The Impact of Adverse Weather Conditions on Autonomous Vehicles: How Rain, Snow, Fog, and Hail Affect the Performance of a Self-Driving Car

2019 ◽  
Vol 14 (2) ◽  
pp. 103-111 ◽  
Author(s):  
Shizhe Zang ◽  
Ming Ding ◽  
David Smith ◽  
Paul Tyler ◽  
Thierry Rakotoarivelo ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
The Impact

scholarly journals Influence of Overheating Phenomenon on Bitumen and Asphalt Mixture Properties

Materials ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 610 ◽  
Author(s):  
Michał Sarnowski ◽  
Karol Kowalski ◽  
Jan Król ◽  
Piotr Radziszewski
Keyword(s):  
Asphalt Mixture ◽  
Fatigue Cracking ◽  
Weather Conditions ◽  
Asphalt Mixtures ◽  
Heating Process ◽  
Test Results ◽  
Adverse Weather Conditions ◽  
Loss Of Resistance ◽  
Adverse Weather ◽  
The Impact

In the course of manufacturing, transport and installation, road bitumens and asphalt mixtures can be exposed to the impact of elevated process temperatures exceeding 240 °C. This mainly applies to the mixtures used for road pavements and bridge deck insulation during adverse weather conditions. The heating process should not change the basic and rheological properties of binders and the asphalt mixtures that to a degree cause the degradation of asphalt pavement durability. The work involved analyzing the properties of non-modified bitumens and SBS polymer modified bitumens, heated at temperatures of 200 °C, 250 °C and 300 °C for 1 h. Next, the asphalt mixtures were heated in the same temperatures. Based on the developed Overheating Degradation Index (ODI) it was demonstrated that polymer-modified bitumens were characterized by higher overheating sensitivity A(ODI) than non-modified bitumens, which was confirmed by mixture test results. Overheating limit temperatures T(ODI) were determined, which in the case of polymer-modified bitumens are up to 20 °C lower than for non-modified bitumens. When the temperature increases above T(ODI), loss of viscoelastic properties occurs in the material which causes, among other effects, a loss of resistance to fatigue cracking.

Impact of Variable Speed Limit in a Connected Vehicle Environment on Truck Driver Behavior under Adverse Weather Conditions: Driving Simulator Study

2019 ◽  
Vol 2673 (7) ◽  
pp. 132-142 ◽  
Author(s):  
Guangchuan Yang ◽  
Mohamed M. Ahmed ◽  
Sherif Gaweesh
Keyword(s):  
Driving Simulator ◽  
Weather Conditions ◽  
Truck Drivers ◽  
Connected Vehicle ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Advisory Speed ◽  
The Impact

In 2015, the U.S. Department of Transportation (U.S. DOT) selected Wyoming as one of three sites to develop, test, and deploy a suite of connected vehicle (CV) applications on a 402-mi Interstate 80 corridor. One of the Wyoming’s key CV applications is the variable speed limit (VSL) warning, which aimed to provide commercial truck drivers with real-time regulatory and advisory speed limits to help in better managing speeds under adverse weather conditions, and reducing potential speed variances that may cause traffic collisions. This paper developed a driving simulator testbed to assess the impact of the Wyoming’s CV-based VSL (CV-VSL) application on truck drivers’ behavior under adverse weather conditions. A total of 18 professional truck drivers were recruited to participate in the driving simulator experiment. Participants’ instantaneous speeds at various locations were collected to reveal the impact of the CV-VSL warnings on their driving behavior. Simulation results showed that when the advisory speed limits were lower than 55 mph, participants generally followed the VSLs displayed on the CV human–machine interface (HMI). In addition, traffic flows utilizing CV-VSL technology tend to exhibit lower average speeds and speed variances compared with baseline scenarios. These effects of CV-VSL warnings can bring potential safety benefits, as reduction in average speeds and speed variances are effective surrogate measures of safety, that is, lower risk of crashes, under adverse weather conditions.

scholarly journals Nie tylko „generał Mróz ” wpływ czynników pogodowych na przebieg kampanii rosyjskiej Napoleona na wybranych przykładach

2020 ◽  
Author(s):  
Dawid Gralik
Keyword(s):  
Drinking Water ◽  
Weather Conditions ◽  
Cold Winter ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
The Impact ◽  
Intense Heat

Napoleon’s Russian campaigns one of the best known examples of the impact of weather conditions on the process of military actions. In the article, on selected examples, the influence of weather on the actions and condition of both armies, mainly the Great Army, is analyzed. Adverse weather conditions accompanied the 1812 warfare from the very beginning in the form of a storm that took place at the turn of June and July. Then a period of intense heat began, which caused considerable problems for the soldiers moving in fast marches, who were also deprived of access to drinking water. Finally, the extremely cold winter, even for Russia’s climate, contributed, however not always directly, to deaths of many soldiers on both sides of conflict. Although weather is difficult to see as the main cause of Napoleon’s defeat, it was an extremely important part of 1812 military actions.

scholarly journals Pogodowe uwarunkowania działań wojennych. Wpływ warunków atmosferycznych na przebieg starć i kampanii militarnych w okresie średniowiecza. Wybrane przykłady

