SUMMARYA simplified analytical method is presented for the vertical dynamic analysis of a rigid, massive, cylindrical foundation embedded in a poroelastic soil layer. The foundation is subjected to a time-harmonic vertical loading and is perfectly bonded to the surrounding soil in the vertical direction. The soil underlying the foundation base is represented by a single-layered poroelastic soil based on rigid bedrock while the soil at the side of the foundation is modeled as an independent poroelastic layer composed of a series of infinitesimally thin layers. The behavior of the soil is governed by Biot's poroelastodynamic theory and its governing equations are solved by the use of Hankel integral transform. The contact surface between the foundation base and the soil is smooth and fully permeable. The dynamic interaction problem is solved following standard numerical procedures. The accuracy of the present solution is verified by comparisons with the well-known solutions obtained from other approaches for both the elastodynamic interaction problem and poroelastodynamic interaction problem. Numerical results for the vertical dynamic impedance and response factor of the foundation are presented to demonstrate the influence of nondimensional frequency of excitation, soil layer thickness, poroelastic material parameters, depth ratio and mass ratio on the dynamic response of a rigid foundation embedded in a poroelastic soil layer.

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To highlight the advantages of autonomous vehicles (AVs) in modern traffic, it is necessary to investigate the sensing requirement parameters of the road environment during the vehicle braking process. Based on the texture information obtained using a field measurement, the braking model of an AV was built in Simulink and the ride comfort under typical braking scenarios was analyzed using CarSim/Simulink co-simulation. The results showed that the proposed brake system for the AV displayed a better performance than the traditional ABS when considering pavement adhesion characteristics. The braking pressure should be controlled to within the range of 4 MPa~6 MPa on a dry road, while in wet road conditions, the pressure should be within 3 MPa~4 MPa. When steering braking in dry road conditions, the duration of the “curve balance state” increased by about 57.14% compared with wet road conditions and the recommended curve radius was about 100 m. The slope gradient had a significant effect on the initial braking speed and comfort level. Overall, the ride comfort evaluation method was proposed to provide theoretical guidance for AV braking strategies, which can help to complement existing practices for road condition assessment.

To fully consider the impact of asphalt pavement rut on steering stability of autonomous vehicles, the sensitivity of various indicators of rut shape to vehicle stability was comprehensively measured, and pavement rut control standards based on comfort demands of autonomous vehicles were investigated. Firstly, a steering control system for autonomous vehicles was built in Simulink according to fuzzy control theory. Then, through orthogonal experiment design theory, different rut shape indicators are simulated in CarSim. The influence sensitivity of different rut shape indicators and the allowable rut range considering driving comfort were studied. The results show that both the rut depth and the rut side angle have a greater effect on the vehicle vertical acceleration within a certain parameter range. The maximum roll angle of vehicle body is mainly affected by the rut depth, and the rut width has a small effect on the vehicle driving stability. Meanwhile, considering human comfort, the rut side angle should not be greater than 1° when the rut depth reaches 2 cm. For autonomous driving, the rut depth should not exceed 2.5 cm. When the rut depth exceeds 2.5 cm, the vehicle body roll angle caused by the rut exceeds the inertial centrifugal force of the vehicle itself, which has a significant impact on the passenger comfort and safety.

As the main objective influencing factor on the brake safety of autonomous vehicles, pavement texture information is directly related to road surface antiskid performance. However, in the brake system of autonomous vehicles, the influence of road surface adhesion characteristics on braking stability is seldomly considered. To study the braking stability of autonomous vehicles on curved sections under different road conditions, the advanced close-range photogrammetry system was utilized to extract the road surface texture information. Thereafter, the power spectral density (PSD) of the road surface was calculated by MATLAB to obtain the pavement adhesion coefficient curves based on the Persson friction theory model under different road conditions. Considering the pavement adhesion characteristics, the braking model of autonomous vehicles was built in Simulink, and then, the braking performance on curved sections was analyzed with CarSim/Simulink cosimulation. The results indicate that, according to the adhesion coefficient of different asphalt pavement types under different road conditions, the ranking order is open-grade friction course (OGFC) > stone matrix asphalt (SMA) > dense-graded asphalt concrete (AC). In addition, both the maximum lateral offset distances and the maximum lateral forces of the tires decrease as the curve radius gradually increases under different road conditions. It can also be found that there is a relatively uniform vertical forces distribution of the tire when the curve radius is no less than 100 m, and the limit speed of the vehicle varies parabolically with increasing in curve radius. Compared with dry road, the reduction of vehicle braking deceleration is more significant and the yaw rate is greater on wet road. Last but not least, the braking comfort with a radius of 200 m is the best according to the comfort index (CI) in International Standard ISO, in which the comfort level can be sorted into six levels.