Rough Road Conditions Research Articles

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

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.

Vibration Analysis on Car seats due to Rough and Smooth Road conditions

Vibration Analysis on Car seats due to Rough and Smooth Road conditions

Vibration Analysis on Car Steering Due to Smooth and Rough Road Condition

Vibration Analysis on Car Steering Due to Smooth and Rough Road Condition

Lifetime Deflections of Long-Span Bridges under Dynamic and Growing Traffic Loads

Steady traffic growth may pose a safety hazard to in-service bridges, especially long-span bridges subjected to the simultaneous presence of multiple heavy-duty trucks. This study presents a methodology for evaluating the statistical extrapolation of traffic-load effects on long-span bridges. As part of the contributions advancing the state of the art, this study addresses several challenging issues, including traffic growth, and the resulting dynamic impact, and actual traffic patterns. The nonstationarity of the traffic-load effects due to traffic growth is considered in a series system compounded by several interval traffic models. The dynamic impacts of traffic loads were simulated by a traffic-bridge-coupled vibration system, and the statistical characteristics were captured using a level-crossing model. The actual traffic pattern was simulated by stochastic traffic flows on the basis of the statistics of the weigh-in-motion measurements of a highway bridge. Two numerical examples show the ability of the interval-traffic-growth model to capture the nonstationarity of the growing traffic loads. In addition, a case study of a long-span suspension bridge shows the effectiveness of implementing the proposed methodology for the statistical extrapolation of the maximum deflection. The numerical results of the case study also reveal that the degradation of road-roughness conditions leads to more level crossings but also results in a slight increase in the extrapolation of the deflection. However, traffic growth results in rapid increases in both the extrapolated deflection and the probability of exceedance of the deflection limit.

Vertical vibrations of a bridge based on the traffic-pavement-bridge coupled system

When studying the vibration of a suspension bridge based on the traffic-bridge coupled system, most researchers ignored the contribution of the pavement response. For example, the pavement was simplified as a rigid base and the deformation of pavement was ignored. However, the action of deck pavement on the vibration of vehicles or bridges should not be neglected. This study is mainly focused on establishing a new methodology fully considering the effects of bridge deck pavement, probabilistic traffic flows, and varied road roughness conditions. The bridge deck pavement was modeled as a boundless Euler-Bernoulli beam supported on the Kelvin model; the typical traffic flows were simulated by the improved Cellular Automaton (CA) traffic flow model; and the traffic-pavement-bridge coupled equations were established by combining the equations of motion of the vehicles, pavement, and bridge using the displacement and interaction force relationship at the contact locations. The numerical studies show that the proposed method can more rationally simulate the effect of the pavement on the vibrations of bridge and vehicles.

Lifetime fatigue reliability evaluation of short to medium span bridges under site-specific stochastic truck loading

Bridges are vulnerable to the fatigue damage accumulation caused by traffic loading over the service period. A continuous growth in both the vehicle weight and the traffic volume may cause a safety hazard to existing bridges. This study presented a computational framework for probabilistic modeling of the fatigue damage accumulation of short to medium span bridges under actual traffic loading. Stochastic truck-load models were simulated based on site-specific weigh-in-motion measurements. A response surface method was utilized to substitute the time-consuming finite element model for an efficient computation. A case study of a simply supported bridge demonstrated the effectiveness of the computational framework. Numerical results show that the simulated fatigue stress spectrum captures the probability density functions of the heavy traffic loading. The equivalent fatigue stress range increases mostly linearly in the good road roughness condition with the growth of the gross vehicle weight. The vehicle typ...

Lifetime fatigue reliability evaluation of short to medium span bridges under site-specific stochastic truck loading

Bridges are vulnerable to the fatigue damage accumulation caused by traffic loading over the service period. A continuous growth in both the vehicle weight and the traffic volume may cause a safety hazard to existing bridges. This study presented a computational framework for probabilistic modeling of the fatigue damage accumulation of short to medium span bridges under actual traffic loading. Stochastic truck-load models were simulated based on site-specific weigh-in-motion measurements. A response surface method was utilized to substitute the time-consuming finite element model for an efficient computation. A case study of a simply supported bridge demonstrated the effectiveness of the computational framework. Numerical results show that the simulated fatigue stress spectrum captures the probability density functions of the heavy traffic loading. The equivalent fatigue stress range increases mostly linearly in the good road roughness condition with the growth of the gross vehicle weight. The vehicle type and the road roughness condition affect the stress range. The influence of the driving speed on the equivalent stress range is non-monotonic. The bridge fatigue reliability has a considerable increase even under a relatively high overload limit. It is anticipated that the proposed computational framework can be applied for more types of bridges.

