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This paper presents an optimal cooperative path planning method considering driver’s driving intention for shared control to address target path conflicts during the driver-automation interaction by using the convex optimization technique based on the natural cubic spline. The optimal path criteria (e.g. the optimal curvature, the optimal heading angle) are formulated as quadratic forms using the natural cubic spline, and the initial cooperative path profiles of the cooperative path in the Frenet-based coordinate system are induced by considering the driver’s lane-changing intention recognized by the Support Vector Machine (SVM) method. Then, the optimal cooperative path could be obtained by the convex optimization techniques. The noncooperative game theory is adopted to model the driver-automation interaction in this shared control framework, where the Nash equilibrium solution is derived by the model predictive control (MPC) approach.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.

One main objective is to find out how these parameters interact and optimal driver control gain and driver preview time are obtained. Some steps further, neuromuscular dynamics is considered and the system becomes different from the simplified driver-vehicle system studied before. New optimal driver control gain and driver preview time could be obtained for both tensed and relaxed muscle state. Final step aims at analysing the full system considering driver, neuromuscular, steer-by-wire and vehicle models. The steer-by-wire system could potentially have a significant influence on the vehicle when the driver is at impaired state, which could be represented by setting higher response delay time or smaller preview time. Vehicle's stability and active safety could also be improved by introducing the steer-by-wire system.

Compared to the vehicles with conventional steering, the articulated frame steer vehicles (ASV) are known to exhibit lower directional and roll stability limits. Furthermore, the tire interactions with relatively rough terrains could adversely affect the directional and roll stability limits of an ASV due to terrain-induced variations in the vertical and lateral tire forces. It may thus be desirable to assess the dynamic safety of ASVs in terms of their directional control and stability limits while operating on different terrains. The effects of terrain roughness on the directional stability limits of an ASV are investigated through simulations of a comprehensive three-dimensional model of the vehicle with and without a rear axle suspension. The model incorporates a torsio-elastic rear axle suspension, a kineto-dynamic model of the frame steering struts and equivalent random profiles of different undeformable terrains together with coherence between the two tracks profiles.

This study investigates influence of compressible hydraulic fluid and suspension floating piston dynamics of fluidic suspensions on heavy vehicle roll stability and ride dynamics. Two fluidic suspension designs, including a single-gas-chamber strut and a novel twin-gas-chamber strut, are analyzed to develop the mathematical formulations of dynamic forces, upon considerations of hydraulic fluid compressibility and floating piston dynamics. Dynamic responses of the heavy vehicle with the different suspension configurations are then performed using a nonlinear roll plane vehicle model. The excitations arise from vehicle-road interactions as well as a steady steering maneuver. The results demonstrate that the compressibility characteristic of hydraulic fluid within a hydro-pneumatic suspension could affect the vehicle roll stability and ride dynamics, while the influence of suspension floating piston dynamics on vehicle dynamic responses is negligible.

The ride performance potentials of a prototype torsio-elastic axle suspension for an off-road vehicle were investigated analytically and experimentally. A forestry vehicle was fitted with the prototype suspension at its rear axle to assess its ride performance benefits. Field measurements of ride vibration along the vertical, lateral, fore-aft, roll and pitch axes were performed for the suspended and an unsuspended vehicle, while traversing a forestry terrain. The measured vibration responses of both vehicles were evaluated in terms of unweighted and frequency-weighted rms accelerations and the acceleration spectra, and compared to assess the potential performance benefits of the proposed suspension. The results revealed that the proposed suspension could yield significant reductions in the vibration magnitudes transmitted to the operator's station.

The handling and braking responses of a heavy vehicle equipped with a cross-axle fluidically-coupled hydro-pneumatic suspension concept are investigated. The proposed fluidically-coupled suspension is conceived by diagonally interconnecting different hydraulic fluid chambers of the four suspension struts of the vehicle. The analytical formulations of suspension forces are derived based on fluid flows through the couplings and damping valves. A generalized full-vehicle model is developed and validated to evaluate the handling and braking responses to two critical vehicle maneuvers: (i) braking-in-a-turn; and (ii) split-μ straight-line braking. The responses of the vehicle model with the coupled suspension are compared with those of the uncoupled suspension under various inputs to demonstrate the potential benefits of the proposed cross-axle fluidic coupling of the suspension struts.

The optimal damping design of roll plane interconnected hydro-pneumatic suspension is investigated, in order to improve vertical ride and road-friendliness of heavy vehicles, while maintaining enhanced roll stability. A nonlinear roll plane vehicle model is developed to study vertical as well as roll dynamics of heavy vehicles. The damping valves and gas chamber are integrated within the same suspension strut unit to realize compact design. The influence of variations in damping valve threshold velocity on relative roll stability is explored, under centrifugal acceleration excitations arising from steady turning and lane change maneuvers, as well as crosswind. The effects of damping valve design parameters on the vertical ride vibration and vehicle-road interaction characteristics are also investigated under a medium rough road input and two different vehicle speeds.

This study investigates the performance potentials of hydro-pneumatic suspensions interconnected in the pitch plane of a heavy vehicle. Different configurations of interconnected suspensions comprising pneumatic, hydraulic or hybrid fluidic couplings between the front-and rear-suspension struts are proposed and analyzed. A 7-DOF pitch plane vehicle model is formulated to explore the relative vertical and pitch properties of different suspension configurations, as well as the dynamic responses of the vehicle under braking and road inputs. The mathematical formulations of strut forces due to both the unconnected and pitch-connected suspensions are derived. Relative performance potentials of different configurations are evaluated in terms of sprung mass pitch angle, suspension travel and stopping distance characteristics under different braking inputs and road conditions. The vertical ride quality is further assessed under a range of road roughness excitations and vehicle speeds.

Two different concepts in hydro-pneumatic suspension struts are formulated to conveniently realize either hydraulic or pneumatic interconnections between the struts within different wheel suspensions. The formulation employs a compact strut design that integrates a gas chamber and damping valves within the same unit, and provides considerably enhanced working area to appreciably reduce the operating pressure. A transverse interconnection between the hydro-pneumatic struts in the roll plane is analyzed to investigate its static and dynamic heave and roll properties, and relative potential benefits in enhancing the roll properties, while retaining the soft heave ride. Different hydraulically and pneumatically interconnected strut configurations are analyzed for a heavy vehicle, with appropriate considerations of the fluid compressibility, while the feedback effects associated with the interconnections are emphasized.