scholarly journals Evaluating the Dynamic Response of the Bridge-Vehicle System considering Random Road Roughness Based on the Moment Method

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fan Feng ◽  
Fanglin Huang ◽  
Weibin Wen ◽  
Zhe Liu ◽  
Xiang Liu
Keyword(s):  
Random Process ◽  
Moment Method ◽  
System Response ◽  
Vehicle Speed ◽  
The Road ◽  
Bridge Span ◽  
Road Roughness ◽  
System Vibration ◽  
The Moment ◽  
The Impact

The bridge-vehicle interaction (BVI) system vibration is caused by the vehicles passing through the bridge. The road roughness has a great impact on the system vibration. In this regard, poor road roughness is known to affect the comfort of the vehicle crossing the bridge and aggravate the fatigue damage of the bridge. Road roughness is usually regarded as a random process in numerical calculation. To fully consider the influence of road roughness randomness on the response of the BVI system, a random BVI model was established. Thereafter, the random process of road roughness was expressed by Karhunen–Loeve expansion (KLE), after which the moment method was used to calculate the maximum probability value of the BVI system response. The proposed method has higher accuracy and efficiency than the Monte Carlo simulation (MCS) calculation method. Subsequently, the influences of vehicle speed, roughness grade, and bridge span on the impact factor (IMF) were analyzed. The results show that the road roughness grade has a greater impact on the bridge IMF than the bridge span and vehicle speed.

scholarly journals A new approach to assess the influence of road roughness on driver speed behavior based on driving simulator tests

2016 ◽  
Vol 11 (2) ◽  
pp. 144-152 ◽  
Author(s):  
Mariano Pernetti ◽  
Mauro D’Apuzzo Mauro D’Apuzzo ◽  
Francesco Galante
Keyword(s):  
Driving Simulator ◽  
Experimental Studies ◽  
Vertical Vibration ◽  
The Other ◽  
Added Value ◽  
Published Data ◽  
Vehicle Speed ◽  
Safety Level ◽  
The Road ◽  
Road Roughness

Vehicle speed is one of main parameters describing driver behavior and it is of paramount importance as it affects the travel safety level. Speed is, in turn, affected by several factors among which in-vehicle vibration may play a significant role. Most of speed reducing traffic calming countermeasures adopted nowadays rely on vertical vibration level perceived by drivers that is based on the dynamic interaction between the vehicle and the road roughness. On the other hand, this latter has to be carefully monitored and controlled as it is a key parameter in pavement managements systems since it influences riding comfort, pavement damage and Vehicle Operating Costs. There is therefore the need to analyse the trade-off between safety requirements and maintenance issues related to road roughness level. In this connection, experimental studies aimed at evaluating the potential of using road roughness in mitigating drivers’ speed in a controlled environment may provide added value in dealing with this issue. In this paper a new research methodology making use of a dynamic driver simulator operating at the TEST Laboratory in Naples is presented in order to investigate the relationship between the driver speed behavior on one hand, and the road roughness level, road alignment and environment, vehicle characteristics on the other. Following an initial calibration phase, preliminary results seem fairly promising since they comply with the published data derived from scientific literature.

Study on the Dynamic Wheel Load of Multi-Axle Vehicle Based on Distribute Loading Weight

2010 ◽  
Vol 159 ◽  
pp. 35-40
Author(s):  
Zhong Hong Dong
Keyword(s):  
Dynamic Load ◽  
Influence Factors ◽  
Vehicle Speed ◽  
Tire Pressure ◽  
Wheel Load ◽  
The Road ◽  
Road Roughness ◽  
Tire Stiffness ◽  
On The Road

To study the dynamic wheel load on the road, a dynamic multi-axle vehicle mode has been developed, which is based on distribute loading weight and treats tire stiffness as the function of tire pressure and wheel load. Taking a tractor-semitrailer as representative, the influence factors and the influence law of the dynamic load were studied. It is found that the load coefficient increases with the increase of road roughness, vehicle speed and tire pressure, yet it decreases with the increase of axle load. Combining the influences of road roughness, vehicle speed, axle load and tire pressure, the dynamic load coefficient is 1.14 for the level A road, 1.19 for the level B road, 1.27 for the level C road, and 1.36 for the level D road.

