A Potential Field Approach-Based Trajectory Control for Autonomous Electric Vehicles With In-Wheel Motors

Steering control for path tracking in autonomous vehicles is well documented in the literature. Also, continuous direct yaw moment control, i.e., torque-vectoring, applied to human-driven electric vehicles with multiple motors is extensively researched. However, the combination of both controllers is not yet well understood. This paper analyzes the benefits of torquevectoring in an autonomous electric vehicle, either by integrating the torque-vectoring system in the path tracking controller, or through its separate implementation alongside the steering controller for path tracking. A selection of path tracking controllers is compared in obstacle avoidance tests simulated with an experimentally validated vehicle dynamics model. A genetic optimization is used to select the controller parameters. Simulation results confirm that torque-vectoring is beneficial to autonomous vehicle response. The integrated controllers achieve the best performance if they are tuned for the specific tire-road friction condition. However, they can also cause unstable behavior when they operate in lower friction conditions without any retuning. On the other hand, separate torque-vectoring implementations provide consistently stable cornering response for a wide range of friction conditions. Controllers with preview formulations, or based on appropriate reference paths with respect to the middle line of the available lane, are beneficial to the path tracking performance.

show abstract

“…IACA , +IACA , (28) where the subscripts 'FF' and 'FB' refer to the feedforward and feedback contributions, respectively.…”

Section: E Performance Indicators and Objective Functionmentioning

confidence: 99%

Comparison of Path Tracking and Torque-Vectoring Controllers for Autonomous Electric Vehicles

Chatzikomis¹,

Sorniotti

Gruber

et al. 2018

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

show abstract

“…The meanings of the symbols are as shown in Table 2. According to Newton's second law, the balanced force equations of the vehicle along the x-axis, y-axis, and z-axis are obtained, as shown in (21). According to Newton's second law, the balanced force equations of the vehicle along the x-axis, y-axis, and z-axis are obtained, as shown in (21).…”

Section: Tire Force Allocator Layermentioning

confidence: 99%

“…The longitudinal and lateral forces of the tire are affected by the nonlinear deflection characteristics, respectively. Many methods for obtaining tire torque and wheel angle through the desired tire force include the linear tire force model [20], the non-linear Dugoff tyre model [12,21], magic tire model, and so on [22]. Information flow in Figure 10 shows the working principle of the actuator controlling layer.…”

Section: Actuator Controllermentioning

confidence: 99%

Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

et al. 2019

View full text Add to dashboard Cite

Featured Application: The proposed method is applied to the coordinated control for over-actuated vehicle platoon with an integrated hierarchical controller.Abstract: Collaborative vehicle platoon control with full drive-by-wire vehicles with four-wheel independent driving and steering (FWIDSV) has attracted broader research interests. However, the problem of cooperative vehicle platoon control in two-dimensional driving scenes remains to be solved. This paper proposes a coupling control method for path tracking and spacing-maintaining based on the reference vector field (RVF). An integrated hierarchical control structure, including the following control layer, tire force allocator layer, and an actuator controlling layer for FWIDSV is presented. Inside, the next control layer was designed according to the spacing control strategy and RVF within the limitation of the friction circle. For verifying the effectiveness of this control method, sufficient conditions for error convergence are analyzed when considering the influence of the critical parameters on the particle dynamics model. The tire force allocator layer is designed based on linear quadratic programming (LQP), which is used to distribute the total forces and yaw moment. The sliding mode control (SMC) is employed to track the desired tire forces in the actuator controlling layer. The proposed control methods are validated through simulation in intelligent cruise control (ICC) and platoon merging scenarios. The results demonstrate an effective FWIDSV platoon control approach that is based on the RVF in the 2-D driving scenes.

show abstract

“…After the road topography information is available, the road topography information can be included into the optimal cost function (23) as the following equation: When the optimisation values of ending position d 1 and terminal time τ are determined based on (26), the desired best trajectory can be determined according to Eqs. (16)- (18).…”

Section: Determine the Optimisation Cost Functionmentioning

confidence: 99%

Path Planning for Autonomous Vehicle in Off-Road Scenario

Li¹,

Du²,

Zhang³

2019

Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver

Self Cite

View full text Add to dashboard Cite

The road topography information, such as bank angle and road slope, can significantly affect the trajectory tracking performance of the autonomous vehicle, so this information needs to be considered in the trajectory planning and tracking control for off-road autonomous vehicle. In this chapter, a two-level real-time dynamically integrated spatiotemporal-based trajectory planning and control method for off-road autonomous vehicle is proposed. In the upper-level trajectory planner, the most suitable time-parameterised trajectory with the minimum values of road slope and bank angle can be selected from a set of candidate trajectories. In the lower-level trajectory tracking controller, the sliding-mode control (SMC) technique is applied to control the vehicle and achieve the desired trajectory. Finally, simulation results are presented to verify the proposed integrated trajectory planning and control method and prove that the proposed integrated method has better overall tracking control and dynamics control performance than the conventional method both in the highway scenario and off-road scenario. Furthermore, the four-wheel-independent-steering (4WIS) and four-wheel-independent-driving (4WID) vehicle shows better tracking control performance than vehicle based on two-wheel model.

show abstract

A Potential Field Approach-Based Trajectory Control for Autonomous Electric Vehicles With In-Wheel Motors

Cited by 80 publications

References 29 publications

Comparison of Path Tracking and Torque-Vectoring Controllers for Autonomous Electric Vehicles

Comparison of Path Tracking and Torque-Vectoring Controllers for Autonomous Electric Vehicles

Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

Path Planning for Autonomous Vehicle in Off-Road Scenario

Contact Info

Product

Resources

About