カーナビゲーションシステムが記録した加速度による路面性状のモニタリングに向けた基礎的検討

This study aims to develop a numerical model to evaluate the road roughness condition using acceleration time histories recorded by car navigation systems. The acceleration record of transverse component of the vehicle is employed to detect the road sections with the international roughness index (IRI) of 12 mm/m or above. To achieve the objective, the IRI was measured with the interval of 10 m in Yokohama City and Chofu City. The relationship between the IRI and the accelerations recorded by car navigation system was evaluated, and logistic regression analyses were performed. The discrimination ability of the numerical model was revealed, and the model was applied to the acceleration time histories accumulated in March, 2015.

Measuring and evaluating of road roughness conditions with a compact road profiler and ArcGIS

With a wide range of requirements throughout the world, high-quality road management is subject to increasing demand from a perspective of customer-oriented levels of service. In recent years, road administrators are requested to create a visual map of a road network to monitor conditions. To fulfill these requirements, this study conducted as follows. Firstly, this paper introduces a new compact road profiler to collect the profile data at ease. Using the international roughness index (IRI) to assess public roads in local cities of Japan's Hokkaido prefecture, this study also provides real-time monitoring of pavement roughness conditions. Moreover, this study deals with an effective method for visualizing collected IRI data as an attribute in a geographic information system (GIS) and the database of Japan digital road map (DRM). Secondly, the authors present the measurement results of IRI at two different cities during different seasons by using GIS to compare the road conditions. According to the results clarified on different statistical characteristics of road profiles, this study recommends that it is necessary to establish pavement management system (PMS) in consideration of road class, network of local city, and evaluation and management of road conditions in winter quantitatively. Finally, the authors measure and evaluate ride quality by assessing differences between the inner wheel path (IWP) and outer wheel path (OWP) of the vehicle into account, using the previously mentioned profilers and the driving simulator, which is called KITDS. Results show that information from both wheel paths contributes to improve current monitoring process regarding pavement surface, and expects to construct a high level of PMS for road administration in the future.

Three-Dimensional Vibrations of a Suspension Bridge Under Stochastic Traffic Flows and Road Roughness

When studying the vibration of a bridge–vehicle coupled system, most researchers mainly focus on the vertical vibration of bridges under moving vehicular loads, while the lateral and longitudinal vibrations of the bridges and the stochastic characteristics of the traffic flows are neglected. However, for long-span suspension bridges, neglecting the bridge’s three-dimensional (3D) vibrations under stochastic traffic flows can cause considerable inaccuracy in predicting the dynamic performance. This study is mainly focused on establishing a new methodology fully considering a suspension bridge’s vertical, lateral, and longitudinal vibrations induced by stochastic traffic flows under varied road roughness conditions. A new full-scale vehicle model with 18 degrees of freedom (DOFs) was developed to predict the longitudinal and lateral vibrations of the vehicle. An improved Cellular Automaton (CA) model considering the influence of the next-nearest vehicle was introduced. The bridge and vehicles in traffic flow coupled equations are established by combining the equations of motion of both the bridge and vehicles using the displacement relationship and interaction force relationship at the patch contacts. The numerical simulations show that the proposed method can rationally simulate the 3D vibrations of the suspension bridge under stochastic traffic flows.

STUDY ON THE ROAD TRANSMITTED VIBRATION OF A MOUNTAIN BICYCLE

Mountain bicycle (MTB) is one the most favorite vehicles in the globe. MTB comfort, in consequence, has then become a challenge issue to the manufacturers since MTB nowadays is not only being used for sports and exercises, but also for daily activities. One of the simplest methods to assess vehicle comfort is by evaluating their vibration level. Thus, this paper presents an experimental assessment on the road transmitted vibration on a MTB through a field test subjected to different road surface conditions and tire sizes. The result shows that the cycling comfort is significantly affected by the road roughness condition and tire size. As the road is rougher, higher force excitation is generated to the bike which is then generating higher vibration. Similarly, as the contact area between the tire and the road is increased, bike vibration is also significantly increased.

