Single Lane Change Research Articles

2D‐Action Asynchronous Cooperative Lane Change Trajectory Planning Method for Connected and Automated Vehicles

The ability to change lanes safely, efficiently, and comfortably is an important prerequisite for the application of Connected‐Automated Vehicles (CAVs). Based on the five‐order polynomial trajectory planning for CAVs, the 2D‐Action Asynchronous Lane Change (AALC) trajectory planning model is constructed by further considering the longitudinal and lateral driving action execution time parameters. This is done to improve the applicability of the lane change model and increase the CAV lane change success rate. The continuous collision space algorithm is constructed by determining the continuity condition of collision trajectory parameter solution space through the monotonicity of trajectory curve parameters and collision form classification. AALC trajectory safety judgment is realized through this algorithm. A cooperative lane change trajectory evaluation objective function is constructed, considering multivehicle comfort and efficiency. Finally, the AALC model is solved in the continuous collision space according to the optimal objective function, and the lane change is divided into free, cooperative, and refused according to the optimization. The results indicate that the AALC model achieves the transfer of collision space between lanes through asynchronous process of behavior execution time window, thereby reducing the possibility of vehicle collision. The AALC model reduces the degree of change of cooperative lane change parameters by asynchronous process of behavior, increasing the number of free lane change trajectories by about 17%, effectively reducing the occurrence of lane change refusal, improving the successful rate of lane change, and enhancing the overall evaluation of the lane change. The AALC model realizes the reallocation of collision space between different lanes through asynchronous process, making it more suitable for environments with large differences in vehicle gaps such as ramp merging. The collision‐based trajectory optimization algorithm can quickly obtain the corresponding safety space and optimal trajectory. The maximum calculation time for a single cooperative lane change is 0.073 s, thus enabling real‐time trajectory planning.

Research on multi-lane energy-saving driving strategy of connected electric vehicle based on vehicle speed prediction

In order to enhance the energy-saving potential of electric vehicles, a lane change decision method based on vehicle-to-everything (V2X) is designed to further improve the economics of intelligent connected electric vehicles. Firstly, the traversal test of electric vehicles is conducted at different speeds and accelerations to construct an energy consumption cloud model that reflects the mapping relationship between electric vehicle speed, acceleration and power. Next, the traffic flow information from V2X is used to train the long short-term memory neural network model optimized by particle swarm optimization (PSO-LSTM) for the prediction of the future speed of the vehicle in front of each lane. Then, according to the established energy consumption cloud model, the power performance corresponding to the predicted vehicle speed is obtained. Finally, a lane change decision method based on analytic hierarchy process (AHP) is established, and it is applied in four typical parallel scenarios to verify the robustness and effectiveness of the decision method. Simulation tests were conducted in a simulated urban traffic environment, involving both single-lane change scenarios and continuous lane change scenarios. The results show that this method can accurately and effectively select the lane with the best economic performance. Compared with the driving strategy of selecting a fixed lane, the energy consumption can be improved by up to 27.2% in the continuous lane change scenario.

Safe autonomous lane changes and impact on traffic flow in a connected vehicle environment

Despite the recent advancements in autonomous vehicle technologies, performing safe lane changes and merging in dense traffic environments remains an open challenge. One important question is how to find a space to merge into without placing any vehicle in a collision-prone situation. Moreover, what is the traffic flow impact of doing so? To tackle this issue, we start by adopting a safety definition based on a worst-case braking scenario. We then propose a decentralized controller-agnostic cooperative approach for lane changes that relies only on Vehicle-to-Vehicle communications and guarantees safety. In our method, the merging vehicle operates as having two possible leaders, one in its own lane and one in the destination lane, till the lane change maneuver is completed. Furthermore, the future following vehicle in the destination lane cooperates by acting as if the merging vehicle has already changed lanes. The merging vehicle only performs the lane change maneuver when the gaps are safe. Vehicle-level simulations are used to evaluate the approach in detail for a single lane change maneuver. Then, the method’s impact on highway safety and traffic flow is assessed using microscopic traffic simulations based on the commercial software VISSIM. We simulate three types of vehicles: adaptive cruise control equipped vehicles, autonomous vehicles, and connected and autonomous vehicles. The various simulations allow us to identify which improvements are brought by cooperative lane changes. Results indicate that connected and autonomous vehicles can achieve almost zero collision risk in congested and uncongested scenarios while improving traffic flow by 26% in the congested case. However, energy consumption increases significantly in the uncongested scenario. Moreover, our method outperforms an existing cooperative lane-changing method regarding safety and traffic flow. Our simulations with mixed traffic suggest that the proposed method is advantageous only at high penetrations of autonomous vehicles or in congested situations.

