scholarly journals Vehicle Tracking and Counting System in Dusty Weather with Vibrating Camera Conditions

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Nastaran Yaghoobi Ershadi ◽  
José Manuel Menéndez
Keyword(s):  
Traffic Control ◽  
Gaussian Model ◽  
Weather Conditions ◽  
Surveillance Systems ◽  
Traffic Surveillance ◽  
Traffic Conditions ◽  
Detection And Tracking ◽  
Traffic Volumes ◽  
Medium Level ◽  
Bad Weather

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles are a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.) or dusty weather in arid and semiarid regions or at night, among others. In this paper, we proposed a method to track and count vehicles in dusty weather with a vibrating camera. For this purpose, we used a background subtraction based strategy mixed with extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result. Our proposed method was tested on several video surveillance records in different conditions such as in dusty or foggy weather, with a vibrating camera, and on roads with medium-level traffic volumes. The results showed that the proposed method performed better than other previously published methods, including the Kalman filter or Gaussian model, in different traffic conditions.

scholarly journals Multispectral Fusion Approach for Traffic Target Detection in Bad Weather

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 271
Author(s):  
Yajing Han ◽  
Dean Hu
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Cost Effective ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Surveillance Systems ◽  
Traffic Surveillance ◽  
Thermal Images ◽  
The Road ◽  
Bad Weather

Visual traffic surveillance using computer vision techniques can be noninvasive, automated and cost effective. Traffic surveillance systems with the ability to detect, count and classify vehicles can be employed in gathering traffic statistics and achieving better traffic control in intelligent transportation systems. This works well in daylight when the road users are clearly visible to the camera, but it often struggles when the visibility of the scene is impaired by insufficient lighting or bad weather conditions such as rain, snow, haze and fog. Therefore, in this paper, we design a dual input faster region-based convolutional neural network (RCNN) to make full use of the complementary advantages of color and thermal images to detect traffic objects in bad weather. Different from the previous detector, we used halfway fusion to fuse color and thermal images for traffic object detection. Besides, we adopt the polling from multiple layers method to adapt the characteristics of large size differences between objects of traffic targets to accurately identify targets of different sizes. The experimental results show that the present method improves the target recognition accuracy by 7.15% under normal weather conditions and 14.2% under bad weather conditions. This exhibits promising potential for implementation with real-world applications.

Delays in the Flow of Air Traffic

1948 ◽  
Vol 52 (448) ◽  
pp. 251-258 ◽  
Author(s):  
E. G. Bowen ◽  
T. Pearcey
Keyword(s):  
Traffic Control ◽  
Weather Conditions ◽  
Air Traffic ◽  
High Density ◽  
Control Methods ◽  
Distant Point ◽  
Civil Aircraft ◽  
Bad Weather

It is becoming recognised that before civil aircraft can operate at high density, the most important problem to be solved is that of traffic control. Methods exist by which a single aircraft can navigate from a distant point to an airport and let down to a safe landing under bad weather conditions. Difficulties arise when several aircraft are involved at once and long delays can occur in the neighbourhood of airports carrying high density traffic. In this paper an analysis is made of the traffic problem in an attempt to clarify some of the factors involved.

CNN-based Rain Reduction in Street View Images

2020 ◽  
Vol 2020 (1) ◽  
pp. 78-81
Author(s):  
Simone Zini ◽  
Simone Bianco ◽  
Raimondo Schettini
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
State Of The Art ◽  
Weather Conditions ◽  
Specific Interest ◽  
Optical Character ◽  
Street View ◽  
In The Wild ◽  
Bad Weather ◽  
Detection And Recognition

Rain removal from pictures taken under bad weather conditions is a challenging task that aims to improve the overall quality and visibility of a scene. The enhanced images usually constitute the input for subsequent Computer Vision tasks such as detection and classification. In this paper, we present a Convolutional Neural Network, based on the Pix2Pix model, for rain streaks removal from images, with specific interest in evaluating the results of the processing operation with respect to the Optical Character Recognition (OCR) task. In particular, we present a way to generate a rainy version of the Street View Text Dataset (R-SVTD) for "text detection and recognition" evaluation in bad weather conditions. Experimental results on this dataset show that our model is able to outperform the state of the art in terms of two commonly used image quality metrics, and that it is capable to improve the performances of an OCR model to detect and recognise text in the wild.

