Adverse Weather Situations Research Articles

E-suite for Soldiers based on Photovoltaic Cells

We are urgently attempting to power the technology that surround us with clean energy. However, It never occurs to me to make bulletproof coats intelligent. In addition to a basic Kevlar vest, soldiers who defend our nation should receive an E-Uniform that operates on sustainable energy. This study article suggests such a uniform. The attire improves a soldier's ability to withstand extremes of temperature in adverse weather situations. It has a solar panel installed that charges the battery. The necessary heating and cooling effect is provided by the mounted Peltier plate. Additionally, the soldier's clothing incorporates GPS to track their precise location and GSM to make touch with them. Additionally, it has a metal detector to locate metal objects like bombs and is naturally camouflaged. Keywords—Kevlar, Peltier plate, GPS, GSM, Metal Detector,Camouflage..

Innovative Integration of Severe Weather Forecasts into an Extended Arrival Manager

In the H2020 project “Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM” (SINOPTICA), an air traffic controller support system was extended to organize approaching traffic even under severe weather conditions. During project runtime, traffic days with extreme weather events in the Po Valley were analyzed, an arrival manager was extended with a module for 4D diversion trajectory calculation, two display variants for severe weather conditions in an air traffic controller primary display were developed, and the airport Milano Malpensa was modelled for an air traffic simulation. On the meteorological side, three new forecasting techniques were developed to better nowcast weather events affecting tactical air traffic operations and used to automatically organize arrival traffic. Additionally, short-range weather forecasts with high spatial resolution were elaborated using radar-based nowcasting and a numerical weather prediction model with data assimilation. This nowcast information was integrated into the extended arrival manager for the sequencing and guiding of approaching aircraft even in adverse weather situations. The combination of fast and reliable weather nowcasts with a guidance support system enables severe weather diversion coordination in combination with a visualization of its dynamics on traffic situation displays.

Data Augmentation of Automotive LIDAR Point Clouds under Adverse Weather Situations.

In contrast to previous works on data augmentation using LIDAR (Light Detection and Ranging), which mostly consider point clouds under good weather conditions, this paper uses point clouds which are affected by spray. Spray water can be a cause of phantom braking and understanding how to handle the extra detections caused by it is an important step in the development of ADAS (Advanced Driver Assistance Systems)/AV (Autonomous Vehicles) functions. The extra detections caused by spray cannot be safely removed without considering cases in which real solid objects may be present in the same region in which the detections caused by spray take place. As collecting real examples would be extremely difficult, the use of synthetic data is proposed. Real scenes are reconstructed virtually with an added extra object in the spray region, in a way that the detections caused by this obstacle match the characteristics a real object in the same position would have regarding intensity, echo number and occlusion. The detections generated by the obstacle are then used to augment the real data, obtaining, after occlusion effects are added, a good approximation of the desired training data. This data is used to train a classifier achieving an average F-Score of 92. The performance of the classifier is analyzed in detail based on the characteristics of the synthetic object: size, position, reflection, duration. The proposed method can be easily expanded to different kinds of obstacles and classifier types.

Assessing the Contribution of Data Mining Methods to Avoid Aircraft Run-Off from the Runway to Increase the Safety and Reduce the Negative Environmental Impacts.

The Single Europe Sky Air Traffic Management Research (SESAR) program develops and implements innovative technological and operational solutions to modernize European air traffic management and to eliminate the negative environmental impacts of aviation activity. This article presents our developments within the SESAR Solution “Safety Support Tools for Avoiding Runway Excursions”. This SESAR Solution aims to mitigate the risk of runway excursion, to optimize airport operation management by decreasing the number of runway inspections, to make chemical treatment effective with respect to the environment, and to increase resilience, efficiency and safety in adverse weather situations. The proposed approach is based on the enhancement of runway surface condition awareness by integrating data from various sources. Dangerous windy conditions based on Lidar measurements are also discussed as another relevant factor in relation to runway excursions. The paper aims to explore four different data mining methods to obtain runway conditions from the available input data sources, examines their performance and discusses their pros and cons in comparison with a rule-based algorithm approach. The output of the SESAR Solution is developed in compliance with the new Global Reporting Format of the International Civil Aviation Organization for runway condition description to be valid from 2020. This standard is expected to provide concerned stakeholders with more precise information to enhance flight safety and environmental protection.

Attribute non-attendance in choosing the bike as a transport mode in Belgium

Cycling is an important pillar of the global endeavor to have a more sustainable transportation system. Many papers have studied how trip and person characteristics affect selecting the bike as a transport mode but unlike other researchers, we model the probability of cycling using a binary item response model where the choice is modelled as a trade-off between the individuals' tendency to cycle and the threshold related to each cycling situation.
 We distinguish between frequent and occasional cyclists. The results show that occasional cyclists are more affected by adverse weather situations, darkness, and uphill slopes. Contrary to the previous studies, a separate bike path turned out a stronger motivator for the group of frequent cyclists.
 The model fit can substantially be improved by accounting for attribute non-attendance. The results show that weather and wind speed have the highest probability to be taken into account, and the bike path had the lowest probability of being considered by the respondents.
 Employing the attribute non-attendance model made it possible to make accurate and trustworthy conclusions about the attributes by focusing on the people who take into account the attributes. More specifically, it was found that the presence of a separate bike path and a 100% asphalt route can increase the average probability of taking the bike by up to 55 and 40 percentage points, respectively.