Motion Sickness Mitigating Algorithms and Control Strategy for Autonomous Vehicles

Autonomous Vehicles (AVs) have the potential to generate socioeconomic benefits by reducing commute times, accidents and energy consumption. Ergonomists have foreseen the future of these vehicles as comfortable pods where the passengers will be watching movies, reading or simply relaxing. Motion Sickness (MS) is thought to be a human comfort issue which needs to be addressed to enable such a vision. The present study endeavours to address this issue by firstly proposing three algorithms for mitigating MS during various manoeuvres, namely: (1) Single Lane Change (SLC), (2) Double Lane Change (DLC) and (3) Cornering. This is done in 3 phases; phase 1 is the identification of coordinates using Particle Swarm Optimization (PSO), phase 2 is the MS-free block that minimizes MS, and the last phase is shaping and symmetry block for minimizing postural instability and maximizing handling comfort. This is believed to be the first time an ultimate motion sickness mitigating algorithm is introduced. The second proposed solution is a control strategy to ensure real-time adaptive MS reduction while the AV is on the move with the help of modern & traditional controllers. Ultimately, The proposed hybrid solution is compared against other recent studies, with results illustrating a substantial MS reduction in AV’s of about 75%.

Toward Fault-Tolerant Vehicle Motion Control for Over-Actuated Automated Vehicles: A Non-Linear Model Predictive Approach

Automated driving systems operated at SAE levels 4 and 5 require a far-reaching fault-tolerant design. To meet this need at the actuator level, we present an integrated vehicle motion control approach that is able to tolerate a wide range of different actuator degradations and failures as well as tire blowouts in vehicles featuring four wheel-individual steering, drive, and brake actuators. The approach, which is based on non-linear model predictive control (MPC), tracks a temporal sequence of reference poses. Fault tolerance is achieved by reconfiguration of the MPC’s constraints, weights, and prediction model, which consists of a double-track vehicle and a brush tire model. The evaluation of the approach is based on two reference trajectories. The example of a simple single lane change trajectory in IPG CarMaker demonstrates the basic functionality of the approach. The example of a demanding decelerated single lane change trajectory shows that the approach is subject to limitations when tolerating different degradations and failures. Still, the observed limitations can be explained by the interplay of the specific degradation or failure and the demanding nature of the trajectory. Therefore, the results indicate that the suitability of fault-tolerant vehicle motion control as part of a system-wide safety concept is strongly connected to the range of possible driving scenarios that an automated driving system can encounter.

Reinforcement Learning Enabled Safety-Critical Tracking of Automated Vehicles with Uncertainties via Integrated Control-Dependent, Time-Varying Barrier Function, and Control Lyapunov Function

Model uncertainties are considered in a learning-based control framework that combines control dependent barrier function (CDBF), time-varying control barrier function (TCBF), and control Lyapunov function (CLF). Tracking control is achieved by CLF, while safety-critical constraints during tracking are guaranteed by CDBF and TCBF. A reinforcement learning (RL) method is applied to jointly learn model uncertainties that related to CDBF, TCBF, and CLF. The learning-based framework eventually formulates a quadratic programming (QP) with different constraints of CDBF, TCBF and CLF involving model uncertainties. It is the first time to apply the proposed learning-based framework for safety-guaranteed tracking control of automated vehicles with uncertainties. The control performances are validated for two different single-lane change maneuvers via Simulink/CarSim® co-simulation and compared for the cases with and without learning. Moreover, the learning effects are discussed through explainable constraints in the QP formulation.