Adaptive Road Profile Estimation in Semiactive Car Suspensions

The enhancement of passengers’ comfort and their safety are part of the constant concerns for car manufacturers. Semiactive damping control systems have emerged to adapt the suspension features, where the road profile is one of the most important factors determining the automotive vehicle performance. Because direct measurements of the road profile represent expensive solutions and are susceptible to contamination (e.g. using laser and other visual sensors), this paper proposes a novel road profile estimator that offers the essential information (road roughness and its frequency) for the adjustment of the vehicle dynamics using conventional sensors, such as accelerometers or displacement/velocity sensors easy to mount, cheap, and useful to estimate all suspension variables. Based on the ${Q}$ -parametrization approach, an adaptive observer estimates the dynamic road signal; afterward, a Fourier analysis is used to compute the road roughness condition online and to perform an International Organization for Standardization (ISO) 8608 classification. Experimental results on the rear-left corner of a 1:5 scale vehicle, equipped with electro-rheological (ER) dampers, have been used to validate the proposed road profile estimation method. Different ISO road classes evaluate the performance of the proposed algorithm, whose results show that any road can be identified successfully at least 70% of the time with a false alarm rate lower than 5%; the general accuracy of the road classifier is 95%. A second test with variable vehicle velocity shows the importance of the online frequency estimation to adapt the road estimation algorithm to any driving velocity; in this test, the road is correctly estimated in 868 of 1042 m (an error of 16.7%). Finally, the adaptability of the parametric road estimator to the semiactiveness property of the ER damper is tested at different damping coefficients.

Hierarchical Control Strategy for Active Hydropneumatic Suspension Vehicles Based on Genetic Algorithms

A new hierarchical control strategy for active hydropneumatic suspension systems is proposed. This strategy considers the dynamic characteristics of the actuator. The top hierarchy controller uses a combined control scheme: a genetic algorithm- (GA-) based self-tuning proportional-integral-derivative controller and a fuzzy logic controller. For practical implementations of the proposed control scheme, a GA-based self-learning process is initiated only when the defined performance index of vehicle dynamics exceeds a certain debounce time threshold. The designed control algorithm is implemented on a virtual prototype and cosimulations are performed with different road disturbance inputs. Cosimulation results show that the active hydropneumatic suspension system designed in this study significantly improves riding comfort characteristics of vehicles. The robustness and adaptability of the proposed controller are also examined when the control system is subjected to extremely rough road conditions.

Fatigue life prediction of heavy vehicle suspension system under varying load conditions

Leaf spring experiences frequent cyclic loading during working conditions. When design stage itself it is very essential to assess the fatigue life of the suspension system. It is important to consider and evaluate the key aspects of fatigue failure and life by using Finite Element Analysis (FEA) techniques to overcome these failures. This paper serves to stimulate the premature failure of the existing and proposed bracket model with generalized force elements under dynamic load conditions. Scanning Electron Microscope (SEM) was used to identify the bracket failure prone areas which indicate that the cyclic load in the suspension system is caused by rural area road-induced vibrations and bumps. This contributes to the increase of the fatigue fracture, which ends up with a bracket failure. The results indicated that the fatigue life of existing bracket is low for rough road conditions; the modified bracket has been optimized for the safe load conditions of the heavy vehicle suspension system

상용차 시트용 X-형 구조 마그네틱 현가기구의 최적 설계 및 성능평가

Commercial vehicle drivers typically feel more fatigued compared to general-public drivers. because they spend longer periods of time driving and experience more rough road conditions. This study showed that the application of a magnet, a linear spring, and a seat suspension with nonlinear characteristics was the optimal design to increase comfort while driving. The resonant frequency for the optimal design suspension was 2.8 Hz, and the stiffness was analyzed through displacement-load experiments. Vibration transmissibility was analyzed by suspension stiffness and the existing dynamic compression. The magnetic spring type was at 0.875. As a result, the X-type magnetic spring performed better than the existing spring at 0.729.

