Off-axis propagation of a laser beam in low visibility weather conditions

1980 ◽  
Vol 19 (16) ◽  
pp. 2822 ◽  
Author(s):  
W. G. Tam ◽  
A. Zardecki
Keyword(s):  
Laser Beam ◽  
Weather Conditions ◽  
Low Visibility

scholarly journals Vehicle Collision Prediction under Reduced Visibility Conditions

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3026 ◽  
Author(s):  
Keng-Pin Chen ◽  
Pao-Ann Hsiung
Keyword(s):  
Communication Systems ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Collision Probability ◽  
Percentage Error ◽  
Collision Warning ◽  
Congested Traffic ◽  
Prediction Horizon ◽  
Low Visibility ◽  
Velocity Prediction

Rear-end collisions often cause serious traffic accidents. Conventionally, in intelligent transportation systems (ITS), radar collision warning methods are highly accurate in determining the inter-vehicle distance via detecting the rear-end of a vehicle; however, in poor weather conditions such as fog, rain, or snow, the accuracy is significantly affected. In recent years, the advent of Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems has introduced new methods for solving the rear-end collision problem. Nevertheless, there is still much left for improvement. For instance, weather conditions have an impact on human-related factors such as response time. To address the issue of collision detection under low visibility conditions, we propose a Visibility-based Collision Warning System (ViCoWS) design that includes four models for prediction horizon estimation, velocity prediction, headway distance prediction, and rear-end collision warning. Based on the history of velocity data, future velocity volumes are predicted. Then, the prediction horizon (number of future time slots to consider) is estimated corresponding to different weather conditions. ViCoWs can respond in real-time to weather conditions with correct collision avoidance warnings. Experiment results show that the mean absolute percentage error of our velocity prediction model is less than 11%. For non-congested traffic under heavy fog (very low visibility of 120 m), ViCoWS warns a driver by as much as 4.5 s prior to a possible future collision. If the fog is medium with a low visibility of 160 m, ViCoWs can give warnings by about 2.1 s prior to a possible future collision. In contrast, the Forward Collision Probability Index (FCPI) method gives warnings by only about 0.6 s before a future collision. For congested traffic under low visibility conditions, ViCoWS can warn a driver by about 1.9 s prior to a possible future collision. In this case, the FCPI method gives 1.2 s for the driver to react before collision.

scholarly journals Empirical analysis of extreme weather conditions and aviation safety in Nigeria

2016 ◽  
Vol 9 (6) ◽  
pp. 680-690
Author(s):  
C.O. Akanni ◽  
A.M. Hassan ◽  
T.C. Osuji
Keyword(s):  
Traffic Accidents ◽  
Weather Condition ◽  
Secondary Data ◽  
Weather Conditions ◽  
Aviation Safety ◽  
Extreme Weather ◽  
Aviation Industry ◽  
A Value ◽  
Low Visibility ◽  
Safety Accident

The frequency of delay, diversion and outright cancellation occasioned by poor weather has affected the Nigerian aviation industry and serious safety implication.This study therefore examines the influence of weather conditions on aviation safety in Nigeria. Secondary data basically from Nigeria Meteorological Agency such as information on thunderstorm, fog occurrence and rainfall from 2004 to 2013 and data obtained from Federal Airport Authority of Nigeria on air accident induced by extreme weather within the same period were analysed using Multiple Regression Analysis. Results show that low visibility as a result of fog occurrence causes four (4) air traffic accidents more than other weather conditions and that Lagos experienced two (2) air accidents more than other airports during the period under study.  So also the value of R2 shows a value of 77.8% which implies that there is variation in the dependent variable (Airport Operation) which can be predicted by independent variables (Weather conditions). The F-statistic value of 62.892 is also found to be statistically significant at 5% (p<0.05) which shows that weather condition has significant influence on aviation safety. Baseline studies on flight operation, government intervention in aviation industry, maintenance culture were recommended.Keywords: Fog, Thunderstorm, Rainfall, Safety, Accident

scholarly journals Biomass Burning Aerosols and the Low Visibility Events in Southeast Asia

2016 ◽  
Author(s):  
Hsiang-He Lee ◽  
Rotem Z. Bar-Or ◽  
Chien Wang
Keyword(s):  
Particulate Matter ◽  
Southeast Asia ◽  
Biomass Burning ◽  
Wrf Model ◽  
Weather Conditions ◽  
General Situation ◽  
Kuala Lumpur ◽  
The Past ◽  
Low Visibility ◽  
Aerosol Module