scholarly journals Advanced Flight Planning and the Benefit of In-Flight Aircraft Trajectory Optimization

2021 ◽  
Vol 13 (3) ◽  
pp. 1383
Author(s):  
Judith Rosenow ◽  
Martin Lindner ◽  
Joachim Scheiderer
Keyword(s):  
New York ◽  
Traffic Control ◽  
Traffic Management ◽  
Trajectory Optimization ◽  
Service Providers ◽  
Weather Conditions ◽  
Air Traffic ◽  
Weather Data ◽  
Weather Forecasts ◽  
Aircraft Trajectory

The implementation of Trajectory-Based Operations, invented by the Single European Sky Air Traffic Management Research program SESAR, enables airlines to fly along optimized waypoint-less trajectories and accordingly to significantly increase the sustainability of the air transport system in a business with increasing environmental awareness. However, unsteady weather conditions and uncertain weather forecasts might induce the necessity to re-optimize the trajectory during the flight. By considering a re-optimization of the trajectory during the flight they further support air traffic control towards achieving precise air traffic flow management and, in consequence, an increase in airspace and airport capacity. However, the re-optimization leads to an increase in the operator and controller’s task loads which must be balanced with the benefit of the re-optimization. From this follows that operators need a decision support under which circumstances and how often a trajectory re-optimization should be carried out. Local numerical weather service providers issue hourly weather forecasts for the coming hour. Such weather data sets covering three months were used to re-optimize a daily A320 flight from Seattle to New York every hour and to calculate the effects of this re-optimization on fuel consumption and deviation from the filed path. Therefore, a simulation-based trajectory optimization tool was used. Fuel savings between 0.5% and 7% per flight were achieved despite minor differences in wind speed between two consecutive weather forecasts in the order of 0.5 m s−1. The calculated lateral deviations from the filed path within 1 nautical mile were always very small. Thus, the method could be easily implemented in current flight operations. The developed performance indicators could help operators to evaluate the re-optimization and to initiate its activation as a new flight plan accordingly.

The importance of public support in the implementation of green transportation in smart cities using smart vehicle bicycle communication transport

2020 ◽  
Vol 38 (5/6) ◽  
pp. 997-1011
Author(s):  
Ning Li ◽  
Parthasarathy R. ◽  
Harshila H. Padwal
Keyword(s):  
Smart Cities ◽  
Optimization Technique ◽  
Public Support ◽  
Weather Conditions ◽  
Transport Systems ◽  
Content Type ◽  
Signaling Systems ◽  
Traffic Conditions ◽  
Green Transportation ◽  
Smart Vehicle

Purpose Smart mobility is a major guideline in the development of Smart Cities’ transport systems and management. The issue of transition into green, secure and sustainable transport modes, such as using bicycles, should be implemented in this case, along with the subjectivism of management. Design/methodology/approach The proposed technology reflects the Smart Bicycle vehicle model, which tracks cyclists and weather conditions and turns to electric motors in critical circumstances. Findings This reduces the physical load and battery consumption of cyclists which affects the Smart Cities’ ecology positively. Originality/value In Smart Vehicle Bicycle Communication Transport, the vehicle movement optimization technique is used for traffic scenarios to analyze traffic signaling systems that give better results in variable and dense traffic conditions.

Weather effects on intrahabitat movements of the western green lizard, Lacerta bilineata (Daudin, 1802), at its northern distribution range border: a radio-tracking study

2000 ◽  
Vol 78 (10) ◽  
pp. 1831-1839 ◽  
Author(s):  
P Sound ◽  
M Veith
Keyword(s):  
Activity Patterns ◽  
Strong Dependence ◽  
Weather Conditions ◽  
Distribution Range ◽  
Maximum Temperature ◽  
Second Phase ◽  
Northern Distribution ◽  
Radio Transmitters ◽  
Movement Parameters ◽  
Bad Weather

