Effect Of Vehicle Velocity Research Articles

Study of the influence of lateral forces and velocity on the lateral dynamics of automobile

Stability of a car's trajectory of motion is the ability of a car to retain its required state of motion, under different conditions of motion. Depending on different states of motion, cars can lose direction of motion instability when there is a lateral force, due to vehicle speed, due to turning or braking the road with different grip coefficients on the sides of the wheel. In such complex moving conditions, cars need to keep a stable trajectory of movement under the driver's control. The paper examines the stability of the car's trajectory in linear motion conditions with the influence of lateral forces and the velocity of the vehicle, these two factors act to change the state of movement of the vehicle, which significantly affects the safety of the vehicle's movement. The authors looked at the effect of vehicle velocity and lateral forces on vehicle transverse dynamics: lateral forces caused by horizontal winds, inclination of the road surface, speed of movement of the vehicle acting on the entire body create centrifugal inertial forces; this force acts to cause the tires to deform. At this point the vehicle is shifted from its original trajectory. In the research content, the authors built a lateral Dynamics Model, in which the influencing factors are set as inputs to the model including vehicle velocity and transverse wind forces, output is the rotation angle of the body, transverse acceleration and horizontal displacement of the vehicle. The simulation results showed that the effect of vehicle speed was relatively large: lateral displacement increased by 228 % at a speed of 120 km/h. Therefore, when driving on the highway, there should always be driver control to ensure that the car does not deviate from the lane

Evaluation of risk injury in pedestrians’ head and chest region during collision with an autonomous bus

Autonomous vehicle (AV) can detect pedestrians with high accuracy by utilising various sensors. Although it is an undesirable condition, traffic crashes can occur if any sensor misfunctions. This paper focuses to measure the severity of pedestrian injury during autonomous bus-pedestrian crashes via finite element simulation as pedestrians are very vulnerable in traffic crashes. Two types of vehicle impact were considered (frontal and side), and risk injury in head and chest region were evaluated. Effect of vehicle velocity (ranging from 5–10 m/s) on risk probability were evaluated. It was found that higher velocity caused more damage to pedestrian body, and frontal impact was more severe than the side impact. Maximum values of head-injury-criteria and chest acceleration were 248 and 36 g, respectively, when vehicle speed was 10 m/s. AV developers can use these results to implement a safer AV design and reduce pedestrian risk injury.

Tire-pavement friction modeling considering pavement texture and water film

The accurate estimation of tire-pavement friction, especially under wet conditions, is critical to ensure pavement safety. For this purpose, this paper develops a modified tire-pavement friction model which takes the effect of pavement texture and water film into consideration. The influence of pavement texture is quantified by a newly proposed parameter called texture influence coefficient, which is related to the real contact patch of tire-pavement. The water effect is calculated from two parts, namely lubrication effect and hydrodynamic effect. Based on these two steps, a modified average lumped LuGre (ALL) model is developed. The proposed model is calibrated and verified by GripTester data collected under different vehicle velocities and water film thicknesses. The root mean square error between the calculated value of the model and the measured value is 0.023. In addition, the effects of vehicle velocity, slip rate, water film thickness, and pavement type on the friction coefficient are analyzed by numerical calculation. The results show that the friction coefficient reaches the maximum when the slip rate is in the range of [0.15, 0.20]. The increases in the vehicle speed and water film thickness will lead to the decrease in the friction coefficient. Besides, in thin water film (<1 millimeter) conditions, the deterioration effect of water film thickness on the friction coefficient is more remarkable. The results prove that the modified tire-pavement friction model provides a precise and reliable way to estimate the friction coefficient of pavement, which can assist the pavement management systems in risk warning and safety guarantee.

A vehicle-bridge interaction vibration model considering bridge deck pavement

The bridge pavement subjected to vehicle loads is the most vulnerable component in the highway bridge and overloaded vehicles can result in serious damage to the bridge pavement more easily. Therefore, it is necessary to consider the pavement in vehicle-bridge interaction (VBI) system. However, the bridge pavement is not considered in the traditional VBI system or the viscoelasticity of bridge pavement is ignored. In this study, a new vehicle-pavement-bridge interaction (VPBI) system is established. The viscoelastic asphalt pavement is simulated with the continuously and uniformly distributed spring-damper. The equivalent stiffness coefficient and equivalent damping coefficient of the pavement are determined through dynamic mechanical analysis (DMA) test and finite element method. The equations of motion for VPBI system can be derived using Lagrange equation and the modal superposition method. Then the crucial parameters such as displacement at mid-span of bridge, acceleration of vehicle body, tire contact force, and pavement deformation are obtained. The effects of vehicle velocity, bridge span, tire contact area, pavement stiffness coefficient, and pavement damping coefficient on VPBI responses are analyzed. The results show that (1) The pavement is compressive during vehicle passing bridge and its dynamic deformation fluctuates around initially static deformation of pavement. (2) Increasing the stiffness of pavement can rapidly reduce the deformation of pavement, while the pavement damping has the opposite effect. (3) The increase of bridge span can conduct exponentially growth of dynamic responses of VPBI system. The pavement deformation will increase by 7.9% if the bridge span is lengthened by 5 m. This study provides a reliability response analysis method for VPBI system.