Abstract. Fires including peatland burning in Southeast Asia have become a major concern of general public as well as governments in the region. This is because that aerosols emitted from such fires can cause persistent haze events under favorite weather conditions in downwind locations, degrading visibility and causing human health issues. In order to improve our understanding of the spatial-temporal coverage and influence of biomass burning aerosols in Southeast Asia, we have used surface visibility and particulate matter concentration observations, added by decadal long (2002 to 2014) simulations using the Weather Research and Forecasting (WRF) model with a fire aerosol module, driven by high-resolution biomass burning emission inventories. We find that in the past decade, fire aerosols are responsible for nearly all the events with very low visibility (< 7 km), and a substantial fraction of the low visibility events (visibility < 10 km) in the major metropolitan areas of Southeast Asia: 38 % in Bangkok, 35 % in Kuala Lumpur, and 34 % in Singapore. Biomass burnings in Mainland Southeast Asia account for the largest contributor to total fire produced PM2.5 in Bangkok (99.1 %), while biomass burning in Sumatra is the major contributor to fire produced PM2.5 in Kuala Lumpur (49 %) and Singapore (41 %). To examine the general situation across the region, we have further defined and derived a new integrated metric for 50 cities of the Association of Southeast Asian Nations, i.e., Haze Exposure Days (HEDs) that measures the annual exposure days of these cities to low visibility (< 10 km) caused by particulate matter pollution. It is shown that HEDs have increased steadily in the past decade across cities with both high and low populations. Fire events are found to be responsible for about half of the total HEDs. Therefore, our result suggests that in order to improve the overall air quality in Southeast Asia, mitigation policies targeting at both biomass and fossil fuel burning sources need to be put in effect.

The Practical Use of Radio as a Direct Aid to the Landing Approach in Conditions of Low Visibility

1938 ◽  
Vol 42 (330) ◽  
pp. 483-511
Author(s):  
R. S. Blucke
Keyword(s):  
Weather Conditions ◽  
Practical Work ◽  
High Tension ◽  
Low Visibility

The problem of landing an aeroplane under conditions of low visibility has been a subject for speculation for the last twenty years, but it is only within the last ten years that it has been given any serious practical attention. This practical attention has been forced by the necessity for aircraft to maintain schedule regardless of weather conditions in competition with other forms of transport.Although certain schemes involving radio were amongst the earliest proposals for a solution of the problem, the first practical work appears to have been concerned with methods of a more mechanical or optical nature, including a proposal to deposit the fog by high tension discharge.

scholarly journals Vision-Based Safety-Related Sensors in Low Visibility by Fog

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2812
Author(s):  
Bong Keun Kim ◽  
Yasushi Sumi
Keyword(s):  
Weather Conditions ◽  
Outdoor Environment ◽  
Service Robots ◽  
Mobile Service ◽  
Light Sources ◽  
Functional Safety ◽  
Safety Function ◽  
Low Visibility ◽  
And Control ◽  
Measurement And Control

Mobile service robots are expanding their use to outdoor areas affected by various weather conditions, but the outdoor environment directly affects the functional safety of robots implemented by vision-based safety-related sensors (SRSs). Therefore, this paper aims to set the fog as the environmental condition of the robot and to understand the relationship between the quantified value of the environmental conditions and the functional safety performance of the robot. To this end, the safety functions of the robot built using SRS and the requirements for the outdoor environment affecting them are described first. The method of controlling visibility for evaluating the safety function of SRS is described through the measurement and control of visibility, a quantitative means of expressing the concentration of fog, and wavelength analysis of various SRS light sources. Finally, object recognition experiments using vision-based SRS for robots are conducted at low visibility. Through this, it is verified that the proposed method is a specific and effective method for verifying the functional safety of the robot using the vision-based SRS, for low visibility environmental requirements.

scholarly journals Atmospheric Error Correction of the Laser Beam Ranging

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
J. Saydi ◽  
A. Lotfalian ◽  
M. Abedi ◽  
J. Khalilzadeh ◽  
H. Saghafifar
Keyword(s):  
Laser Beam ◽  
Meteorological Data ◽  
Atmospheric Correction ◽  
Weather Conditions ◽  
Emission Angle ◽  
Laser Ranging ◽  
Atmospheric Effects ◽  
Atmospheric Models ◽  
Ranging Error ◽  
Surface Measurements

Atmospheric models based on surface measurements of pressure, temperature, and relative humidity have been used to increase the laser ranging accuracy by ray tracing. Atmospheric refraction can cause significant errors in laser ranging systems. Through the present research, the atmospheric effects on the laser beam were investigated by using the principles of laser ranging. Atmospheric correction was calculated for 0.532, 1.3, and 10.6 micron wavelengths through the weather conditions of Tehran, Isfahan, and Bushehr in Iran since March 2012 to March 2013. Through the present research the atmospheric correction was computed for meteorological data in base of monthly mean. Of course, the meteorological data were received from meteorological stations in Tehran, Isfahan, and Bushehr. Atmospheric correction was calculated for 11, 100, and 200 kilometers laser beam propagations under 30°, 60°, and 90° rising angles for each propagation. The results of the study showed that in the same months and beam emission angles, the atmospheric correction was most accurate for 10.6 micron wavelength. The laser ranging error was decreased by increasing the laser emission angle. The atmospheric correction with two Marini-Murray and Mendes-Pavlis models for 0.532 nm was compared.