Manoeuvring speed of a 6×6 autonomous vehicle using a database obtained from multi-body dynamic simulation

2009 ◽  
Vol 223 (8) ◽  
pp. 979-985 ◽  
Author(s):  
S-L Cho ◽  
K-C Yi ◽  
J-H Lee ◽  
W-S Yoo
Keyword(s):  
Dynamic Simulation ◽  
Autonomous Vehicle ◽  
Sensor Data ◽  
Vehicle Speed ◽  
The Road ◽  
Driving Speed ◽  
Road Roughness ◽  
Motion Speed ◽  
Vertical Accelerations ◽  
Vehicle Dynamic Simulation

For an autonomous vehicle that travels off-road, the driving speed is limited by the driving circumstances. To decide on a stable manoeuvring speed, the driving system should consider road conditions such as the height of an obstacle and road roughness. In general, an autonomous vehicle has many sensors to preview road conditions, and the information gathered by these sensors can be used to find the proper path for the vehicle to avoid unavoidable obstacles. However, sensor data are insufficient for determining the optimal vehicle speed, which could be obtained from the dynamic response of the vehicle. This paper suggests an algorithm that can determine the optimal vehicle speed running over irregular rough terrains such as when travelling off-road. In the determination of the manoeuvring speed, the vehicle dynamic simulation is employed to decide whether the vehicle response is within or beyond the prescribed limits. To determine the manoeuvring speed in real time, the dynamic simulation should be finished much more quickly than the real motion speed of the vehicle. In this paper, the equation of motion of the vehicle is derived in terms of the chassis local coordinates to reduce the simulation time. The velocity transformation technique, which combines the generality of Cartesian coordinates and the efficiency of relative coordinates, was combined with a symbolic computation to enhance further the computational efficiency. First the developed algorithm calculates the level of the previewed road roughness to determine the manoeuvring speed. Then, the maximum stable speed is judged against the database, which already has stored the maximum vertical accelerations as a function of the road roughness and vehicle speed.

scholarly journals CORRELATION ANALYSIS OF DRIVING CONDITIONS AND ON-ROAD EMISSIONS TRENDS FOR VEHICLES

2017 ◽  
pp. 63-72
Author(s):  
Jawad Hilmi Al-rifai
Keyword(s):  
Vehicle Emissions ◽  
Measurement Unit ◽  
Vehicle Speed ◽  
Emission Rates ◽  
Gas Emissions ◽  
The Road ◽  
Grade Parameter ◽  
Road Grade ◽  
Driving Conditions ◽  
The Impact

This paper presents the impact of road grade, vehicle speed, number of vehicles and vehicle type on vehicle emissions. ANOVA analyses were conducted among different driving conditions and vehicle emissions to discover the significant effects of driving conditions on measured emission rates. This study is intended to improve the understanding of vehicle emission levels in Jordan. Gas emissions in real-world driving conditions were measured by a portable emissions measurement unit over six sections of an urban road. The road grade, speed, type and number of vehicles were found to have a significant influence on the rate of gas emissions. Road grade and diesel-fueled vehicles were positively correlated with average emission rates. The average emission rates were higher at speeds ranging between 60–69 km/hr than at three other speed ranges. The results of ANOVA showed a strong and consistent regression between rates of emissions measured and grade, speed and diesel vehicle parameters. The grade parameter contributed the most to the rate of emissions compared to other parameters. Gasoline vehicles contributed the least.

scholarly journals Algorithms for Particle Detection in Complex Plasmas

2019 ◽  
Vol 5 (2) ◽  
pp. 30
Author(s):  
Daniel Mohr ◽  
Christina Knapek ◽  
Peter Huber ◽  
Erich Zaehringer
Keyword(s):  
Moment Method ◽  
Granular Matter ◽  
Synthetic Data ◽  
Single Particles ◽  
Particle Detection ◽  
Threshold Detection ◽  
Video Cameras ◽  
The Moment ◽  
Complex Plasmas ◽  
The Impact

In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are required to accurately determine their positions to sub-pixel accuracy from the recorded images. Typically, a straightforward algorithm such as the moment method is used for this task. Here, we combine different variations of the moment method with common techniques for image pre- and post-processing (e.g., noise reduction and fitting), and we investigate the impact of the choice of threshold parameters, including an automatic threshold detection, on synthetic data with known attributes. The results quantitatively show that each algorithm and method has its own advantage, often depending on the problem at hand. This knowledge is applicable not only to complex plasmas, but useful for any kind of comparable image-based particle tracking, e.g., in the field of colloids or granular matter.

