmospheric light for each frame, it is calculated at an interval of 5000 frames. Many real-time heuristic tests have been conducted during day as well at night on the highway and test analysis reveals that, after defogging, the distance of visibility increases by more than 65% during heavy fog. Besides, there is a massive increase in visibility during low foggy condition also.

Observations of carbon dioxide and turbulent fluxes during fog conditions in north India

The occurrence of thick fog for longer duration in the northern regions of India disturbs the aviation, road transportation and other day to day activities. To understand the turbulence properties during fog period, we measured the atmospheric turbulent parameters along with carbon dioxide concentrations in the atmospheric boundary layer using eddy covariance system. These measurements were conducted over the agricultural station, Hisar, India, during the months of January–February of the year 2017 and 2018. During this period, total five thick fog events and three moderate fog events were captured. The turbulent parameter such as friction velocity, stability, sensible and latent heat fluxes are presented with respect to fog events. During the study period, the western disturbance persists over the north Pakistan and neighborhood region which advects the large amount of moisture into the lower troposphere and further through evaporation. It enforces stable and clear sky atmospheric conditions and reduces the surface temperature leading to the formation of strong surface-based temperature inversion which facilitates the fog formation in the study region. The land surface processes with neutral stability conditions in the surface layer, play significant role to sustain fog in the study region. The observations show substantial increase of carbon dioxide concentration during the thick fog events. The foggy days did not depict the diurnal pattern in flux of CO2. The anomalies of the meteorological parameters during foggy days and clear sky are analyzed. The foggy conditions (04:00–10:00 h, IST) are found to be characterized with low wind speed, high relative humidity with remarkable fluctuations in dew point temperature. Also, the sensible and latent heat flux shows remarkable changes during foggy and clear sky conditions.

Exploring the Effects of Signs’ Design and In-Vehicle Audio Warning on Driver Behavior at Flashing-Light-Controlled Grade Crossings: A Driving Simulator-Based Study

The complex environment at grade crossings and the severe collision consequences give rise to the concern of safety condition at crossings among traffic control authorities. Optimizing conventional devices and applying emerging technologies are worthwhile measures to improve the safety conditions at grade crossings. In this study, a flashing-light running (FLR) warning system was proposed to reduce crossing violation and improve performances of drivers at flashing-light-controlled grade crossings (FLCGCs). Forty-four fully licensed drivers aged between 30 and 48 years participated in a driving simulator study to investigate the efficacy of two countermeasures of the system: proposed design of signs and pavement markings (PSM) for grade crossing, and two-stage in-vehicle audio warning (IVAW) technology. A range of flashing light trigger timing and two foggy conditions were designed in this experiment to test the system applicability. Drivers’ gender and vocation were considered as well to examine drivers’ adaptation to the new proposed system. Five variables were collected and analyzed in this study to investigate the effectiveness of the system, i.e., drivers’ compliance, approaching mean speed, brake reaction time, deceleration, and red-to-crossing time. Results showed that drivers’ driving performances were improved in both PSM only condition and PSM + W condition. The FLR warning system could eliminate the negative effects of foggy weather and reduce gender differences in driver behaviors to some extent. These findings suggested that the FLR warning system has a potential to reduce the probability of grade crossing collisions.

Performance analysis of continuous-variable measurementdevice-independent quantum key distribution under diverse weather conditions**Project supported by the National Natural Science Foundation of China (Grant No. 61505261).

The effects of weather conditions are ubiquitous in practical wireless quantum communication links. Here in this work, the performances of atmospheric continuous-variable measurement-device-independent quantum key distribution (CV-MDI-QKD) under diverse weather conditions are analyzed quantitatively. According to the Mie scattering theory and atmospheric CV-MDI-QKD model, we numerically simulate the relationship between performance of CV-MDI-QKD and the rainy and foggy conditions, aiming to get close to the actual combat environment in the future. The results show that both rain and fog will degrade the performance of the CV-MDI-QKD protocol. Under the rainy condition, the larger the raindrop diameter, the more obvious the extinction effect is and the lower the secret key rate accordingly. In addition, we find that the secret key rate decreases with the increase of spot deflection distance and the fluctuation of deflection. Under the foggy condition, the results illustrate that the transmittance decreases with the increase of droplet radius or deflection distance, which eventually yields the decrease in the secret key rate. Besides, in both weather conditions, the increase of transmission distance also leads the secret key rate to deteriorate. Our work can provide a foundation for evaluating the performance evaluation and successfully implementing the atmospheric CV-MDI-QKD in the future field operation environment under different weather conditions.

