scholarly journals Analysis of the distribution of the number of applications of the estimated load on the Federal roads during the year

2018 ◽  
Vol 5 (4) ◽  
Author(s):  
Vladimir Akulov ◽  
Artem Tiraturyan ◽  
Ilya Bodro ◽  
Anastasia Simakova ◽  
Marina Farnieva
Keyword(s):  
Traffic Flow ◽  
Statistical Processing ◽  
Weather Conditions ◽  
Design Stage ◽  
Traffic Intensity ◽  
Agricultural Industry ◽  
The Road ◽  
Calculated Load ◽  
On The Road ◽  
Favorable Weather

The article is devoted to the statistical processing of traffic intensity and composition of traffic flow obtained from the points of automated traffic intensity accounting for 2010-2018 in order to determine the distribution of the number of applications of the calculated load by months. The main source of information for statistical processing was the results of traffic accounting on highways M-1 «Belarus», a-107 MMK Mozhaisk-Volokolamsk highway, M-3 «Ukraine», M-4 «don», M-4 «don». The correct determination of the traffic intensity and composition of the traffic flow is an important task that allows you to make adequate decisions at the design stage of roads, namely to choose a road structure that can operate under load from the actual traffic flow for the entire service life. The authors calculated the total number of applications of the calculated load to the point on the surface of the coating, using the coefficients of reduction of vehicles to the calculated load of 115 kN. After calculating the total number of applications, the resulting value was divided by the number of days in the month in question. According to the data obtained, the total total number of applications of the calculated load at all points of accounting, by month, was found. The minimum values of the number of load applications are observed in winter (January, February, March), when the situation on the road deteriorates due to weather conditions. The values range from 4.75 % to 8 % for roads M-1 «Belarus», M-3 «Ukraine», M-4 «Don», M-4 «Don». The maximum values of the number of load applications observed in the warmer months (July, August, September, October), due to the fact that there are favorable weather conditions for recreation and the most active agricultural industry. The values range from 7.6 % to 11.3 % for the roads M-1 «Belarus», M-3 «Ukraine», M-4 «Don», M-4 «Don».

scholarly journals Fail to Yield? An Analysis of Ambulance Crashes in Taiwan

2021 ◽  
Vol 13 (3) ◽  
pp. 1566
Author(s):  
Rong-Chang Jou ◽  
Ming-Che Chao
Keyword(s):  
Public Education ◽  
Weather Conditions ◽  
Medical Emergency ◽  
Transportation Safety ◽  
Emergency Vehicle ◽  
The Road ◽  
Mnl Model ◽  
On The Road ◽  
Crash Injuries ◽  
The Relationship

Introduction—Medical emergency vehicles help patients get to the hospital quickly. However, there were more and more ambulance crashes on the road in Taiwan during the last decade. This study investigated the characteristics of medical emergency vehicle crashes in Taiwan from January 2003 to December 2016. Methods—The ordered logit (OL) model, multinominal logit (MNL) model, and partial proportional odds (PPO) model were applied to investigate the relationship between the severity of ambulance crash injuries and its risk factors. Results—We found the various factors have different effects on the overall severity of ambulance crashes, such as ambulance drivers’ characteristics and road and weather conditions. When another car was involved in ambulance crashes, there was a disproportionate effect on the different overall severity, as found by the PPO model. Conclusions—The results showed that male ambulance drivers and car drivers who failed to yield to an ambulance had a higher risk of severe injury from ambulance crashes. Ambulance crashes are an emerging issue and need further policies and public education regarding Taiwan’s ambulance transportation safety.

scholarly journals Assessment of the impact of the traffic situation in urban area on the amount of volatile organic compounds getting into the cabin of the car on the road

2019 ◽  
Vol 100 ◽  
pp. 00073
Author(s):  
Maria Skrętowicz ◽  
Joanna Świeściak
Keyword(s):  
Volatile Organic Compounds ◽  
Urban Area ◽  
Organic Compounds ◽  
Traffic Situation ◽  
Traffic Intensity ◽  
The Road ◽  
Volatile Organic ◽  
On The Road ◽  
Time Of Travel ◽  
The Impact

In the paper the levels of concentrations of volatile organic compounds getting into car cabin during the driving have been measured. Three series of the tests have been performed. Each series has been carried out in different road situation in terms of traffic intensity. For the tests exploited passenger car, Subaru Impreza was used. Before every series the background measurements was carried out and directly after that, the correct the correct tests were performed. Inside the cabin 14 different organic compounds have been identified. To analyse the change of the concentrations levels between the correct and background test have been calculated. The results indicate that the longer time of travel caused that the driver and passengers are more exposed to highest concentrations of VOCs.

scholarly journals PATTERNS OF URBAN TRANSPORT FLOWS GENERATION

2020 ◽  
Vol 1 (154) ◽  
pp. 248-252 ◽  
Author(s):  
I. Chumachenko ◽  
A. Galkin ◽  
N. Davidich ◽  
Y. Kush ◽  
I. Litomin
Keyword(s):  
Nervous System ◽  
Travel Time ◽  
Traffic Flow ◽  
Individual Characteristics ◽  
Urban Transport ◽  
Traffic Intensity ◽  
Important Criterion ◽  
Traffic Lights ◽  
The Road ◽  
Expert Opinions