scholarly journals Analysis of the Impact of Traffic Violation Monitoring on the Vehicle Speeds of Urban Main Road: Taking China as an Example

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Fuquan Pan ◽  
Yongzheng Yang ◽  
Lixia Zhang ◽  
Changxi Ma ◽  
Jinshun Yang ◽  
...  
Keyword(s):  
Probability Density ◽  
Road Traffic ◽  
Maximum Speed ◽  
Vehicle Speed ◽  
Main Road ◽  
The Road ◽  
Before And After ◽  
Traffic Violation ◽  
The Impact ◽  
Monitoring Area

In recent years, there are more and more applications of traffic violation monitoring in some countries. The present work aims to analyze the vehicle speeds nearby road traffic violation monitoring area on urban main roads and find out the impact of road traffic violation monitoring on the vehicle speeds. A representative urban main road section was selected and the traffic flow was recorded by camera method. The vehicle speeds before, within, and after the road traffic violation monitoring area were obtained by the calculation method. The speed data was classified and processed by SPSS software and mathematical method to establish the vehicle speed probability density models before, within, and after the road traffic violation monitoring area. The results show that the average speed and maximum speed within the traffic violation monitoring area are significantly slower than those before and after the traffic violation monitoring area. 70.1% of the vehicles before the road traffic violation monitoring area were speeding, and 80.2% of the vehicles after the road traffic violation monitoring area were speeding, while within the road traffic violation monitoring area, the speeding vehicles were reduced to 15.9%. When vehicles pass through the road traffic violation monitoring area, the vehicle speeds tend to first decrease and subsequently increase. In its active area, road traffic violation monitoring can effectively regulate driving behaviors and reduce speeding, but this effect is limited to the vicinity of the traffic violation monitoring. The distribution of vehicle speeds can be calculated from vehicle speed probability density models.

DEVELOPMENT OF MEASURES TO IMPROVE ROAD CONDITIONS ON ROAD SECTIONS BASED ON THE ANALYSIS OF TRAFFIC CONDITIONS

2021 ◽  
Vol 2021 (24) ◽  
pp. 159-168
Author(s):  
Anatolii Palchyk ◽  
Keyword(s):  
Experimental Studies ◽  
Traffic Volume ◽  
Important Indicator ◽  
The Road ◽  
Traffic Conditions ◽  
Traffic Lane ◽  
Road Capacity ◽  
Traffic Speed ◽  
The Moment ◽  
The Impact

Introduction. The analysis of road capacity is carried out. Problem statement. One of the reasons for the appointment of the road reconstruction or part of it is the deterioration of traffic safety, resulting in an increase in the number of victims and material losses during traffic accidents. Road capacity is an important indicator during highway reconstruction. The analysis of the road section capacity makes it possible to assess the work of the road during its entire life cycle from the moment of its commissioning to the moment of reconstruction. Existing methods for determining the practical traffic lane capacity, the maximum traffic volume on the highway section give ambiguous results that need to be improved. Purpose. The purpose of the work is to study the average speed, which is one of the factors that determine the maximum traffic volume on the road. Materials and methods. Analysis of the results of experimental studies of average speeds of free movement of different type of vehicles on roads of different categories. Results. The general form of equations of dependence of average traffic speed on radii of horizontal curves and speed on a longitudinal slope is established; the impact of road conditions on the traffic speed according to the study of graphs of average speeds before and after the improvement of traffic conditions on road sections was analyzed. Conclusions. Based on the assessment of traffic conditions with the provision of maximum traffic volume on road sections between intersections and junctions, which determine the traffic volume between them, it is possible to address the need for partial or complete reconstruction of the highway. Keywords: road capacity, traffic volume, highway, intersection, junctions, traffic speed, highway reconstruction.

scholarly journals Driving Safety Analysis Using Grid-Based Water-Filled Rut Depth Distribution

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiao Yan ◽  
Hongwei Zhang ◽  
Bing Hui
Keyword(s):  
Water Depth ◽  
Three Dimensional ◽  
Element Model ◽  
Road Surface ◽  
Driving Safety ◽  
Vehicle Speed ◽  
Adhesion Coefficient ◽  
The Road ◽  
Left And Right ◽  
The Impact