Impact of Variable Speed-Limit System on Driver Speeds during Low-Visibility Conditions

AbstractLow-visibility conditions can inhibit a driver’s ability to perceive appropriate operating speeds, particularly during foggy conditions in which the characteristics of the fog can vary spat...

Report on Sky Brightness, Seeing, and Weather Measurements at Timau Observatory, East Nusa Tenggara

In 2015, a joint collaboration project to build a new observatory in Mount Timau, East Nusa Tenggara was initiated between LAPAN, ITB, UNDANA, Kupang Regency and East Nusa Tenggara governments. The site selection is based on preliminary studies conducted on nearby location. This paper presents in situ measurements report on seeing, weather and sky brightness obtained on July 2018 using Differential Image Motion Monitor (DIMM) with 20 cm-telescope, Davis Vantage Vue automatic weather station, and Sky Quality Meter, respectively. Despite the high humidity and foggy condition on the afternoon, the site has good seeing condition with median of 0.93 arcsecond and sky brightness around 22.18 magnitude per arcsecond square after midnight.

A joint image dehazing and segmentation model

Objects and their feature identification in hazy or foggy weather conditions has been of interest in the last decades. Improving image visualization by removing weather influence factors for easy image postprocessing, such as object detection, has benefits for human assistance systems. In this paper, we propose a novel variational model that will be capable of jointly segmenting and dehazing a given image. The proposed model incorporates atmospheric veil estimation and locally computed denoising constrained surfaces into a level set function by performing a robust and efficient image dehazing and segmentation scheme for both gray and color outdoor images. The proposed model not only shows efficient segmentation of objects in foggy images by outperforming state-of-the-art methods but also produces dehazed object results in the same time.

Effects of connected vehicle-based variable speed limit under different foggy conditions based on simulated driving

In response to developing and/or diminishing foggy conditions, the variable speed limit application in a connected vehicle environment (CV-VSL) can estimate and deliver recommended travel speeds to individual drivers, which can help to reduce crashes when visibility conditions change. This study aims to quantify the effectiveness of the CV-VSL application by exploring drivers’ reactions to warnings (e.g., recommended travel speeds). In order to analyze the effectiveness of the CV-VSL application, a connected vehicle testing platform was established based on a driving simulator, and characteristics of the drivers’ speed adjustments after receiving warnings were analyzed with respect to different levels of visibility (i.e., no fog, slight fog, and heavy fog). This study also examined the effect of warnings on drivers in different impact zones (i.e., clear zone, transition zone, and fog zone). Three indicators were identified: 1) speed at the end of the clear zone, 2) maximum deceleration rate in the transition zone, and 3) average speed reduction in the fog zone. Throughout the experiment, the relationship between speed adjustments and the level of visibility was explored. The results indicated that the CV-VSL application is effective in making drivers reduce travel speeds in all three types of zones. Furthermore, it appeared that the CV-VSL application could help manage travel speeds prior to vehicles entering the transition zone, and influence drivers’ braking decisions upon encountering reduced visibility. It was also found that the CV-VSL application was more effective in heavy fog conditions than in light fog conditions. The connected vehicle testing platform based on the driving simulator provided a new method for evaluating the effectiveness of in-vehicle messaging generated by connected vehicle applications.

Propagation properties of sub-millimeter waves in foggy conditions

The propagation of millimeter (MMW) and submillimeter (terahertz, THz) waves in the atmosphere is subject to absorptive and dispersive effects. The resulting attenuation and temporal group delay increase in cloudy and hazy weather. In this work, the effects of water droplets suspended in the air on the propagation of electromagnetic radiation in submillimeter waves are studied theoretically and experimentally. A comparison is made between the link budget in THz frequencies and the expected attenuation for free space optics (FSO) links. Using the modified millimeter-wave propagation model, the frequency-dependent attenuation and group delay are expressed in terms of the complex refractivity of the atmospheric medium. The theory is employed to study the effect of fog and clouds on the accuracy of a frequency-modulated continuous-wave high-resolution radar operating at 330 GHz. In an experiment, the propagation of MMW was studied in a controlled fog chamber for various ranges of visibility, even below 1 m. The resulting attenuation and group delay of submillimeter waves were measured, while the properties of fog (optical visibility distance and water content) were monitored using FSO techniques. Apart from attenuation, the incremental group delay caused by fog also affected the accuracy of the radar. The experimental results were compared with those of an analytical model and were in good agreement even for very low visibility in very foggy conditions. Dispersive effects should be considered in the design of remote sensing radars operating in the MMW and THz regimes.