Longitudinal and lateral control of autonomous vehicles in multi‐vehicle driving environments

IET Control Theory & Appl

Liang

et al. 2021

Vehicles have irregular shapes and inter-vehicle coordination is not a trivial task. Based on the distributed-system framework, this paper studies multi-vehicle control and coordinated obstacle avoidance for multiple autonomous vehicles with irregular shapes. The goal is to reach target points without collisions. The proposed approaches are based on collision time, which is calculated using vehicles' irregular shapes. The approaches have two parts. The first part enables a number of vehicles to reach the target points. The second part enables collision avoidance, which includes inter-vehicle collisions and vehicle-to-obstacle collisions. Speed regulation approach is proposed to change the speeds, and frequencymodulation approach is proposed to update control commands at varying steps, and a combined approach is also proposed. Simulation examples are set to verify the effectiveness of the proposed approaches.

Section: Introductionsupporting

confidence: 60%

Coordinated collision avoidance for multi‐vehicle systems based on collision time

IET Control Theory & Appl

Liang

et al. 2021

“…We use a polynomial (19) to generate a collision-avoidance curve including the value of the optimal yaw ϕ re f and lateral coordinate ζ re f which are both the function of X, where p y1 ∼ p y5 , p ϕ1 ∼ p ϕ5 are fitting coefficients calculated by the predictive sequence Y n,k as shown in (18).…”

Section: Path Planning Controller Based On Nonlinear Mpcmentioning

confidence: 99%

“…In [16], social behaviors were taken into consideration when solving the MPC problem. However, effectively solving an optimization problem is extremely dependent on high-computing performance, consequently the interpolation curve-based methods such as Polynomial Curves [17,18], Bezier Curves [19], etc., are widely used to reduce the computation.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Model Predictive Control for Autonomous Collision Avoidance of Distributed Electric Drive Vehicle with Lateral Stability Analysis in Extreme Scenarios

Lin

Liang

et al. 2021

WEVJ

This paper proposes an active collision avoidance controller based on a hierarchical model predictive control framework for distributed electric drive vehicles (4IDEV) considering extreme conditions. In this framework, a two-layer strategy is developed. The upper layer is the path replanning controller based on nonlinear MPC (nMPC), from which a collision-free path including the optimal lateral displacement and yaw angle can be obtained in real-time while encountering the obstacles. The lower layer is the path tracking controller based on hybrid MPC (hMPC), and the coordinated control inputs (yaw moment and the front wheel steering angle) are solved by a Mixed-Integer Quadratic Programming (MIQP) with the piecewise affine (PWA) tire model considering tire saturation region. Moreover, to improve the lateral stability when tracking, the stable zone of lateral stability in the high-risk condition is analyzed based on the phase portrait method, by which the constraints of vehicle states and inputs are derived. The verification is carried out on the MATLAB and CarSim co-simulation platform, and the simulation results show that the proposed active collision avoidance controller can track the reference path accurately and prevent vehicle instability in extreme scenarios.

“…9 Besides, an integrated longitudinal and lateral trajectory planning and tracking control strategy is introduced to ensure riding comfort and collision avoidance. 10 For longitudinal control, road bumps as uncertain disturbances are inevitable for multivehicle cooperative systems during driving. 11 As actuators in a longitudinal driving process, vehicle motors are saturated for the reason of constraints in vehicle dynamic characteristics.…”

Section: Introductionmentioning

confidence: 99%

Adaptive longitudinal control for multivehicle cooperative systems with actuator saturation under road bumps

Yang

Intl J Robust & Nonlinear

et al. 2022

In this article, an adaptive longitudinal control strategy is proposed for a multivehicle cooperative system with actuator saturation. The multivehicle cooperative system is modeled as a longitudinal system. Uncertain disturbances caused by road bumps during vehicle driving are estimated by an adaptive extended state observer based on Silverman canonical transformation and pole placement.An adaptive integral sliding mode control algorithm is designed to accomplish adaptive longitudinal control and handle actuator saturation. With Lyapunov criterion, stability is presented for the multivehicle cooperative system with the adaptive longitudinal control strategy. Simulation results are given to show effectiveness of the adaptive extended state observer and the adaptive integral sliding mode control algorithm.