scholarly journals Theoretical and practical methodology for recognizing the road surface structure

2019 ◽  
Vol 17 (4) ◽  
pp. 035-045
Author(s):  
Stefan Firlej ◽  
Marcin Dębiński

A recognition indicator of the possibility of further use of the road during transferring transport loads are changes in the condition of the road surface. If the surface condition indicates incorrect parameters of its equality, rutting, or cracks, the road durability is qualitatively assessed. In this case, the actual load capacity rating and possible reconstruction of the structure begins. Values of dynamic defl ections can be used to recognize the modulus of elasticity and thus the possibility of assessing the durability of a structure. The mechanistic method is used to dimensioning the structure due to the movement planned. It allows a fl exible approach to further construction, giving the opportunity to assess whether part or all of it should be left or apply an additional layer to meet future requirements. The elastic modulus needed for this pavement structure design method for existing layers has been recognized by identifi cation as backcalculation methodology that have been used for many years.

2021 ◽  
Vol 2113 (1) ◽  
pp. 012080
Author(s):  
Xiuhao Xi ◽  
Jun Xiao ◽  
Qiang Zhang ◽  
Yanchao Wang

Abstract For the problem of road surface condition recognition, this paper proposes a real-time tracking method to estimate road surface slope and adhesion coefficient. Based on the fusion of dynamics and kinematics, the current road slope of the vehicle which correct vertical load is estimated. The effect of the noise from dynamic and kinematic methods on the estimation results is removed by designing a filter. The normalized longitudinal force and lateral force are calculated by Dugoff tire model, and the Jacobian matrix of the vector function of the process equation is obtained by combining the relevant theory of EKF algorithm. The road adhesion coefficient is estimated finally. The effectiveness of the algorithm is demonstrated by analyzing the results under different operating conditions, such as docking road and bisectional road, using a joint simulation of Matlab/Simulink and Carsim.


2009 ◽  
Vol 48 (12) ◽  
pp. 2513-2527 ◽  
Author(s):  
L. Bouilloud ◽  
E. Martin ◽  
F. Habets ◽  
A. Boone ◽  
P. Le Moigne ◽  
...  

Abstract A numerical model designed to simulate the evolution of a snow layer on a road surface was forced by meteorological forecasts so as to assess its potential for use within an operational suite for road management in winter. The suite is intended for use throughout France, even in areas where no observations of surface conditions are available. It relies on short-term meteorological forecasts and long-term simulations of surface conditions using spatialized meteorological data to provide the initial conditions. The prediction of road surface conditions (road surface temperature and presence of snow on the road) was tested at an experimental site using data from a comprehensive experimental field campaign. The results were satisfactory, with detection of the majority of snow and negative road surface temperature events. The model was then extended to all of France with an 8-km grid resolution, using forcing data from a real-time meteorological analysis system. Many events with snow on the roads were simulated for the 2004/05 winter. Results for road surface temperature were checked against road station data from several highways, and results for the presence of snow on the road were checked against measurements from the Météo-France weather station network.


Author(s):  
Andrii Siedov ◽  
Olena Fomenko

Abstract. The emergence of a large number of modern high-speed cars with improved dynamic characteristics and an increase in the share of cars, especially large load capacity, have significantly accelerated the destruction of asphalt roads. Plastic deformations, tracks and cracks are more and more often observed on asphalt concrete pavements of roads, their wear is accelerated. As a result, the transport and operational condition of roads deteriorates, the speed of traffic decreases, the cost of road transport increases, and increasing costs are required for road repairs. Thus, the conditions of traction of the wheels of the car with the road surface are influenced by the service life of the coating, traffic intensity, the amount of harmful emissions of industrial enterprises and climatic factors. At the same time uneven change of conditions of coupling in cross and longitudinal profiles of the highway comes to light. Analyzing the natural and climatic factors, we can establish that different weather conditions have different effects on the condition of the road surface. In summer, the condition of the surface is dry and clean, so the driving conditions are safe. Taking into account all the factors that lead to the destruction of the coating with the formation of residual deformations and irreversible changes, requires the study of wear of the coating surface. he wear of the coating largely depends on the friction force in the area of contact of the tire with the surface of the coating, the type of tires and the pressure in the tires. But the random nature of changes in the intensity and composition of traffic, seasons, temperature, humidity, rainfall affects the amount of wear over a period of operation of the road surface. The presence of water or solutions in the pores of the coating leads to the separation of mineral particles from the layer under the action of impact force from the wheels of vehicles. It is experimentally established that the wear of asphalt concrete in the dry and wet state increases with increasing temperature. One of the main types of damage to road surfaces is their premature wear under the influence of vehicle wheels, in combination with changing weather conditions. Analyzing the natural and climatic factors, we can establish that different weather conditions have different effects on the condition of the road surface. The article considers the influence of temperature, humidity and the presence of solutions of chloride anti-icing materials on the process of abrasion of asphalt pavement in the autumn-winter period. Occurrence of big differences of temperature and humidity accelerates processes of aging of materials from which layers are made, influencing their durability and wear resistance.


