scholarly journals Model for Predicting Road Markings Service Life

2019 ◽  
Vol 14 (3) ◽  
pp. 341-359
Author(s):  
Dario Babić ◽  
Anđelko Ščukanec ◽  
Darko Babić ◽  
Mario Fiolić
Keyword(s):  
Service Life ◽  
Measuring Method ◽  
Timely Manner ◽  
Data Set ◽  
Winter Maintenance ◽  
The Road ◽  
Annual Average Daily Traffic ◽  
Dynamic Measuring ◽  
Road Marking ◽  
Life Prediction Model

Road markings provide drivers with the information necessary for their comfortable and safe journey. To achieve that, they must be visible in all driving conditions, which means that they have to be renewed and maintained in a timely manner. This research aims to develop a model for predicting the service life of paint, thermoplastic and agglomerate cold plastic road markings. The research comprised 5218.00 km (115 roads) of solvent-borne paint road markings, 579.00 km (30 roads) of thermoplastic and 4979.00 km (30 roads) of agglomerate cold plastic road markings. The retroreflectivity of road markings was measured two times (after renewal and after winter) using the dynamic measuring method. Service life prediction model was developed for each material based on factors such as initial retroreflectivity, road marking age and position, annual average daily traffic and winter maintenance activity of the road. Developed models were tested using a new data set, and all three models showed satisfactory accuracy. The application of the model enables road authorities to optimise road-marking maintenance activities, while at the same time, ensuring the level of visibility required by drivers.

scholarly journals The Evaluation of Experimental Variables for Sustainable Virtual Road Safety Audits

2021 ◽  
Vol 13 (11) ◽  
pp. 5899
Author(s):  
Yeonsoo Jun ◽  
Juneyoung Park ◽  
Chunho Yeom
Keyword(s):  
Road Safety ◽  
Traffic Light ◽  
Scenario Development ◽  
Driving Simulators ◽  
Traffic Condition ◽  
The Road ◽  
Road Pavement ◽  
Net Promoter ◽  
Road Safety Audits ◽  
Road Marking

This paper evaluates experimental variables for virtual road safety audits (VRSAs) through practical experiments to promote sustainable road safety. VRSAs perform road safety audits using driving simulators (DSs), and all objects in the road environment cannot be experimental variables because of realistic constraints. Therefore, the study evaluates the likelihood of recommendation of VRSA experimental variables by comparing DSs experiments and field reviews to secure sustainable road safety conditions. The net promoter score results evaluated “Tunnel”, “Bridge”, “Underpass”, “Footbridge”, “Traffic island”, “Sign”, “Lane”, “Road marking”, “Traffic light”, “Median barrier”, “Road furniture”, and “Traffic condition” as recommended variables. On the contrary, the “Road pavement”, “Drainage”, “Lighting”, “Vehicle”, “Pedestrian”, “Bicycle”, “Accident”, and “Hazard event” variables were not recommended. The study can be used for decision making in VRSA scenario development as an initial effort to evaluate its experimental variables.

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

scholarly journals Characterization of Road Condition with Data Mining Based on Measured Kinematic Vehicle Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Johannes Masino ◽  
Jakob Thumm ◽  
Guillaume Levasseur ◽  
Michael Frey ◽  
Frank Gauterin ◽  
...  
Keyword(s):  
Data Mining ◽  
Support Vector ◽  
Matlab Toolbox ◽  
Data Set ◽  
The Road ◽  
Acceleration Sensors ◽  
Road Surfaces ◽  
Road Condition ◽  
Sensor Signals

This work aims at classifying the road condition with data mining methods using simple acceleration sensors and gyroscopes installed in vehicles. Two classifiers are developed with a support vector machine (SVM) to distinguish between different types of road surfaces, such as asphalt and concrete, and obstacles, such as potholes or railway crossings. From the sensor signals, frequency-based features are extracted, evaluated automatically with MANOVA. The selected features and their meaning to predict the classes are discussed. The best features are used for designing the classifiers. Finally, the methods, which are developed and applied in this work, are implemented in a Matlab toolbox with a graphical user interface. The toolbox visualizes the classification results on maps, thus enabling manual verification of the results. The accuracy of the cross-validation of classifying obstacles yields 81.0% on average and of classifying road material 96.1% on average. The results are discussed on a comprehensive exemplary data set.

