Cascade Optimization Control of Unmanned Vehicle Path Tracking Under Harsh Driving Conditions

Under ultra-high-speed and harsh conditions,conventional control methods struggle to ensure the path tracking accuracy and driving stability of unmanned vehicles during the turning process.Therefore,this study proposes a cascade control to solve this problem.Based on the new vehicle error model that considers vehicle tire sideslip and road curvature,the feedforward-parametric adaptive linear quadratic regulator(LQR)and proportional integral control-based speed-keeping controllers are used to compose the path-tracking cascade optimization controller for unmanned vehicles.To improve the adaptability of the unmanned vehicle path-tracking control under harsh driving conditions,the LQR controller parameters are automatically adjusted using a back-propagation neural network,in which the initial weights and thresholds are optimized using the improved grey wolf optimization algorithm according to the driving conditions.The speed-keeping controller reduces the impact on the curve-tracking accuracy under nonlinear vehicle speed variations.Finally,a joint model of MATLAB/Simulink and CarSim was established,and simulations show that the proposed control method can achieve stable entry and exit curves at ultra-high speeds for unmanned vehicles.Under strong wind and ice road conditions,the method exhibits a higher tracking accuracy and is more adaptive and robust to external interference in driving and variable curvature roads than methods such as the feedforward-LQR,preview and pure pursuit controls.

Exploring traffic safety climate with driving condition and driving behaviour:a random parameter structural equation model approach

This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour.To achieve the objective,the random parameter structural equation model was proposed so that driver action and driving condition can address the safety climate by integrating crash features,vehicle profiles,roadway conditions and environment conditions.The geo-localized crash open data of Las Vegas metropolitan area were collected from 2014 to 2016,including 27 arterials with 16827 injury samples.By quantifying the driving conditions and driving actions,the random parameter structural equation model was built up with measurement variables and latent variables.Results revealed that the random parameter structural equation model can address traffic safety climate quantitatively,while driving conditions and driving actions were quantified and reflected by vehicles,road environment and crash features correspondingly.The findings provide potential insights for practitioners and policy makers to improve the driving environment and traffic safety culture.

Chassis Coordinated Control for Full X-by-Wire Vehicles-A Review

An X-by-wire chassis can improve the kinematic characteristics of human-vehicle closed-loop system and thus active safety especially under emergency scenarios via enabling chassis coordinated control.This paper aims to provide a complete and systematic survey on chassis coordinated control methods for full X-by-wire vehicles,with the primary goal of summarizing recent reserch advancements and stimulating innovative thoughts.Driving condition identification including driver’s operation intention,critical vehicle states and road adhesion condition and integrated control of X-by-wire chassis subsystems constitute the main framework of a chassis coordinated control scheme.Under steering and braking maneuvers,different driving condition identification methods are described in this paper.These are the trigger conditions and the basis for the implementation of chassis coordinated control.For the vehicles equipped with steering-by-wire,braking-by-wire and/or wire-controlled-suspension systems,state-of-the-art chassis coordinated control methods are reviewed including the coordination of any two or three chassis subsystems.Finally,the development trends are discussed.

The Roll Stability Analysis of Semi-Trailer Based on the Wheel Force

It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance,and that may cause serious accidents.Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation,how to make an effective early warning of rollover is still unsolved in practice.The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining.The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude of the vehicle.Unfortunately,the lateral acceleration is more useful for sideslip rather than rollover,and the attitude is a kind of posterior way,which means it is hard to take measures to cope with the rollover accident when the attitude exceeds the safety threshold.Considering the movement of the vehicle is totally caused by the wheel force,the rollover could also be predicted by the changing of the wheel force.Therefore,in this paper,we developed a method to analyze the roll stability by the vertical wheel force.A thorough experiment environment is established,and the effectiveness of the proposed method is verified in real driving conditions.

Real‑Time Predictive Control of Path Following to Stabilize Autonomous Electric Vehicles Under Extreme Drive Conditions

A novel real-time predictive control strategy is proposed for path following(PF)and vehicle stability of autonomous electric vehicles under extreme drive conditions.The investigated vehicle configuration is a distributed drive electric vehicle,which allows to independently control the torques of each in-wheel motor(IWM)for superior stability,but bringing control com-plexities.The control-oriented model is established by the Magic Formula tire function and the single-track vehicle model.For PF and direct yaw moment control,the nonlinear model predictive control(NMPC)strategy is developed to minimize PF tracking error and stabilize vehicle,outputting front tires’lateral force and external yaw moment.To mitigate the calcu-lation burdens,the continuation/general minimal residual algorithm is proposed for real-time optimization in NMPC.The relaxation function method is adopted to handle the inequality constraints.To prevent vehicle instability and improve steering capacity,the lateral velocity differential of the vehicle is considered in phase plane analysis,and the novel stable bounds of lateral forces are developed and online applied in the proposed NMPC controller.Additionally,the Lyapunov-based constraint is proposed to guarantee the closed-loop stability for the PF issue,and sufficient conditions regarding recursive feasibility and closed-loop stability are provided analytically.The target lateral force is transformed as front steering angle command by the inversive tire model,and the external yaw moment and total traction torque are distributed as the torque commands of IWMs by optimization.The validations prove the effectiveness of the proposed strategy in improved steering capacity,desirable PF effects,vehicle stabilization,and real-time applicability.