2020 ◽  
Author(s):  
Andrzej Niewiński
Keyword(s):  
Disease Outbreaks ◽  
Temperature Fluctuations ◽  
Weather Conditions ◽  
Military Operation ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Medieval Chronicles ◽  
Military Campaigns ◽  
Bad Weather ◽  
The Impact

The article examines the impact of adverse weather conditions and astronomical occurrences on the outcome of the selected medieval military campaigns and pitch battles. Unpredictability of weather was an important factor in medieval warfare: unexpected wind, rain, snow, heat or day-to-night temperature fluctuations could influence a military operation in a significant way. As medieval chronicles recorded, troops often suffered from famine as a result of excessive rains, droughts or adverse winds which prevented supplies from being delivered by sea. Apart from causing fatigue and exhaustion bad weather contributed to disease outbreaks and equipment damage. People were weakened physically and psychologically which reduced their fighting ability.

A Weather Index for Analysing Grain Yield Instability in China, 1952–81

1984 ◽  
Vol 97 ◽  
pp. 68-83 ◽  
Author(s):  
Y. Y. Kueh
Keyword(s):  
Grain Yield ◽  
Weather Conditions ◽  
Water Control ◽  
Weather Impact ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Regression Techniques ◽  
Long Term Trends ◽  
The Impact

This article applies standard regression techniques to examine the impact of adverse weather conditions on average grain yield per sown hectare in contemporary China. By isolating the weather impact I hope (a) to quantify the possible influence of frequent policy and organizational changes which have been so characteristic of Chinese agriculture since 1949; and (b) to show to what extent grain production in China has become more “weather-proof” after three decades of massive investment in water control and other modern inputs. I shall deal mainly with the long-term trends from 1952 to 1981, with special reference to the extraordinary 1959–61 period, during which total grain output and yield declined by an average of 21 and 12 per cent respectively (or 25 and 18 per cent for the two trough years of 1960 and 1961), measured against the benchmark year of 1957.

scholarly journals Application of Kalman Filter to Improve 3D LiDAR Signals of Autonomous Vehicles in Adverse Weather

2021 ◽  
Vol 11 (7) ◽  
pp. 3018
Author(s):  
Shih-Lin Lin ◽  
Bing-Han Wu
Keyword(s):  
Kalman Filter ◽  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Autonomous Vehicle ◽  
Weather Conditions ◽  
Weather Data ◽  
Stereo Images ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
On The Road

A worldwide increase in the number of vehicles on the road has led to an increase in the frequency of serious traffic accidents, causing loss of life and property. Autonomous vehicles could be part of the solution, but their safe operation is dependent on the onboard LiDAR (light detection and ranging) systems used for the detection of the environment outside the vehicle. Unfortunately, problems with the application of LiDAR in autonomous vehicles remain, for example, the weakening of the echo detection capability in adverse weather conditions. The signal is also affected, even drowned out, by sensory noise outside the vehicles, and the problem can become so severe that the autonomous vehicle cannot move. Clearly, the accuracy of the stereo images sensed by the LiDAR must be improved. In this study, we developed a method to improve the acquisition of LiDAR data in adverse weather by using a combination of a Kalman filter and nearby point cloud denoising. The overall LiDAR framework was tested in experiments in a space 2 m in length and width and 0.6 m high. Normal weather and three kinds of adverse weather conditions (rain, thick smoke, and rain and thick smoke) were simulated. The results show that this system can be used to recover normal weather data from data measured by LiDAR even in adverse weather conditions. The results showed an effective improvement of 10% to 30% in the LiDAR stereo images. This method can be developed and widely applied in the future.

Effective Range Assessment of Lidar Imaging Systems for Autonomous Vehicles Under Adverse Weather Conditions with Stationary Vehicles

2021 ◽  
Author(s):  
Jamil Abdo ◽  
Spencer Hamblin ◽  
Genshe Chen
Keyword(s):  
Data Collection ◽  
Technology Implementation ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Imaging Systems ◽  
Extreme Conditions ◽  
Commercial Vehicles ◽  
Performance Quality ◽  
Adverse Weather Conditions ◽  
Adverse Weather

Abstract Light detection and ranging (Lidar) imaging systems are being increasingly used in autonomous vehicles. However, the final technology implementation is still undetermined as major automotive manufacturers are only starting to select providers for data collection units that can be introduced in commercial vehicles. Currently, testing for autonomous vehicles is mostly performed in sunny environments. Experiments conducted in good weather cannot provide information regarding performance quality under extreme conditions such as fog, rain, and snow. Under extreme conditions, many instances of false detection may arise because of the backscattered intensity, thereby reducing the reliability of the sensor. In this work, lidar sensors were tested in adverse weather to understand how extreme weather affects data collection. Testing setup and algorithms were developed for this purpose. The results are expected to provide technological validation for the commercial use of lidar in automated vehicles. The effective ranges of two popular lidar sensors were estimated under adverse weather conditions, namely, fog, rain, and snow. Results showed that fog severely affected lidar performance, and rain too had some effect on the performance. Meanwhile, snow did not affect lidar performance.

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