Coordinated control of ESC with active front steering and active suspension normal force control for better vehicle’s dynamic response

Advances in vehicle technologies brought changes into architectures of integration of chassis control systems. Alongside other improvements, integration can provide better vehicle handling, stability and safety. Different chassis control systems can use different control methods. Considering while in motion vehicle has movements in longitudinal, lateral and vertical direction, different control systems target different motion. If there is no coordination among active control systems, interaction and performance conflict can arise. This paper presents coordination of three control systems: electronic stability control (ESC), active front steering control (AFSC) and active suspension normal force control (ASNF). ESC is actually direct yaw and anti-roll control using selective wheel braking. ASNF is considered only on front axle. All systems use fuzzy-logic as a control method. Vehicle is presented as 14-DOF nonlinear full vehicle model and for the control purposes 3-DOF reference model was introduced. Emphasis was given on vehicle parameters characterizing dynamic behavior in longitudinal and lateral direction. Benefits of coordinated action of the three systems can be seen from the results gained through simulation of cornering event and single lane change in Matlab/Simulink. Coordinated control adds to the action of ESC itself, resulting in improved stability and handling, and thus safety of the vehicle.

High-speed lateral stability and trajectory tracking performance for a tractor-semitrailer with active trailer steering.

An active trailer steering (ATS) controller is investigated to improve the lateral stability and trajectory tracking performance of the tractor-semitrailer. First of all, a linear yaw-roll dynamic model of the tractor-semitrailer with steerable trailer wheels is established, and the model accuracy is verified. Then a linear quadratic regulator (LQR) for actively steering the trailer's wheels is designed. For the LQR controller, the lateral acceleration and the sideslip angle at the center of gravity (CG) of the trailer are taken as the optimization objectives, and the steering angle of the wheel on the middle axle of the trailer is set as the control input. Finally, the effectiveness of the designed controller is tested based on the co-simulation platform under the single lane-change (SLC) maneuver at the speed of 100 km/h and the double lane-change (DLC) maneuver at the speed of 80 km/h and 88km/h. Research results show that under the high-speed SLC maneuver, the designed LQR controller can significantly improves the lateral stability and trajectory tracking performance of the trailer, and cannot affect apparently the trajectory and dynamic responses of the tractor. Under the high-speed DLC maneuver, the designed controller can still make the tractor-semitrailer reach a new steady state in a short time, and improve the vehicle lateral stability and the trajectory tracking performance of the trailer at the same time.

Lateral Stability Control of a Tractor-Semitrailer at High Speed

To improve the high-speed lateral stability of the tractor-semitrailer, a lateral stability control strategy based on the additional yaw moment caused by differential braking is proposed and investigated based on the co-simulation environment. First of all, a five-degree-of-freedom (5-DOF) yaw-roll dynamic model of the tractor-semitrailer is established, and the model accuracy is verified. Secondly, the lateral stability control strategy of the tractor-semitrailer is proposed, two yaw moment controllers and the braking torque distributor are designed. Then, the effectiveness of the proposed control strategy and the influence of the yaw moment controller on the lateral stability of the tractor-semitrailer are investigated under the high-speed lane-change maneuvers. Finally, the controller robustness is discussed. Research results show that the proposed high-speed lateral stability control strategy can ensure the tractor-semitrailer to perform safely the single lane-change (SLC) maneuver at 110 km/h and the double lane-change (DLC) maneuver at 88 km/h; the yaw moment controller has significant influence on the lateral dynamic performance of the tractor-semitrailer; compared with the proportional-derivative (PD) control, the model predictive control (MPC) can make the tractor-semitrailer obtain better lateral stability under high-speed lane-change maneuvers; MPC and PD controllers exhibit good robustness to the considered vehicle parameter uncertainties.

Electric Delta Trike Stability Characteristic and Maneuverability Analysis: Experiment and Multi-Body Dynamic Simulation

This paper reveals the stability characteristics of an electric-powered delta trike (e-trike), which is developed for goods delivery services. The changeable center of gravity position and weight due to electric component placement and the carried good weight can cause instability of the e-trike. Three main parameters are firstly evaluated on the e-trike: 1) geometry, 2) center of gravity, and 3) stiffness and damping coefficient of the suspensions. Single Lane-Change (SLC) and Double Lane-Change (DLC) tests were then conducted following ISO 14791:2000 and ISO 3888-1:2018 standards, respectively. An e-trike model was created and simulated using SIMPACK, a multi-body dynamic software. The simulation results showed that the developed e-trike model can replicate SLC and DLC tests, indicating the model was valid. A parametric study with the validated model was then conducted with various e-trike weights, center of gravity position, and suspension stiffness and damping ratio values. The results showed additional weight and higher center of gravity position can decrease threshold velocity to avoid rollover. The low suspension stiffness also contributed to lower the threshold velocity. However, the damping coefficient value did not change the threshold velocity significantly. These results can be a guideline in designing a delta trike with better performance in stability and maneuverability.