scholarly journals A Study on Training Data Selection for Object Detection in Nighttime Traffic Scenes

2020 ◽  
Vol 2020 (16) ◽  
pp. 203-1-203-6
Author(s):  
Astrid Unger ◽  
Margrit Gelautz ◽  
Florian Seitner
Keyword(s):  
Object Detection ◽  
Weather Conditions ◽  
Training Data ◽  
Data Selection ◽  
Training Dataset ◽  
Detection Algorithms ◽  
Low Visibility ◽  
Selection For ◽  
Training Data Selection ◽  
Selection Of

With the growing demand for robust object detection algorithms in self-driving systems, it is important to consider the varying lighting and weather conditions in which cars operate all year round. The goal of our work is to gain a deeper understanding of meaningful strategies for selecting and merging training data from currently available databases and self-annotated videos in the context of automotive night scenes. We retrain an existing Convolutional Neural Network (YOLOv3) to study the influence of different training dataset combinations on the final object detection results in nighttime and low-visibility traffic scenes. Our evaluation shows that a suitable selection of training data from the GTSRD, VIPER, and BDD databases in conjunction with selfrecorded night scenes can achieve an mAP of 63,5% for ten object classes, which is an improvement of 16,7% when compared to the performance of the original YOLOv3 network on the same test set.

scholarly journals Ingenious vehicular system to evade collisions

2017 ◽  
Vol 7 (1.2) ◽  
pp. 53
Author(s):  
R. Sridhar ◽  
Aditya Nema ◽  
Anshul Nalin ◽  
Ankur Rai
Keyword(s):  
Situational Awareness ◽  
Weather Conditions ◽  
Model Design ◽  
Test Results ◽  
Extrinsic Information ◽  
Wireless Broadcast ◽  
Pilot Model ◽  
Low Visibility ◽  
Vehicle To Infrastructure ◽  
Indication System

Driver’s response is indispensable in the aversion of collisions and in stringent circumstances. WiB-IVS (Wireless Broadcast Intelligent Vehicular System) is a proposed design for Intelligent Vehicular Systems enabling Vehicle to Infrastructure (V2I) communication for effectuating an interconnected network of vehicles for easier and faster information sharing in order to prevent collisions. The system centralizes on driver’s response and thus aims to bring extrinsic information to the driver, stimulating situational awareness. An indication system fulfils this purpose and helps the driver respond to the scenario ahead. Information transmission is facilitated by communication between vehicle and broadcasting station based on User Datagram Protocol (UDP). The design approach caters to the problems of the collision at sharp or blind turns, offsite intersections and those occurring due to low visibility in extreme weather conditions such as fog. A pilot model design to test for the effectiveness of the proposed system architecture is also put forth in this paper. The pilot test results confirm the system’s rapid response and its key potential for the future.

scholarly journals Real-Time Tunnel Deformation Monitoring Technology Based on Laser and Machine Vision

2018 ◽  
Vol 8 (12) ◽  
pp. 2579 ◽  
Author(s):  
Zurong Qiu ◽  
Haopeng Li ◽  
Wenchuan Hu ◽  
Chenglin Wang ◽  
Jiachen Liu ◽  
...  
Keyword(s):  
Machine Vision ◽  
Laser Beam ◽  
Real Time ◽  
Measurement Errors ◽  
Detection System ◽  
Deformation Monitoring ◽  
Interest Points ◽  
Real Time System ◽  
Deformation Velocity ◽  
Low Visibility

Structural health monitoring is a topic of great concern in the world, and tunnel deformation monitoring is one of the important tasks. With the rapid developments in tunnel traffic infrastructure construction, engineers need a portable and real-time system to obtain the tunnel deformation during construction. This paper reports a novel method based on laser and machine vision to automatically measure tunnel deformation of multiple interest points in real time and effectively compensate for the environment vibration, and moreover it can overcome the influence of a dusty and dark tunnel environment in low visibility. An automatic and wireless real-time tunnel deformation monitoring system, which is based on laser and machine vision and can give early warnings for tunnel collapse accidents, is proposed. The proposed system uses a fixed laser beam as a monitoring reference. The image acquisition modules mounted on the measured points receive the laser spots and measure the tunnel accumulative deformation and instantaneous deformation velocity. Compensation methods are proposed to reduce measurement errors caused by laser beam feasibility, temperature, air refraction index, and wireless antenna attitude. The feasibility of the system is verified through tunnel tests. The accuracy of the detection system is better than 0.12 mm, the repeatability is less than 0.11 mm, and the minimum resolution is 10 μm; therefore, the proposed system is very suitable for real-time and automatic detection of tunnel deformation in low visibility during construction.

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