Daily activity patterns of male western green lizards, Lacerta bilineata (Daudin, 1802), at the edge of their northern distribution range in western Germany after the breeding season from June to October were recorded using implanted radio transmitters. Different activity indices discriminating between stimulation, duration, and length of movement were correlated with actual weather conditions (d0) and with weather conditions on the 2 previous days (d-1 and d-2). The lizards' dependence on weather showed two different phases throughout the study period. During the first period and in the period preceding a drastic change of weather in midsummer, weather had no significant influence on movement parameters. After that event, temperatures dropped and a strong dependence on weather of all movement parameters except those indicating displacements became apparent. Thresholds for 50% activity during this second phase were a maximum temperature of 17°C and a minimum humidity of 35%. Two days after periods of bad weather, the influence of weather conditions increased again. This can be explained by physiological deficits that require compensation during the period of marginal weather conditions prior to hibernation. Displacement movements were significantly longer than home-range movements and were neither triggered nor modulated by the weather. They must therefore represent activities such as patrolling territory boundaries.

Short-term scheduling problem in smart grid considering reliability improvement in bad weather conditions

2017 ◽  
Vol 11 (10) ◽  
pp. 2521-2533 ◽  
Author(s):  
Babak Yousefi-khangah ◽  
Saeid Ghassemzadeh ◽  
Seyed Hossein Hosseini ◽  
Behnam Mohammadi-Ivatloo
Keyword(s):  
Smart Grid ◽  
Weather Conditions ◽  
Scheduling Problem ◽  
Short Term ◽  
Reliability Improvement ◽  
Bad Weather

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

scholarly journals Risk Analysis and Management of Moored Ships in Ports

2018 ◽  
Author(s):  
Liliana V. Pinheiro ◽  
Conceição J. E. M. Fortes ◽  
João A. Santos
Keyword(s):  
Integrated Management ◽  
Warning System ◽  
Weather Conditions ◽  
Complete Information ◽  
Decision Makers ◽  
Modular System ◽  
Economic Losses ◽  
Sea Waves ◽  
Bad Weather ◽  
Port Areas

The risks associated with mooring of ships are a major concern for port and maritime authorities. Sea waves and extreme weather conditions can lead to excessive movements of vessels and mooring loads affecting the safety of ships, cargo, passengers, crew or port infrastructures. Normally, port activities such as ships’ approach manoeuvres and loading/unloading operations, are conditioned or suspended based solely on weather or wave forecasts, causing large economic losses. Nevertheless, it has been shown that some of the most hazardous events with moored ships happen on days with mild sea and wind conditions, being the culprit long waves and resonance phenomena. Bad weather conditions can be managed with an appropriate or reinforced mooring arrangement. A correct risk assessment must be based on the movements of the ship and on the mooring loads, taking into account all the moored ship’s system. In this paper, the development of a forecast and warning system based on the assessment of risks associated with moored ships in port areas, SWAMS ALERT, is detailed. This modular system can be scaled and adapted to any port, providing decision-makers with accurate and complete information on the behaviour of moored ships, movements and mooring loads, allowing a better planning and integrated management of port areas.

scholarly journals Sugarcane stems as larval habitat for the stable fly (Stomoxys calcitrans) in sugarcane plantations

2013 ◽  
Vol 33 (6) ◽  
pp. 741-744 ◽  
Author(s):  
Paulo H.D. Cançado ◽  
Taciany Ferreira ◽  
Eliane M. Piranda ◽  
Cleber O. Soares
Keyword(s):  
Primary Source ◽  
Weather Conditions ◽  
Larval Habitat ◽  
Stomoxys Calcitrans ◽  
Stable Fly ◽  
Mato Grosso ◽  
Larval Habitats ◽  
Control Programs ◽  
Bad Weather ◽  
Mato Grosso Do Sul

Outbreaks of stable fly, Stomoxys calcitrans, cause losses for livestock producers located near sugarcane mills in Brazil, especially in southern Mato Grosso do Sul. The sugarcane mills are often pointed by local farmers as the primary source of these outbreaks; some mills also joined the farmers in combating the flies. Brazilian beef cattle production has great economic importance in similar level to bio-fuel production as ethanol. In this context, the wide-ranging knowledge on the biology and ecology of the stable fly, including larval habitats and their reproduction sites is extremely important for further development of control programs. This paper aims to report the occurrence and development of S. calcitrans larvae inside sugarcane stems in three municipalities of Mato Grosso do Sul. The sugarcane stems give protection against bad weather conditions and insecticide application. In this way, for sustainable sugarcane growth specific research concerning this situation should be conducted.

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