A real-time obstacle avoidance and path tracking strategy for a mobile robot using machine-learning and vision-based approach

In this paper, an obstacle avoidance and target tracking method for both indoor and outdoor mobile robots in dynamic environment is presented, and it aims to enhance autonomous navigation capability of such robots. In the proposed method, image processing and machine-learning approaches are considered. Since obstacles have differences in color and texture and in order to identify non-navigable areas, a monocular onboard camera is used to capture the road lanes by dealing with an image processing technique. The position of the robot with respect to road lane center during navigation is calculated on the basis of a proposed fuzzy logic rules set. In order to provide fast and robust computation, the Haar cascade classifier-based machine-learning technique has been exploited to detect the different sizes and shapes of the obstacles faced by the robot during its movement from source to destination. The dynamic model of a four-wheel mobile robot is initially developed using bond graph theory and then, the proposed obstacle-avoidance strategy is applied. The effectiveness and performance of the proposed method are tested under various simulation and experimentation scenarios. The behavior of the mobile robot for detecting and avoiding static obstacle for single and double road lane change environment is analyzed and discussed.

Integrated control of electric vehicles based on active front steering and model predictive control

Energy efficiency and handling stability are of the most importance for the control of electric vehicles. It is a challenge to maintain the stability and mobility of the vehicle at the cost of minimum energy under various driving conditions. A novel integrated control strategy of yaw stability and energy efficiency based on model predictive control and active steering system is presented. To improve the energy efficiency of the in-wheel motors, a global search algorithm of the instantaneous optimal efficiency of the motor is used to obtain the optimal torque distribution of the front and rear axles. Meanwhile, a terminal sliding mode controller is presented to maintain the lateral stability of the vehicle under general conditions. To reduce the large additional yaw moment of the vehicle under high-speed cornering condition, the model predictive controller is used to coordinate the active steering system and the direct yaw moment control system. Then, to balance the lateral stability and energy efficiency of the vehicle under extreme conditions, a stability judgment controller is proposed, which based on the theory of phase plane and yaw rate threshold method. The simulation results show that the integrated control strategy can improve the lateral stability of the vehicle under different road friction conditions, and compared with the control strategy without motor efficiency optimization , the integrated control strategy reduces the energy consumption by 21.66% and 11.18% in the ‘sine steering’ and ‘single lane change’ maneuver, respectively. In the slalom maneuver, the energy consumption of the integrated control strategy with energy saving optimization function is reduced by 10.13%.

Evaluating Coordinated Cooperative Control of Three Active Car Systems Using Fuzzy-Logic

Vehicle systems automation is an inevitable process as a result of the growing safety requirements and the trend of increasing car operation autonomy by reducing driver’s influence. The paper covers the coordinated control operation of three active systems to assess the improvement of vehicle response. Direct yaw control through selective wheel braking (DYC), active front steering control (AFS) and active suspension normal force control (NFC) are included. The control method is fuzzy logic. The modelling is done in Matlab/Simulink, where 14-DOF nonlinear full vehicle model and 3-DOF reference model were introduced. Simulations were done for three manoeuvres: cornering event, single lane change and fishhook manoeuvre, at a speed of 130 km/h and dry road surface with adhesion coefficient of 0.9 was assumed. Coordination was done with adjusting scaling factors for each control. Results show improvements in the transient response behaviour of the vehicle compared with four vehicles: vehicle without any active system, vehicle with coordinated DYC and AFS, vehicle with coordinated DYC and NFC and vehicle with coordinated AFS and NFC. The biggest impact can be seen in results for sideslip angle and roll angle, coordinated cooperative control here gives lowest values in the transient period during the manoeuvre. Although it gives better results for the other variables as well. The goal of the coordinated cooperative control is fulfilled by improving the stability and handling of the vehicle, which helps the driver to maintain the feeling of manoeuvrability and the sense for the direction of movement of the vehicle. The system for direct yaw control through selective wheel braking has major impact but the coordination with the other two systems lowers the braking force per wheel. The system for active front steering control has lower impact but at lower speeds helps for maintaining better direction of vehicle movement. Considering these three active systems act simultaneously during high speeds and critical manoeuvres next step would be to define sequence of activation depending on the currently measured vehicle behaviour variables.