Forecasting Adverse Weather Situations in the Road Network

Weather is an important factor that affects traffic flow and road safety. Adverse weather situations affect the driving conditions directly; hence, drivers must be informed about the weather conditions downstream to adapt their driving. In the framework of intelligent transport systems, several systems have been developed to know the weather situations and inform drivers. However, these systems do not forecast weather in advance, and they need the support of road operators to inform drivers. This paper presents a new autonomous system to forecast weather conditions in a short time and to give users the information obtained. The system uses a set of algorithms and rules to determine the weather and to forecast dangerous situations on the road network. It has been implemented using a multiagent approach and tested with real data. Results are very promising. The system is able to forecast adverse situations with a high degree of quality. This quality makes it possible to trust in the system and to avoid the supervision of operators.

On the identification of weather avoidance routes in the terminal maneuvering area of Hong Kong International Airport

The safety and efficiency of air traffic are significantly affected by adverse weather. This holds especially in terminal maneuvering areas (TMA) where, in addition to the impact of weather itself, potential weather avoidance routes are strongly restricted by air traffic regulations. A weather avoidance model DIVMET has been developed which proposes a route through a field of developing thunderstorms. Air traffic control regulations have not been included in it at this stage. DIVMET was applied to the TMA of Hong Kong International Airport as air traffic control (ATC) there has become interested in improving the controller’s work load, especially for managing incoming traffic by avoidance route simulations. Although visual inspection of simulated avoidance routes by ATC was satisfactory, a quantitative validation of simulated with real observed routes was also carried out. Two real adverse weather situations with thunderstorms within the TMA of Hong Kong and with heavily distorted traffic were chosen. The main objective prior to any validation, however, was to identify routes which are solely impacted by weather but do not show any signs of regulation. Route selection was done on the base of flight position data. Landing flights were selected and deviations from standard approach routes were analyzed. As a result, the majority of 272 flights were found to be affected by both weather and regulations (60%), highlighting the challenge for air traffic controllers to manage landing traffic under adverse weather conditions safely and efficiently. Only a few weather-affected flights (7%) were not regulated and could be used for validation. DIVMET simulation routes were presented to local air traffic controllers who confirmed them as potential and realistic avoidance routes. DIVMET weather avoidance route simulations within a TMA appear to be helpful but further model development has to incorporate traffic regulations, to include holdings, short-cuts, and slow-downs.

Usage of Road Weather Sensors for Automatic Traffic Control on Motorways

Within section control systems on motorways drivers get information about adequate speed limits during adverse weather situations. Therefore road weather data are necessary. To detect the danger of aqua-planning measurements of precipitation intensity and waterfilm thickness as well as the status of the road surface are needed. To detect these atmospheric data different weather sensors are located near the motorway. There are two different sensor systems available which detect these measurements at the moment. For the detection of the status of the road surface, like dry, moist or wet, the sensor is imbedded directly in the road surface in most cases. The other sensor system is non-invasive which can be installed next to or over the road. Nowadays more and more open-pored asphalt is used because of its advantage to be less noisy and its property to drain off water better than normal asphalt. But this kind of asphalt cannot be cut to install a road sensor therefore the usage of non-invasive sensors will be increase in the future. This may also lead to different thresholds in automatic traffic control during adverse weather situations.The measurements of waterfilm thickness, road surface and road temperature are very important for automatic traffic control algorithms [2] as a speed limit caused by rain is derived and shown on variable message signs. In the German Technical Bulletin [2] a matrix with the two measurements precipitation intensity and water film thickness define which wetness-level is detected. There are 5 wetness-levels which cause different speed limits. For the first supply thresholds are given based on the experiences with road sensors. For the newer non-invasive sensors other thresholds may be necessary. This paper will show some possible thresholds for the precipitation/waterfilm thickness matrix and their effects on the speed limits shown on the variable massage signs.Within the German Test Site for Road Weather Stations [1] various road sensors as well as various non-invasive sensors are installed. The data for both detection technologies has been collected for the last 2 years and allows a statistically valid comparison of them. In this paper the advantage and disadvantage of the two sensor technologies will be shown for the measurements waterfilm thickness, road surface and road temperature. In order to describe the behavior of the sensors, the available data will be analyzed concerning the availability of valid datasets and the accuracy. Additionally the performance of the sensors is examined during periods of different clusters of traffic volumes.

Agent-based test-bed for road information systems

Road safety is one of the most important concerns of road authorities. In order to improve road safety, traffic managers develop traffic management and control strategies. The use of advanced traffic management systems is to support road managers in daily traffic management tasks. However, it is important to test in advance, the traffic strategies to evaluate the results and their suitability to the current situation. In this study, a test-bed based on multi-agent is presented. The purpose of this test-bed is to be able to test several traffic information strategies in case of adverse weather situations. It consists in a knowledge model implemented by a set of basic agents. These agents are easily configurable and extensible to aid in-depth research in this field. The test includes agents to control variable message signal, weather stations, data collection stations etc. The test-bed interface is based on Google maps providing a realistic environment that facilitates the implementation of the tested strategies in the real world.

A multi-agent system for managing adverse weather situations on the road network

The development of traffic management and control strategies to improve traffic flows and road safety is necessary due to the high dynamism of traffic flows. The use of distributed intelligent systems can help the traffic organizations and the road o