2017 ◽  
Vol 2 (20) ◽  
pp. 111-129
Author(s):  
Artur Plichta ◽  
Adam Piasecki

Within the road investments the very important element determining repeatedly the success of the whole project is an adequate information about the characteristics of the site, its load capacity, stability and the possible impact of geological characteristics that may interfere with subsequent service life, not only for the road surface itself, but also for the surrounded objects. The surface is incessantly influenced by geological characteristics, determining its durability and functional usefulness. The main aim of this paper is to answer the question how by the usage of modern technics for obtaining data it is possible to find a link confirming the characteristics of land on which the specific road projects are supposed to be carried out, or where these projects have already been accomplished, concerning their requirements with high accuracy of location and also the stability and durability of the ground. This article makes also an attempt to answer not only the question how to identify the construction of road surface, but also how to locate underground cavities, created or influenced by the flow of water, or due to geological structures characterized as an inconsistent ground. The results were supported with geophysical researches using GPR method, and also data collected with laser scanners.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
QiMing Wang ◽  
JinMing Xu ◽  
Tao Sun ◽  
ZhiChao Lv ◽  
GaoQiang Zong

Automotive intelligence has become a revolutionary trend in automotive technology. Complex road driving conditions directly affect driving safety and comfort. Therefore, by improving the recognition accuracy of road type or road adhesion coefficient, the ability of vehicles to perceive the surrounding environment will be enhanced. This will further contribute to vehicle intelligence. In this paper, considering that the process of manually extracting image features is complicated and that the extraction method is random for everyone, road surface condition identification method based on an improved ALexNet model, namely, the road surface recognition model (RSRM), is proposed. First, the ALexNet network model is pretrained on the ImageNet dataset offline. Second, the weights of the shallow network structure after training, including the convolutional layer, are saved and migrated to the proposed model. In addition, the fully connected layer fixed to the shallow network is replaced by 2 to 3, which improves the training accuracy and shortens the training time. Finally, the traditional machine learning and improved ALexNet model are compared, focusing on adaptability, prediction output, and error performance, among others. The results show that the accuracy of the proposed model is better than that of the traditional machine learning method by 10% and the ALexNet model by 3%, and it is 0.3 h faster than ALexNet in training speed. It is verified that RSRM effectively improves the network training speed and accuracy of road image recognition.


2021 ◽  
Vol 22 ◽  
pp. 17
Author(s):  
Ali Shahabi ◽  
Amir Hossein Kazemian ◽  
Said Farahat ◽  
Faramarz Sarhaddi

In this study, the vehicle's dynamic behavior during braking and steering input is investigated by considering the quarter-car model. The case study for this research is a Sport-Utility Vehicle (SUV) with the anti-lock braking system (ABS) and nonlinear dynamic equations are considered for it along with Pacejka tire model. Regulating the wheel slip ratio in the optimal value for different conditions of the road surface (dry, wet and icy) during braking is considered as the ABS control strategy. In order to regulating the wheel slip ratio in the optimal value, an intelligent adaptive fuzzy controller that can perform online parameter estimation is considered. In this regard, the proposed controller tracks the optimal wheel slip ratio with changing the condition of the road surface from dry to wet and icy. The adaptive fuzzy controller consists of linguistic base, inference engine and defuzzifier section. The wheel slip ratio and vehicle longitudinal acceleration are selected as inputs of the controller, controller adapter and detector of the road surface condition. During braking and steering input, effective parameters of the wheel that are affected on the vehicle's dynamic behavior and its stability are investigated.


2021 ◽  
Author(s):  
Shahram Sattar

Road surface monitoring is a key factor in providing safe road infrastructure for road users. As a result, road surface condition monitoring aims to detect road surface anomalies such potholes, cracks and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road rehabilitation and maintenance. Several studies have been developed to utilize smartphone sensors (e.g., Global Positioning system (GPS) and accelerometers) mounted on a moving vehicle to collect and process the data to monitor and tag roadway surface defects. Geotagged images or videos from the roadways have also been used to detect the road surface anomalies. However, existing studies are limited to identifying roadway anomalies mainly from a single source or lack the utility of combined and integrated multi-sensors in terms of accuracy and functionality. Therefore, low-cost, more efficient pavement evaluation technologies and a centralized information system are necessary to provide the most up-to-date information about the road status due to the dynamic changes on the road surface This information will assist transportation authorities to monitor and enhance the road surface condition. In this research, a probabilistic-based crowdsourcing technique is developed to detect road surface anomalies from smartphone sensors such as linear accelerometers, gyroscopes and GPS to integrate multiple detections accurately. All case studies from the proposed detection approach showed an approximate 80% detection accuracy (from a single survey) which supports the inclusiveness of the detection approach. In addition, the results of the proposed probabilistic-based integration approach indicated that the detection accuracy can be further improved by 5 to 20% with multiple detections conducted by the same vehicle along the same road segments. Finally, the development of the web-based Geographic Information System (GIS) platform would facilitate the real-time and active monitoring of road surface anomalies and offer further improvement of road surface quality control in large cities like Toronto.


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