scholarly journals A case study of combined winter road snow plowing and de-icer spreading

2017 ◽  
Vol 44 (12) ◽  
pp. 1005-1013 ◽  
Author(s):  
Olivier Quirion-Blais ◽  
André Langevin ◽  
Martin Trépanier
Keyword(s):  
Neighborhood Search ◽  
Problem Analysis ◽  
Winter Maintenance ◽  
The Road ◽  
Snow Plowing ◽  
Winter Road ◽  
Turn Restrictions ◽  
Maintenance Problem

In this article, we address a winter maintenance problem where the streets need to be plowed and gritted in a sequence that depends on the class of the road. The maintenance fleet includes vehicles equipped for plowing, some for spreading, and some for both at once. The objective is to complete the operations as rapidly as possible while considering street hierarchy, turn restrictions, heterogeneous speeds, and street–vehicle compatibility. An adaptive large neighborhood search framework is developed to solve the problem. Analysis of the results obtained can provide both a good basis for vehicle routing and help managers plan long-term policies and investments.

Prediction of Design Hourly Volume on Rural Roads

2020 ◽  
pp. 036119812096556
Author(s):  
Miloš Petković ◽  
Vladan Tubić ◽  
Nemanja Stepanović
Keyword(s):  
Coefficient Of Determination ◽  
Rural Roads ◽  
The Road ◽  
Annual Average Daily Traffic ◽  
Proposed Model ◽  
Traffic Volumes ◽  
Implementation Costs ◽  
On The Road ◽  
Predicted Values ◽  
Design Hourly Volume

Design hourly volume (DHV) represents one of the most significant parameters in the procedures of developing and evaluating road designs. DHV values can be accurately and precisely calculated only on the road sections with the implemented automatic traffic counters (ATCs) which constantly monitor the traffic volume. Unfortunately, many road sections do not contain ATCs primarily because of the implementation costs. Consequently, for many years, the DHV values have been defined on the basis of occasional counting and the factors related to traffic flow variability over time. However, it has been determined that this approach has significant limitations and that the predicted values considerably deviate from the actual values. Therefore, the main objective of this paper is to develop a model which will enable DHV prediction on rural roads in cases of insufficient data. The suggested model is based on the correlation between DHVs and the parameters defining the characteristics of traffic flows, that is, the relationship between the traffic volumes on design working days and non-working days, and annual average daily traffic. The results of the conducted research indicate that the application of the proposed model enables the prediction of DHV values with a significant level of data accuracy and reliability. The coefficient of determination (R2) shows that more than 98% of the variance of the calculated DHVs was explained by the observed DHV values, while the mean error ranged from 4.86% to 7.84% depending on the number of hours for which DHV was predicted.

scholarly journals AUTOMATIC BLOCKED ROADS ASSESSMENT AFTER EARTHQUAKE USING HIGH RESOLUTION SATELLITE IMAGERY

2015 ◽  
Vol XL-1-W5 ◽  
pp. 601-605 ◽  
Author(s):  
H. Rastiveis ◽  
E. Hosseini-Zirdoo ◽  
F. Eslamizade
Keyword(s):  
High Resolution ◽  
World View ◽  
Satellite Image ◽  
Data Set ◽  
The Road ◽  
Vector Map ◽  
Processing Step ◽  
Image Quality Improvement ◽  
High Resolution Satellite Imagery ◽  
The City

In 2010, an earthquake in the city of Port-au-Prince, Haiti, happened quite by chance an accident and killed over 300000 people. According to historical data such an earthquake has not occurred in the area. Unpredictability of earthquakes has necessitated the need for comprehensive mitigation efforts to minimize deaths and injuries. Blocked roads, caused by debris of destroyed buildings, may increase the difficulty of rescue activities. In this case, a damage map, which specifies blocked and unblocked roads, can be definitely helpful for a rescue team. <br><br> In this paper, a novel method for providing destruction map based on pre-event vector map and high resolution world view II satellite images after earthquake, is presented. For this purpose, firstly in pre-processing step, image quality improvement and co-coordination of image and map are performed. Then, after extraction of texture descriptor from the image after quake and SVM classification, different terrains are detected in the image. Finally, considering the classification results, specifically objects belong to “debris” class, damage analysis are performed to estimate the damage percentage. In this case, in addition to the area objects in the “debris” class their shape should also be counted. The aforementioned process are performed on all the roads in the road layer.In this research, pre-event digital vector map and post-event high resolution satellite image, acquired by Worldview-2, of the city of Port-au-Prince, Haiti's capital, were used to evaluate the proposed method. The algorithm was executed on 1200×800 m2 of the data set, including 60 roads, and all the roads were labelled correctly. The visual examination have authenticated the abilities of this method for damage assessment of urban roads network after an earthquake.