The article is devoted to explaining the issue of exploring the patterns of formation of urban traffic flows in case of the development of urban transport systems projects. Existing methods for predicting traffic flow parameters are developed for all drivers of vehicles, regardless of their individual characteristics, and contain only travel time as a parameter. It is proposed to use the route run, travel time, traffic intensity as the possible criteria, the route runs along the main roads, the condition of the road surface, the number of traffic lights on the route, and fatigue when driving. Based on the results of a questionnaire survey of drivers of individual vehicles, the significance of the criteria for choosing a route of movement for drivers with various types of nervous systems is assessed. The most significant criterion was set up when choosing a route for travel is the “condition of the road surface”. The second most important criterion is “run along the route”. The third criterion was “travel time”. The criterion “traffic intensity” has become even less significant for drivers. The next most important criterion was “the route take place over the main roads”. Even less significant was the criterion “quantity of traffic lights on the route”. The criterion “fatigue during movement” became the least significant. To assess the consistency of expert opinions, a concordance coefficient was used. The values of the concordance coefficient showed that there is a consistency of expert opinions both for the total population of drivers and for their groups, divided on the basis of “temperament”. It was found that when choosing a travel route, drivers are guided by numerous criteria. Moreover, the advantage or disadvantage of one or another criterion depends on its individual characteristics, which are determined by the properties of the central nervous system. Keywords: driver, route, traffic flow, vehicle, questionnaire, nervous system, criterion, significance.

scholarly journals FOURIER ANALYSIS OF THE TRAFFIC FLOW INTENSITY

2021 ◽  
pp. 46-59
Author(s):  
M.G. Boyarshinov ◽  
◽  
A.S. Vavilin ◽  
A.G. Shumkov ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Fourier Series ◽  
Traffic Flow ◽  
Harmonic Functions ◽  
Traffic Flows ◽  
The Road ◽  
Flow Intensity ◽  
Software And Hardware ◽  
On The Road ◽  
Amplitude Characteristics

The relevance of this work is determined by the need to find modern ways to process the information about traffic flows for regulating and controlling the movement of transport and pedestrians, to reduce congestion, road accidents, etc. The object of study is a part of road with heavy two-way traffic, equipped with a software and hardware complex that allows to measure the characteristics of the transport flow. The subject of the study is the daily intensity of the cars flow during the week, from Monday to Sunday. The purpose of this study is to analyze the amplitudes, frequencies, and periods of harmonic functions obtained by decomposing the time series of road traffic intensities to identify the main patterns of traffic flow formation. As a theoretical and methodological approach, the decomposition of the function of the traffic flow intensity in the Fourier series with respect to harmonic functions is used. The approach developed by the authors using the fast Fourier transform procedure made it possible to determine the amplitude-frequency characteristics of the time series under consideration, which is a scientific novelty of the analysis. It is proposed to use the «period-amplitude» characteristics as physically more meaningful instead of the «frequency-amplitude» dependencies traditionally used for the analysis. The processing of data obtained from software and hardware complexes allowed us to determine dependences of the car flow intensity on the road of the Perm city at different averaging intervals, to describe the features of the motor transport movement on the road under consideration. As a result of the study, the amplitude-frequency characteristics of time series are obtained. It is shown that the individual harmonics of the Fourier series expansion of the traffic flow intensity, which exhibits the properties of a random function, duplicate the periodicity of the global, local, and intermediate extremes of the original function and have similar periods. The practical significance consists in the use of the decomposition of the function of the traffic flow intensity in the Fourier series of harmonic functions for predicting traffic flows, controlling the operation of traffic lights, monitoring the operation of equipment, as well as in the reconstruction, design and construction of roads and road objects. The study will continue in the direction of obtaining, processing and determining the «period-amplitude» characteristics for time series of traffic flow intensity for other road networks.

scholarly journals Data-driven profiling of traffic flow with varying road conditions

2019 ◽  
pp. 149-157 ◽  
Author(s):  
O K Golovnin
Keyword(s):  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Weather Conditions ◽  
Flow Speed ◽  
Data Driven ◽  
The Road ◽  
Data Driven Approach ◽  
Traffic Flow Characteristics ◽  
The City

The article describes the road, institutional and weather conditions that affect the traffic flow. I proposed a method for traffic flow profiling using a data-driven approach. The method operates with macroscopic traffic flow characteristics and detailed data of road conditions. The article presents the results of traffic flow speed and intensity profiling taking into account weather conditions. The study used road traffic and conditions data for the city of Aarhus, Denmark. The results showed that the method is effective for traffic flow forecasting due to varying road conditions.