Active steering control based on preview theory for articulated heavy vehicles.

This paper investigates the active steering control of the tractor and the trailer for the articulated heavy vehicle (AHV) to improve its high-speed lateral stability and low-speed path following. The four-degree-of-freedom (4-DOF) single track dynamic model of the AHV with a front-wheel steered trailer is established. Considering that the road information at the driver’s focus is the most clear and those away from the focus blurred, a new kind controller based on the fractional calculus, i.e., a focus preview controller is designed to provide the steering input for the tractor to make it travel along the desired path. In addition, the active steering controllers based on the linear quadratic regulator (LQR) and single-point preview controller respectively are also proposed for the trailer. However, the latter is designed on the basis of the articulation angle between the tractor and trailer, inspired by the idea of the driver’s single-point preview controller. Finally, the single lane change maneuver and 90o turn maneuver are carried out. And the simulation results show that compared with the single-point preview controller, the new kind preview controller for the tractor can have good high speed maneuvering stability and low speed path tracking ability by adjusting the fractional order of the controller. On this basis, three different AHVs with the same tractor are simulated and the simulation results show that the AHV whose trailer adopts the single-point preview controller has better high-speed lateral stability and low-speed path tracking than the AHV whose trailer adopts the LQR controller.

Robust trajectory tracking control for autonomous vehicle subject to velocity-varying and uncertain lateral disturbance

Autonomous vehicles are the most advanced intelligent vehicles and will play an important role in reducing traffic accidents, saving energy and reducing emission. Motion control for trajectory tracking is one of the core issues in the field of autonomous vehicle research. According to the characteristics of strong nonlinearity, uncertainty and chang-ing longitudinal velocity for autonomous vehicles at high speed steering condition, the robust trajectory tracking control is studied. Firstly, the vehicle system models are established and the novel target longitudinal velocity planning is carried out. This velocity planning method can not only ensure that the autonomous vehicle operates in a strong nonlinear coupling state in bend, but also easy to be constructed. Then, taking the lateral location deviation minimiz-ing to zero as the lateral control objective, a robust active disturbance rejection control path tracking controller is designed along with an extended state observer which can deal with the varying velocity and uncertain lateral dis-turbance effectively. Additionally, the feedforward-feedback control method is adopted to control the total tire torque, which is distributed according to the steering characteristics of the vehicle for additional yaw moment to enhance vehicle handing stability. Finally, the robustness of the proposed controller is evaluated under velocity-varying condi-tion and sudden lateral disturbance. The single-lane change maneuver and double-lane change maneuver under vary longitudinal velocity and different road adhesions are both simulated. The simulation results based on Matlab/Simulink show that the proposed controller can accurately observe the external disturbances and have good performance in trajectory tracking and handing stability. The maximum lateral error reduces by 0.18 meters compared with a vehicle that controlled by a feedback-feedforward path tracking controller in the single-lane change maneuver. The lateral deviation is still very small even in the double lane change case of abrupt curvature. It should be noted that our proposed control algorithm is simple and robust, thus provide great potential for engineering application.

Modeling the steering wheel influence by the driver on the vehicle's motion stability

In this article, a mathematical model was developed to influence the intensity of the steering wheel turn by the driver on the vehicle's stability. Comparison of the developed mathematical model with the experiment results made it possible to establish their adequacy. The effect of the three conditional drivers on the intensity of the steering wheel was examined. When performing the 'J-turn' maneuver, comparing the indices of the 1st, 2nd and 3rd conditional drivers, their proximity to the requirements of the standard was established. It was found that the indices of the second conditional driver are closest to the standard requirements. When performing the 'Single Lane Change' maneuver by the first conventional driver, the standard deviation value from the specified trajectory was 0.102, and the correlation index was 0.88.