A study on the use of smartphones under realistic settings to estimate road roughness condition

Almost every today's smartphone is integrated with many useful sensors. The sensors are originally designed to make the smartphones' user interface and applications more convenient and appealing. These sensors, moreover, are potentially useful for many other applications in different fields. Using smartphone sensors to estimate road roughness condition has a great potential, since many similar sensors are already in use in many sophisticated road roughness profilers. This study explores the use of data, collected by sensors from smartphones under realistic settings, in which the smartphones are placed at more realistic locations and under realistic manner inside a moving vehicle, to evaluate its relationship with the actual road pavement roughness. An experiment has been conducted to collect data from smartphone acceleration and Global Positioning System (GPS) sensors; frequency domain analysis is also carried out. It has been revealed that the data from smartphone accelerometers has a linear relationship with road roughness condition, whereas the strength of the relationship varies at different frequency ranges. The results of this paper also confirm that smartphone sensors have a great potential to be used for estimating the current status of the road pavement condition.

Developed Driving Cycles for a Passenger Vehicle in Khon Kaen

Traction forces that vehicles use to propel their wheels depend on efficiencies of motors, power transmissions, and vehicle constructions. Behavior of driver on acceleration or deceleration varies responding to road conditions, traffic lights, and driving styles. Average speed estimation of the vehicle under known road conditions can be obtained from the standard driving cycles such as the urban driving cycle by NEDC and the highway fuel economy test cycle (HWFET) by EPA. An urban area, Khon Kaen province located in Northeastern part of Thailand, mostly has flat and rough road conditions that have not been well recorded. In this study a GPS device was installed on a midsize vehicle to record speed and time on roundtrip test drives. In this paper, the data on speed of the vehicle traveled from Department of Electrical Engineering, Khon Kaen University to four nearby locations were investigated than compared with standard driving cycles. These data offer greater knowledge and development in power consumption of electric vehicles and transportation sector.

A Study on the Use of Smartphones for Road Roughness Condition Estimation

Understanding condition of road surface is very important especially for road maintenance and asset management. There are many approaches to obtain road surface condition data, however almost all of them are either low speed with intensive human intervention techniques (visual inspection) or techniques that require advanced measurement equipment (sophisticated profilers), which usually comes with high costs and requiring skillful operators. Using smartphone to collect data is a promising alternative because of its low cost and easy to use features in addition to its potentially wide population coverage as probe devices. This paper explores features and relationship of acceleration vibration that may be useful to express or estimate road roughness condition, which is the main focusing road surface condition for this paper. Results from our experiment and analysis show that acceleration data collected by smartphone sensors at different driving speeds has different significant linear relationships with road roughness condition.

An Experimental Study on Impact of Hard Damper Setting on ABS-Braking Performance Through Brake Pressure Changes Under Rough Road Conditions#

In this study, the effects of hard damper setting on ABS braking performance have been experimentally investigated by taking brake pressure changes as a reference. For this aim, ABS tests have been conducted under wet and slippery rough road conditions by using medium-hard and hard dampers. In order to assess the test results, three braking maneuvers are considered. Test results show that hard damper setting improves ABS-braking performance under slippery road condition, while it deteriorates with wet road condition because of brake pressure oscillations occurring in vehicle body, axle and brake pressure pumping resonances. For this reason, the hard setting causes the bad braking performance during transition from slippery to wet road conditions.

Fatigue Reliability Assessment for Long-Span Bridges under Combined Dynamic Loads from Winds and Vehicles

During a bridge’s life cycle, the stresses from multiple dynamic loads might be superposed and progressive fatigue damage might accumulate and induce serious fatigue damage issues. This paper presents a comprehensive framework for fatigue reliability analysis of long-span bridges under combined dynamic loads from vehicles and wind. After modeling the complicated structure details with equivalent orthotropic material, dynamic stress ranges of a long-span bridge are obtained via solving the equations of motion for the vehicle-bridge-wind dynamic system with multiple random variables considered, for instance, vehicle speed, road roughness conditions, and wind velocity and direction. After counting the number of stress cycles at different stress range levels using the rain flow counting method, fatigue damage increments are obtained using the fatigue damage accumulation rule. The probability of failure for the fatigue damage at the end of each block of stress cycles and the cumulative probability of failure can be obtained. As a result, the fatigue life and reliability for the given structure details can be obtained. Based on the results from a case study, the dynamic effects from vehicles are found to be relatively small for long-span bridges and the effects from vehicle speeds and road roughness conditions can be neglected. Nevertheless, even though the stresses from either the vehicle loads or wind loads may not be able to induce serious fatigue problems alone, the superposed dynamic stress ranges cannot be ignored for fatigue reliability assessment of long-span bridges.