scholarly journals Intelligent Accident Prevention in VANETs

2019 ◽  
Vol 8 (2) ◽  
pp. 2401-2405
Keyword(s):  
Road Safety ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Weather Conditions ◽  
Accident Prevention ◽  
Road Accidents ◽  
Human Errors ◽  
The Road ◽  
On The Road ◽  
Nearest Neighbour Classifier

Accident prevention has always been an important issue for governments and car manufacturers across the world. Roughly 1.5 million people are killed in road accidents annually in India. The primary causes of accidents are broken and weathered roads, hazardous weather conditions, as well as human errors such as over speeding, distracted driving, and not following road safety rules. The traffic police work hard to enforce strict rules and maintain accident-free roads, but this hasn’t proven to be efficient. A vehicular ad hoc network (VANET), as the name says, is a network consisting of nodes. These nodes depict vehicles on the road. This project aims to use this technology with K-Nearest Neighbour Classifier (KNN) to create a prototype of a system which can notify drivers of an impending accident caused by forward collisions, rear collision etc., thus enabling them to take immediate action and prevent it.

scholarly journals Research on Virtual Test of Automobile Automatic Emergency Braking System on Ice-Snow Road

2021 ◽  
Vol 261 ◽  
pp. 02065
Author(s):  
Xianchao Zhu ◽  
Sheng Chang ◽  
Bingtao Li ◽  
Hualei Lu
Keyword(s):  
Weather Conditions ◽  
Simulation Method ◽  
Time To Collision ◽  
The Road ◽  
Injury Reduction ◽  
Emergency Braking ◽  
Virtual Test ◽  
Braking Distance ◽  
On The Road ◽  
Basic Characteristics

In view of the severe weather conditions in cold regions, the basic characteristics and braking distance of ice snow covered pavement are analyzed. This paper uses the PreScan/CarSim/Simulink software co-simulation method to test the automatic emergency braking (AEB) system on ice-snow roads. Through the appropriate adjustment of the time to collision (TTC) threshold, the car makes automatic emergency braking on the road with low friction coefficient system can achieve the effect of collision avoidance and injury reduction.

scholarly journals A Novel Algorithm Based on the Pixel-Entropy for Automatic Detection of Number of Lanes, Lane Centers, and Lane Division Lines Formation

Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 725 ◽  
Author(s):  
Fernando Hermosillo-Reynoso ◽  
Deni Torres-Roman ◽  
Jayro Santiago-Paz ◽  
Julio Ramirez-Pacheco
Keyword(s):  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Moving Objects ◽  
Color Space ◽  
Automatic Detection ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Lane Detection ◽  
Computational Time ◽  
The Road

Lane detection for traffic surveillance in intelligent transportation systems is a challenge for vision-based systems. In this paper, a novel pixel-entropy based algorithm for the automatic detection of the number of lanes and their centers, as well as the formation of their division lines is proposed. Using as input a video from a static camera, each pixel behavior in the gray color space is modeled by a time series; then, for a time period τ , its histogram followed by its entropy are calculated. Three different types of theoretical pixel-entropy behaviors can be distinguished: (1) the pixel-entropy at the lane center shows a high value; (2) the pixel-entropy at the lane division line shows a low value; and (3) a pixel not belonging to the road has an entropy value close to zero. From the road video, several small rectangle areas are captured, each with only a few full rows of pixels. For each pixel of these areas, the entropy is calculated, then for each area or row an entropy curve is produced, which, when smoothed, has as many local maxima as lanes and one more local minima than lane division lines. For the purpose of testing, several real traffic scenarios under different weather conditions with other moving objects were used. However, these background objects, which are out of road, were filtered out. Our algorithm, compared to others based on trajectories of vehicles, shows the following advantages: (1) the lowest computational time for lane detection (only 32 s with a traffic flow of one vehicle/s per-lane); and (2) better results under high traffic flow with congestion and vehicle occlusion. Instead of detecting road markings, it forms lane-dividing lines. Here, the entropies of Shannon and Tsallis were used, but the entropy of Tsallis for a selected q of a finite set achieved the best results.

Self-Driving Robotic Cars

2021 ◽  
pp. 599-631
Author(s):  
Jelena L. Pisarov ◽  
Gyula Mester
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicle ◽  
Closed Circuit ◽  
Small Scale ◽  
Traffic Patterns ◽  
Complex Environments ◽  
The Road ◽  
Traffic Jams ◽  
Simulation Techniques ◽  
On The Road

Even the behavior of a single driver can have a dramatic impact on hundreds of cars, making it more difficult to manage traffic. While the attempts to analyze and correct the traffic patterns that lead to congestion began as early in the 1930s, it wasn't until recently that scientists developed simulation techniques and advanced algorithms to create more realistic visualizations of traffic flow. In experiments conducted by Alexandre Bayen and the Liao-Cho, which included several dozen cars in a small-scale closed circuit, a single autonomous vehicle could eliminate traffic jams by moderating the speed of every car on the road. In larger simulations, the research showed that once their number rises to 5-10% of all cars in the traffic, they can manage localized traffic even in complex environments, such as merging multiple lanes of traffic into two or navigating extremely busy sections.

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