Translating weather forecasts to road accident probabilities

2021 ◽  
Author(s):  
Nico Becker ◽  
Henning Rust ◽  
Uwe Ulbrich
Keyword(s):  
Traffic Management ◽  
Model Performance ◽  
Weather Conditions ◽  
Road Accident ◽  
Road Maintenance ◽  
Logistic Regression Models ◽  
Weather Forecasts ◽  
Road Users ◽  
Accident Probability ◽  
Accident Probabilities

<p>In Germany about 1000 severe road accidents are recorded by the police per day. On average, 8 % of these accidents are related to weather conditions, for example due to rain, snow or ice. In this study we compare several versions of a logistic regression models to predict hourly probabilities of such accidents in German administrative districts. We use radar, reanalysis and ensemble forecast data from the regional operational model of the German Meteorological Service DWD as well as police reports to train the model with different combinations of input datasets. By including weather information in the models, the percentage of correctly predicted accidents (hit rate) is increased from 30 % to 70 %, while keeping the percentage of wrongly predicted accidents (false-alarm rate) constant at 20 %. Accident probability increases nonlinearly with increasing precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are approximately 5 times larger at negative temperatures compared to positive temperatures. When using ensemble weather forecasts to predict accident probabilities for a leadtime of up to 21 h ahead, the decline in model performance is negligible. We suggest to provide impact-based warnings for road users, road maintenance, traffic management and rescue forces.</p>

scholarly journals Predictive modeling of hourly probabilities for weather-related road accidents

2020 ◽  
Vol 20 (10) ◽  
pp. 2857-2871
Author(s):  
Nico Becker ◽  
Henning W. Rust ◽  
Uwe Ulbrich
Keyword(s):  
Traffic Management ◽  
Model Performance ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Road Maintenance ◽  
Road Accidents ◽  
Logistic Regression Models ◽  
Weather Forecasts ◽  
Accident Probability ◽  
Adverse Weather

Abstract. Impacts of weather on road accidents have been identified in several studies with a focus mainly on monthly or daily accident counts. This study investigates hourly probabilities of road accidents caused by adverse weather conditions in Germany on the spatial scale of administrative districts using logistic regression models. Including meteorological predictor variables from radar-based precipitation estimates, high-resolution reanalysis and weather forecasts improves the prediction of accident probability compared to models without weather information. For example, the percentage of correctly predicted accidents (hit rate) is increased from 30 % to 70 %, while keeping the percentage of wrongly predicted accidents (false-alarm rate) constant at 20 %. When using ensemble weather forecasts up to 21 h instead of radar and reanalysis data, the decline in model performance is negligible. Accident probability has a nonlinear relationship with precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are approximately 5 times larger at negative temperatures compared to positive temperatures. The findings are relevant in the context of impact-based warnings for road users, road maintenance, traffic management and rescue forces.

scholarly journals Predictive modeling of hourly probabilities for weather-related road accidents

2020 ◽  
Author(s):  
Nico Becker ◽  
Henning W. Rust ◽  
Uwe Ulbrich
Keyword(s):  
Traffic Management ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Road Maintenance ◽  
Road Accidents ◽  
Logistic Regression Models ◽  
Weather Forecasts ◽  
Hourly Precipitation ◽  
Adverse Weather ◽  
Accident Probabilities

Abstract. An impact of weather on road accidents has been identified in several studies with a focus mainly on monthly or daily accident counts. We study hourly probabilities of road accidents caused by adverse weather conditions in Germany on the spatial scale of administrative districts. Meteorological predictor variables from radar-based precipitation estimates, high-resolution reanalysis and weather forecasts are used in logistic regression models. Models taking into account temperature and hourly precipitation sums reach the best predictive skill according to different metrics. By introducing meteorological variables, the models hit rate is increased from 0.3 to 0.7, while keeping the false alarm rate constant at 0.2. Accident probability has a non-linear relationship with precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are about 5 times larger at negative temperatures compared to positive temperatures. Based on ensemble weather forecasts skilful predictions of accident probabilities of up to 21 hours are possible; the loss of skill compared to a model using radar and reanalysis data is negligible. The findings are relevant in the context of impact based warnings for both road users, road maintenance and traffic management authorities, as well as rescue forces.

