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The steering stability of vehicle was the most important part of vehicle handling and stability. The stability analysis of vehicle negotiating a curve in the plane was studied through simulation. The vehicle dynamics model used in this paper had two degrees of freedom with nonlinear tire characteristics. When two vehicle state variables, namely, velocity and steering angle, were changed, the GA and phase space analysis were used to compute the equilibrium points and analyze the phase space characteristics of vehicle system. Considering the nonlinear tire characteristic, the working region of tire was figured out and compared, while the vehicle was under different operating conditions. From the analysis results, it could be concluded that working in the nonlinear region of tire characteristic was the ultimate reason of vehicle instability. The knowledge derived from simulation results could dramatically enhance the understanding of stability of the actual vehicle negotiating a curve on an even surface. Such knowledge was a prerequisite for robustly designing the chassis, such as steer-by-wire, which would be the topics of future work.

Distracted driving has become a major cause of road traffic accidents. There are generally four different types of distractions: manual, visual, auditory, and cognitive. Manual distractions are the most common. Previous studies have used physiological indicators, vehicle behavior parameters, or machine-visual features to support research. However, these technologies are not suitable for an in-vehicle environment. To address this need, this study examined a non-intrusive method for detecting in-transit manual distractions. Wrist kinematics data from 20 drivers were collected using wearable inertial measurement units (IMU) to detect four common gestures made while driving: dialing a hand-held cellular phone, adjusting the audio or climate controls, reaching for an object in the back seat, and maneuvering the steering wheel to stay in the lane. The study proposed a progressive classification model for gesture recognition, including two major time-based sequencing components and a Hidden Markov Model (HMM). Results show that the accuracy for detecting disturbances was 95.52%. The accuracy associated with recognizing manual distractions reached 96.63%, using the proposed model. The overall model has the advantages of being sensitive to perceptions of motion, effectively solving the problem of a fall-off in recognition performance due to excessive disturbances in motion samples.

Anti-roll hydraulically interconnected suspension (HIS) due to its roll-vibration stiffness and damping performance has been studied and applied in passenger vehicles, buses, and tri-axle straight vehicles. However, very few investigations have been made on six-axle articulated vehicles with the HIS system. Moreover, rollover accidents involving articulated vehicles cause severe casualties, which have attracted wide attention in the vehicle safety field. This calls for a design of a new suspension control technique to improve the handling stability performance at a lower cost and with less energy consumption. This paper presents an anti-roll HIS system control technique to improve the handling stability of a six-axle tractor–semitrailer with nonlinear uncertain parameters. Firstly, the HIS model for leaf-spring suspension of a half semitrailer is established by means of the linear transfer matrix method. Secondly, the power spectral density function is analyzed to validate the obtained model, and equivalent stiffness and damping are computed using natural frequency. Thirdly, six-axle vehicle equations with the HIS model are established considering the equivalent stiffness and damping parameter as the medium. Finally, numerical simulation results are provided and compared with the original vehicle. Dynamic response of the proposed technique is assessed by analyzing roll stability, lateral stability, yaw stability, and articulation stability. The results show that the proposed control technique can effectively improve the handling performance of an articulated vehicle.