The water accumulated in the rutted road sections poses a threat to the safety of vehicles. Water-filled ruts will cause partial or complete loss of the friction between tires and the road surface, leading to driving safety hazards such as hydroplaning and sliding. At present, the maximum water depth of left and right ruts is mostly adopted to analyze the safety of water-filled ruts, ignoring the uneven change of ruts in the driving direction and the cross-section direction, which cannot fully reflect the actual impact of asymmetric or uneven longitudinal ruts on the vehicle. In order to explore the impact of water-filled ruts on driving safety, a three-dimensional (3D) tire-road finite element model is established in this paper to calculate the adhesion coefficient between the tire and the road surface. Moreover, a model of the 3D water-filled rut-adhesion coefficient vehicle is established and simulated by the dynamics software CarSim. In addition, the influence of the water depth difference between the left and right ruts on the driving safety is quantitatively analyzed, and a safety prediction model for the water-filled rut is established. The results of the case study show that (1) the length of dangerous road sections based on vehicle skidding is longer than that based on hydroplaning, and the length of dangerous road sections based on hydroplaning is underestimated by 9.4%–100%; (2) as the vehicle speed drops from 120 km/h to 80 km/h, the length of dangerous road sections obtained based on vehicle sliding analysis is reduced by 93.8%. Therefore, in order to ensure driving safety, the speed limit is controlled within 80 km/h to ensure that the vehicle will not skid. The proposed method provides a good foundation for the vehicles to actively respond to the situation of the water-filled road section.

scholarly journals Online Classification of Road Roughness Conditions with Vehicle Unsprung Mass Acceleration by Sliding Time Window

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Zhongxing Li ◽  
Wenhao Yu ◽  
Xiaoli Cui
Keyword(s):  
Time Window ◽  
Vehicle Speed ◽  
The Road ◽  
Physical Measurements ◽  
Online Classification ◽  
Power Spectral ◽  
Road Roughness ◽  
The Stability ◽  
Roughness Classification ◽  
Unsprung Mass

Suspension control systems are in need for more information of road roughness conditions to improve their performance under different roads. Existing methods of gauging road roughness are limited, and they usually involve visual inspections or special vehicles equipped with instruments that can gauge physical measurements of road irregularities. This paper proposes data collection for a period of a time from accelerometers fixed on unsprung mass and uses the mean square values of this datasets divided by vehicle speed to classify the roughness conditions of a section of a road. This approach is possible due to the existence of relationships between the power spectral densities of the road surface, unsprung mass accelerations via a transfer function, and vehicle speed. This paper gave the relationship between the resolution of road roughness classification and the length of time-window and suggestions about choosing the appropriate time-window length on the balance of road roughness resolution and classification delay. Moreover, to enhance the stability of classification, the influence of damping parameters of vehicle suspension on the classification output is studied, and a classification method of road roughness is proposed based on neural network and damping coefficient correction.

scholarly journals Influence of selected ITS services on the driver’s behaviour - results of simulation test carried out on top-of-the-range driving simulators

2018 ◽  
Vol 231 ◽  
pp. 04005 ◽  
Author(s):  
Tomasz Kamiński ◽  
Małgorzata Pędzierska ◽  
Przemysław Filipek
Keyword(s):  
Simulation Software ◽  
Vehicle Speed ◽  
Driving Simulators ◽  
The Road ◽  
Additional Information ◽  
Road Users ◽  
Road Section ◽  
Variable Content ◽  
Series Of Experiments ◽  
The Impact

The publication is a summary of the test results, using top-of-the-range driving simulators in RID 4D project. Experiment methodology and example of research results were presented in the article entitled: "The use of simulator studies to assess the impact of ITS services on the behaviour of the road users". The project was implemented as part of the Road Innovation Development (RID) program organized and financed by the National Centre for Research and Development and General Directorate of National Roads and Motorways (contract No. DZP/RID-I-41/7/NCBR/2016). The results of the research were used to assess the impact of ITS services on the driver’s behaviour and to calibrate the simulation software Visum/Saturn/Vissim. The result of a series of experiments is a set of data including speed, speed changes, the length of the road section on which the driver maintained constant speed and additional information on the driver’s behaviour. Information for the drivers was presented on boards and signs of variable content. The vehicle speed was analyzed along a distance of 200 m, 30 m, and then at the location spot of the variable content sign/board and 200 m after the sign. The data was also recorded in the case of the traditional speed-limiting sign.

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