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.

scholarly journals Automatic Accident Detection Techniques using CCTV Surveillance Videos: Methods, Data sets and Learning Strategies

2020 ◽  
Vol 9 (3) ◽  
pp. 4282-4285
Keyword(s):  
Learning Strategies ◽  
Traffic Management ◽  
Human Life ◽  
Weather Conditions ◽  
Road Accident ◽  
Data Sets ◽  
Priority List ◽  
Surveillance Videos ◽  
Detection Techniques ◽  
Accident Detection

Intelligent communities are utilizing different creative ideas to improve the quality of human life. Due to fast growing sizes of our cities, need of travelling is constantly increasing, which in turn has increased count of vehicles on the roads. Increasing number of vehicles on the roads has brought about numerous difficulties for Street Traffic Management Authorities. Amongst different traffic related issues, road accidents are something worth giving attention to and have to be on the priority list. This paper describes various automatic road accident detection techniques, which automatically detect accidents using surveillance videos in real-time. As these methods do not consider various lighting conditions, changing weather conditions and different traffic patterns, none of the methods are robust enough to address all the incidences of the accident. In this paper, authors have described and compared many such methods.

Identification of Risk Factors for Collisions Involving Cyclists Based on Gdansk Example

2017 ◽  
Author(s):  
Romanika Okraszewska ◽  
Kazimierz Jamroz ◽  
Marek Bauer ◽  
Krystian Birr ◽  
Anna Gobis
Keyword(s):  
Risk Factors ◽  
Traffic Management ◽  
Weather Conditions ◽  
Traffic Light ◽  
The Road ◽  
Road Users ◽  
Organizational Type ◽  
Road Speed ◽  
External Conditions ◽  
On The Road

The role of pedestrian and bicycle traffic in Poland has growing trend. The comprehensive traffic study, conducted in Gdansk in 2016, has confirmed the increase in the number of cyclists and their share in the modal split. Therefore, it is particularly important to ensure the safety of this group of unprotected road users. Only in 2015 on the roads of Gdansk occurred 93 accidents (excluding collisions) involving cyclists. As a result, 101 people were injured, including nine seriously and 3 people killed. The study aim was to identify risk factors for collisions involving cyclists based on data of accidents reported to the police. The following factors were analysed: the conditions for the drivers on the road (speed limits of, surface conditions), conditions for cyclists (cycling infrastructure, traffic management), external conditions (time of the year, time of the day, weather conditions), conditions organizational (type of intersection, traffic light) as well as the social aspects – the behaviour of all users.

Evaluation Of Major Causes Of Road Accidents Along North–East Highway, Nigeria

2015 ◽  
Vol 73 (4) ◽  
Author(s):  
Arafat Suleiman Yero ◽  
Tijanni Y Ahmed ◽  
Mohd Rosli Hainin
Keyword(s):  
Road Traffic ◽  
Road Accident ◽  
Eastern Region ◽  
Road Maintenance ◽  
Vehicle Accidents ◽  
The Road ◽  
Goods And Services ◽  
North East ◽  
The North ◽  
Road Users

A major road link in the North-Eastern region of Nigeria is the Bauchi – Maiduguri highway that is a 425 km road that links a section of the north east region to other regions of Nigeria. The goods and services to the region are basically transported by road.  This has increased vehicular traffic that resulted in increased road accident rates over the years.  It is paramount to investigate the major causes of vehicle accidents on this highway as much has not been done to investigate accident cases on the route. The five year accident record on that route was obtained from the Federal Road Safety Corp of Nigeria,   the Nigeria Police traffic unit, and the Nigeria union of road traffic workers. The study indicated that speed violation by drivers and bad road conditions contributes greatly in the rate of accidents along the route. Hence the study recommends better road maintenance culture and more sensitization of the road users and enforcement of speed limits.

OPERATING SPEED OF VEHICLES DURING RAINFALL AT NIGHT: CASE STUDY IN PONTIAN, JOHOR

2016 ◽  
Vol 78 (7-2) ◽  
Author(s):  
Sitti Asmah Hassan ◽  
Lavine Wong ◽  
Nordiana Mashros ◽  
Hashim Mohammed Alhassan ◽  
Nur Sabahiah Abdul Sukor ◽  
...  
Keyword(s):  
Traffic Management ◽  
Environmental Changes ◽  
Monsoon Season ◽  
Weather Conditions ◽  
Speed Reduction ◽  
Rainfall Condition ◽  
Road Users ◽  
Water Accumulation ◽  
Traffic Management System ◽  
The Impact