scholarly journals Determining the correlation between daytime and night-time road markings visibility

2016 ◽  
Vol 11 (4) ◽  
pp. 283-290 ◽  
Author(s):  
Dario Babić ◽  
Anđelko Ščukanec ◽  
Darko Babić
Keyword(s):  
Dynamic Test ◽  
Measuring Method ◽  
Objective Evaluation ◽  
Test Method ◽  
Night Time ◽  
Road Section ◽  
Minimum Requirements ◽  
Dynamic Measuring ◽  
The Republic ◽  
The Relationship

Road markings quality control implies conducting several different tests, of which the most significant are visibility tests comprising daytime and night-time visibility measurements by applying the static or the dynamic measuring method. Although the dynamic test method allows measuring the visibility along the entire road section and thus provides a more complete and objective evaluation of road markings quality compared to the static method, it does not measure daytime visibility, for which both the European and the national directives define the minimum requirements. The purpose of this paper is to examine the correlation between daytime and night-time visibility based on static measurements conducted on state roads in the Republic of Croatia. The correlation analysis determined that the strength of relationship between daytime and night-time visibility, is relatively weak. Despite being relatively weak, the relationship still exists, which was the reason for conducting a further analysis. In the analysis, a unique coefficient was obtained through the ratio of retroreflection value and daytime visibility value for all the measurements. The unique coefficient was basis for development of a model that will be able to calculate the daytime visibility based on the results of the dynamic measurements of road markings night-time visibility. The authors evaluated the model with a t-test and concluded that the accuracy of the model is statistically satisfactory.

Summarizing of international experience of winter slipperiness prevention

2021 ◽  
Vol 2021 (23) ◽  
pp. 225-236
Author(s):  
Dmytro Pivtoratskyi ◽  
◽  
Nataliia Bidnenko ◽  
Olha Dubova ◽  
Volodymyr Kaskiv ◽  
...  
Keyword(s):  
Preventive Measures ◽  
Preventive Treatment ◽  
Friction Material ◽  
International Experience ◽  
Surface Scattering ◽  
Winter Period ◽  
Winter Maintenance ◽  
The Road ◽  
Chemical Agents ◽  
Fast Development

Introduction. Maintenance of roads in winter period is a complex of works that include snow resistance, snow removal from roads and slipperiness prevention for ensure the continuous traffic. Different countries have their own approaches for elimination of winter slipperiness, but their essence can be сoncentrated on the following measures: preventive treatment of the pavement to reduce of icing or weakening the adhesion of ice and the pavement; scattering of friction material with or without chemical agents for increasing the coefficient of adhesion of the wheel to the pavement surface; scattering of chemical agents for snow and ice melting with following removal outside of the roadway.The article summarizes the analysis of international experience in elimination and prevention of winter slipperiness formation according to the data of international conferences under the aegis of PIARC.Problems. In conditions of fast development of the transport network of Ukraine the stricter requirements are needed for maintenance of roads and for ensuring the safe traffic on them. The solving of these problems in the winter period also depends of winter slipperiness preventive measures.Purpose. Informing of the road community about the international experience of winter maintenance of roads.Materials and methods. Analysis of information sources regarding the experience of winter maintenance of roads abroad. Results. Specific examples of winter slipperiness preventive measures are given.Conclusions. The experience of different countries in winter slipperiness prevention is summarized and specific examples of its elimination and recommended measures are given.Keywords:road, winter maintenance, ice, maintenance in winter period, icing, deicing materials, brine, salt, slipperiness, snow, sodium chloride

Sign in / Sign up

Export Citation Format

Share Document