Fault-Tolerant Control for Intelligent Electrified Vehicles Against Front Wheel Steering Angle Sensor Faults During Trajectory Tracking

Steer-by-Wire (SBW) systems are an integral and essential component of intelligent electrified vehicles and are critical to ensure safe vehicle operations. In this paper, a fault-tolerant control method for SBW is proposed to mitigate the adverse influence of front wheel steering angle sensor faults based on the Kalman filtering technique. First, a linearized vehicle model is derived based on tire characteristics and is further combined with a steering actuator model to provide the modelling foundation for estimating the front wheel steering angle. Considering multi-source noises and their significant influence on the front wheel steering angle sensor, the Butterworth filter is employed to filter out the high-frequency noises. The front wheel steering angle estimation is realized by incorporating the measurements of the yaw rate and lateral acceleration of vehicle and the current of steering motor. In particular, a dynamic threshold mechanism is adopted to activate the fault diagnosis and fault-tolerant compensation based on the residual theory. Finally, a linear time-varying model predictive controller is presented to execute the trajectory tracking task for an intelligent electrified vehicle. The effectiveness of the proposed scheme is verified under the single lane change and double lane change maneuvers during the trajectory tracking.

Collision Imminent Steering at High Speeds on Curved Roads Using One-Level Nonlinear Model Predictive Control

Collision imminent steering is an automotive active safety feature designed to perform an evasive lane change maneuver when a forward collision cannot be avoided by braking alone. Previous work developed a nonlinear one-level model predictive controller to perform such a maneuver in a straight highway environment and at high speeds. In this article, a new formulation is presented that extends this capability to curved roads. The formulation includes a drivable tube concept, within which the maneuver is allowed to push the vehicle to its limits of handling, but only if the controller deems it necessary. Numerical simulation results showcase aggressive lane change maneuvers on curved roads at high speeds, allowing for both inside and outside lane changes, as well as single and double lane change maneuvers in a shorter distance than braking.

DESIGN AND ASSESSMENT OF A SPEED-BASED INTEGRATED ACTIVE VEHICLE CONTROLLER FOR LATERAL STABILITY

An integrated active vehicle control system implementing fuzzy-logic control (FLC) is introduced. The system integrates three commercially- available active vehicle control systems, namely, Active Front Steering (AFS), Electronic Stability Control (ESC) and Torque Vectoring System (TVS) aiming at enhancing vehicle handling and cornering stability and rollover prevention. Two different vehicle models were constructed to simulate the dynamic behavior of the system with and without the proposed integration controller, namely, a 14-DOF vehicle dynamic model with nonlinear tire characteristics and a 2DOF bicycle reference model. Last model was utilized to generate controller’s reference values of vehicle’s yaw rate and body side slip angle at a given forward speed and driver’s steering input. Simulation was carried out in the MATLAB/SIMULINK software environment. The effectiveness of the system was investigated applying five different standard cornering test maneuvers at different vehicle forward speeds of 10, 20 and 30m/s. Simulated test maneuvers are: step, J-turn, single lane change (SLC), sine with dwell, (SWD) and fishhook.Results reveal that, for stability enhancement, AFS is most effective at low vehicle speeds with declining efficacy as speed goes up. Both ESC and TVS have been found to be equally effective at moderate to high speeds. In conclusion, an integrated chassis control (ICC) strategy has been proposed that improves vehicle handling and cornering performance across the entire operating range of speed using a forward-speed-based stability criterion to allocate stability control authority and ensure smooth transition of control between the three AFS, ESC, and TVS systems.

Stability Coordinated Control of Distributed Drive Electric Vehicle Based on Condition Switching

The distributed drive electric vehicle is a complex hybrid system including discrete events and continuous events. In order to coordinate the longitudinal and lateral motion of the distributed drive electric vehicle, a hierarchical control method was proposed. In the upper layer, the body attitude tracking controller based on sliding mode control algorithm was established to accurately analyze the driving expectation and to track the longitudinal speed, the lateral speed, and the yaw rate of the vehicle. In the lower layer, the switching controller based on the hybrid theory was established to improve the driving stability under various working conditions. The switching controller can switch between control strategies according to the working conditions. The joint simulation was carried out under various working conditions using Simulink and CarSim software. The results showed that the controller can coordinate the longitudinal and lateral motion of the vehicle well in linear acceleration and sinusoidal acceleration conditions and can strictly track the driving expectation and maintain the desired body posture. And another, the controller can be switched according to the working conditions and control strategies accurately and smoothly and can ensure stable driving in the constant speed single lane change condition. The controller can reveal the continuous behavior characteristics of the vehicle and reflect the characteristics of discrete events by coordinating the longitudinal and lateral motion of the vehicle. It improves the stability and control performance of the distributed drive electric vehicle under various working conditions.