Speed is one of the important parameters of traffic flow that can be used to determine the performance of driver’s behaviour under various scenarios. Changes in weather conditions caused changes in drivers’ speed due to various reasons. In Malaysia, there is slightly high number of road accidents at night. Rainfall at night does not only cause poor visibility to drivers, but it also gives a sense of insecurity especially as there is a significant reduction in the visibility of the object in front. Improper road conditions can worsen the situation, for example, rainfall can cause water accumulation on road surfaces which can increase skidding problem, potholes and hydroplaning effect. In relation to these situations, hence it is crucial to understand how the abrupt situation affect response of driver’s in terms of the macroscopic behaviour. These unpredictable environmental changes seem like portraying a very unpleasant journey for drivers especially to travel under rainfall condition at night. Therefore, there is a need to observe how individual vehicles react in terms of speed adjustment and response to the different rainfall intensities downpour at night. Hence this study was conducted to determine the impact of different rainfall intensities at night on vehicles’ speed. Traffic data was obtained using automatic traffic counter at a cross section of a road at Pengkalan Raja, Pontian for about three months during monsoon season. Rainfall data report was obtained from the Department of Drainage and Irrigation, Pontian. From this study, it was found that there is a speed reduction from the dry condition regardless of rainfall intensities at night. As rainfall intensities at night higher, the speed reduction is higher as well except for heavy rainfall condition.   The mean speed, 15th percentile and 85th percentile of vehicles decrease with the increase in rainfall intensity at night. It can be concluded that rainfall have impact on vehicle’s speed irrespective of their intensities. Findings from this study can be used to help local authorities and transport planners in planning an efficient traffic management system for a safer travel experience to road users in Malaysia.

PERSONALIZED APPROACH TO THE ORGANIZATION OF MEDICAL CARE FOR PATIENTS WITH WEATHER DEPENDENCE

2020 ◽  
pp. 35-39
Author(s):  
Klepikov O.V. ◽  
Kolyagina N.M. ◽  
Berezhnova T.A. ◽  
Kulintsova Ya.V.
Keyword(s):  
Medical Care ◽  
Cardiovascular System ◽  
Performance Indicators ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Outpatient Clinics ◽  
Vulnerable Groups ◽  
Pathological Effect ◽  
Weather Forecasts ◽  
Personalized Approach

Relevance. Today, in preventive medicine, climatic conditions that have a pathological effect on the functional state of a person are increasingly being updated. the occurrence of exacerbations of many diseases can be causally associated with various weather conditions. Aim: to develop the main tasks for improving the organization of medical care for weather-dependent patients with diseases of the cardiovascular system. Material and methods. The assessment of personnel, material and technical support and the main performance indicators of an outpatient clinic was carried out on the example of the Voronezh city polyclinic No. 18 to develop the main tasks for improving the organization of medical care for weather-dependent patients with diseases of the cardiovascular system. Results. The main personnel problem is the low staffing of district therapists and specialists of a narrow service. One of the priorities for reducing the burden on medical hospitals is the organization of inpatient replacement medical care on the basis of outpatient clinics. The indicators for the implementation of state guarantees for the outpatient network for 2018, which were fully implemented, are given. The analysis of the planned load performance by polyclinic specialists is presented. Cardiological and neurological services carry out measures to reduce the risk of exacerbations of diseases with cerebral atherosclerosis, hypertension, and major neurological nosologies. Conclusion. Improving the organization of medical care for weather-dependent patients with cardiovascular diseases are: informing patients about the sources of specialized medical weather forecasts in the region, organizing the work of the medical prevention office, implementing an interdepartmental approach to providing health care to the most vulnerable groups of the population.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

scholarly journals Public Roads as Places of Interspecies Conflict: A Study of Horse-Human Interactions on UK Roads and Impacts on Equine Exercise

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1072
Author(s):  
Danica Pollard ◽  
Tamzin Furtado
Keyword(s):  
Near Miss ◽  
Online Questionnaire ◽  
Near Misses ◽  
Logistic Regression Models ◽  
Emotional Management ◽  
The Road ◽  
Human Interactions ◽  
Road Users ◽  
Conflict Risk ◽  
The Individual

Real or perceived traffic risk is a significant barrier to walking and cycling. To understand whether similar barriers influence equestrians, this study obtained exercise behaviours, road use and experiences of road-related incidents from UK equestrians (n = 6390) via an online questionnaire. Multivariable logistic regression models were used to identify factors associated with road use and experiencing a near-miss or injury-causing incident in the previous year. Content analysis identified themes around equestrians’ decisions not to use roads. Our results show that most equestrians (84%) use roads at least once weekly, and in the previous year, 67.7% had a near-miss and 6.1% an injury-causing incident. Road use differs regionally, with exercise type and off-road route availability. Road-using equestrians covered greater daily distances and were younger. However, younger equestrians were at higher risk of near-misses. Respondents’ decisions not to use roads were based on individualised risk assessments arising from: the road itself, perceptions of other road users, the individual horse and the handler’s own emotional management. Roads were perceived as extremely dangerous places with potentially high conflict risk. Injury-causing incidents were associated with increasing road-use anxiety or ceasing to use roads, the proximity of off-road routes, having a near-miss and type of road use. Targeted road-safety campaigns and improved off-road access would create safer equestrian spaces.

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