Obtaining vehicle parameters from bridge dynamic response: a combined semi-analytical and particle filtering approach

Dynamic load imposed on the bridge by moving vehicle depends on several bridge–vehicle parameters with various uncertainties. In the present paper, particle filter technique based on conditional probability has been used to identify vehicle mass, suspension stiffness, and damping including tyre parameters from simulated bridge accelerations at different locations. A closed-form expression is derived to generate independent response samples for the idealized bridge–vehicle coupled system considering spatially non-homogeneous pavement unevenness. Thereafter, it is interfaced with the iterative process of particle filtering algorithm. The generated response samples are contaminated by adding artificial noise in order to reflect field condition. The mean acceleration time history is utilized in particle filtering technique. The vehicle-imposed dynamic load is reconstructed with the identified parameters and compared with the simulated results. The present identification technique is examined in the presence of different levels of artificial noise with bridge response simulated at different locations. The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.

The effect of vehicle velocity and drift angle on through-body AUV tunnel thruster performance

New applications of streamlined Autonomous Underwater Vehicles require an AUV capable of completing missions with both high-speed straight-line runs and slow maneuvers or station keeping tasks. At low, or zero, forward speeds, the AUV's control surfaces become ineffective. To improve an AUV's low speed maneuverability, while maintaining a low drag profile, through-body tunnel thrusters have become a popular addition to modern AUV systems. The effect of forward vehicle motion and sideslip on these types of thrusters is not well understood. In order to characterize these effects and to adapt existing tunnel thruster models to include them, an experimental system was constructed. This system includes a transverse tunnel thruster mounted in a streamlined AUV. A 6-axis load cell mounted internally was used to measure the thrust directly. The AUV was mounted in Memorial University of Newfoundland's tow tank, and several tests were run to characterize the effect of vehicle motion on the transient and steady state thruster performance. Finally, a thruster model was modified to include these effects.

Effect of Vehicle Velocity on the Dynamic Amplification of Two Vehicles Crossing a Simply Supported Bridge

The effect of multiple vehicles on a bridge’s dynamic amplification is a complex problem. Previously writers have examined multiple vehicle presence by constructing elaborate finite element models or undertaking field tests. Although both these methods give valuable information regarding the magnitude of dynamic amplification, the results tend to be site specific and give limited insight into how large amplifications occur. This paper examines the dynamic amplification factor of a simply supported bridge being crossed by two loads traveling in both the same and opposing directions. Simple numerical point load models are used to determine the critical load velocities and load positions that result in high amplifications. An experimentally validated finite element model is used to examine the applicability of the conclusions to real bridge/vehicle systems.

平面交通振動の加振力特性に関する研究 その2 移動振源効果と連成効果の検討

平面交通振動の加振力特性に関する研究 その2 移動振源効果と連成効果の検討

OPTIMUM DESIGN OF A PASSIVE SUSPENSION SYSTEM OF A VEHICLE SUBJECTED TO ACTUAL RANDOM ROAD EXCITATIONS

Vehicles are subjected to random excitation due to road unevenness and variable velocity. In most research work reported earlier, the response analysis for Mean Square Acceleration Response (MSAR) has been carried out by considering the power spectral density (PSD) of the road excitation as white noise, and the velocity of the vehicle as constant. However, in the present paper the PSD of the actual road excitation has been found to follow an approximately exponentially decreasing curve. Also the change in vehicle velocity has a significant effect on the values of Root Mean Square Acceleration Response (RMSAR). Therefore, in this work, the RMSAR of a vehicle dynamic system subjected to actual random road excitations is obtained so as to account for the effect of the actual PSD of road excitation and the frequent changes in vehicle velocity. The RMSAR of the vehicle is calculated for actual field excitation using the Fast Fourier Transformation (FFT) technique to obtain the PSD, by recording observations at the rear wheel. The effect of time lag due to wheelbase on the RMSAR of the vehicle is studied. For this purpose, a new ratio α(τ) has been introduced. The relationship between α(τ) and the autocorrelation has been formulated. This ratio is useful for considering the effect of time lag due to wheelbase on RMSAR. Similarly, the effect of vehicle velocity on the RMSAR is obtained.Further, from a ride comfort point of view, the values of the design variables like spring stiffness and viscous damping coefficient of the front and rear suspensions have been obtained, by minimising the RMSAR using the desired boundary values of the vertical RMSAR as specified in the chart of ISO 2631, 1985(E) [1].

Dynamic response of cable-stayed bridges to moving vehicles using the structural impedance method

The importance of dynamic interactions between cable-stayed bridges and heavy moving vehicles, such as trucks and locomotives, has been recognised by bridge engineers for a long time. A structural impedance algorithm is developed for analysing the dynamic response of cable-stayed bridges subjected to traversing vehicles. The bridge deck is modelled as an elastic plate, and the cables are idealised as springs for simplicity. The vehicles are modelled as a series of masses with suspension systems moving with different speeds and accelerations. A comprehensive computer program, CABLESIM, is developed for the static and dynamic analyses of a cable-stayed bridge. The accuracy of the numerical procedure and its computer implementation is verified with the available analytical and experimental results. A parametric study is conducted to investigate the effects of vehicle velocity, girder depth, different types of cable arrangements, and traffic load on the dynamic response of the deck. The numerical results are expected to be important in assessing the dynamics of cable-stayed bridge components and in determining the safety and allowable traffic conditions.