The path-following problem for four-wheel independent driving and four-wheel independent steering electric autonomous vehicles is investigated in this paper. Owing to the over-actuated characters of four-wheel independent driving and four-wheel independent steering autonomous vehicles, a novel yaw rate tracking-based path-following controller is proposed. First, according to the kinematic relationships between vehicle and the reference path, the yaw rate generator is designed by linear matrix inequality theory, with the ability to minimize the disturbances caused by vehicle side slip and varying curvature of path. Considering that the path-following objective and dynamics stability are in conflict with each other in some extreme path-following conditions, a coordinating mechanism based on yaw rate prediction is proposed to satisfy the two conflicting objectives. Then, according to the desired yaw rate and longitudinal velocity, a hierarchical structure is introduced for motion control. The upper-level controller calculates the generalized tracking forces while the allocation layer optimally distributes the generalized forces to tires considering tire vertical load and adhesive utilization. Finally, simulation results indicate that the proposed method can achieve excellent path-following performances in different driving conditions, while both path-following objective and dynamics stability can be satisfied.
Connected and automated vehicle (CAV) technologies have great potential to improve road safety. However, an emerging type of mixed traffic flow with human-driven vehicles (HDVs) and CAVs has also arisen in recent years. To improve the overall safety of this mixed traffic flow, a novel car-following model is proposed to control the driving behaviors of the above two types of vehicles in a platoon from the perspective of a mechanical system, mass-spring-damper (MSD) system. Furthermore, a quantitative index is proposed by incorporating the psychological field theory into the MSD model. The errors of spacing and speed in the car-following processes can be expressed as the accumulation of the virtual total energy, and the magnitude of the energy is used to reflect the danger level of vehicles in the mixed platoon. At the same time, the optimization model of minimum total energy is solved under the constraints of vehicle dynamics and the mechanical characteristics of the MSD system, and the optimal solutions are used as the parameters of the MSD car-following model. Finally, a mixed platoon composed of 3 CAVs and 2 HDVs without performing lane changing is tested using the driver-in-the-loop test platform. The test results show that, in the mixed platoon, CAVs can optimally adjust the intervehicle spacing by making full use of the braking distance, which also provides sufficient reaction time for the driver of HDV to avoid rear-end collisions. Furthermore, in the early stage of the emergency braking, the spacing error is the dominant factor influencing the car-following behaviors, but in the later stage of emergency braking, the speed error becomes the decisive factor of the car-following behaviors. These results indicate that the proposed car-following model and quantitative index are of great significance for improving the overall safety of the mixed traffic flow with CAVs and HDVs.
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