A non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of driver’s characteristics

2018 ◽  
Vol 233 (10) ◽  
pp. 2405-2420 ◽  
Author(s):  
Kuoran Zhang ◽  
Jinxiang Wang ◽  
Nan Chen ◽  
Guodong Yin
Keyword(s):  
Trajectory Planning ◽  
Vehicle Dynamics ◽  
Cooperative Control ◽  
Control Algorithm ◽  
System A ◽  
Vehicle To Vehicle ◽  
Vehicle System ◽  
Planning Algorithm ◽  
Vehicle Trajectory ◽  
Driver’S Characteristics

This paper presents a non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of the characteristics of different drivers. The driver–vehicle model considering vehicle dynamics and characteristics of the drivers is used to formulate a vehicle-to-vehicle encountering system. A non-cooperative control algorithm considering each of the driver–vehicle system as a player is employed to plan collision-free trajectories for the encountering vehicles with respective initial driving intentions. The non-cooperative problem is solved with the theory of Nash equilibrium and is ultimately converted to a standard nonlinear Model Predictive Control problem. Simulations are conducted in the scenarios of the lane-exchanging and overtaking with different initial vehicle speeds to verify the effectiveness of the proposed algorithm. Results show that the algorithm can accomplish the trajectory-planning task with consideration of both the safety requirement and the characteristics of drivers. The simulation results also show that the proposed algorithm has effectiveness for trajectory planning in different vehicle-to-vehicle encountering scenarios.

Multi-Car Convex Feasible Set Algorithm in Trajectory Planning

2020 ◽  
Author(s):  
Jing Huang ◽  
Changliu Liu
Keyword(s):  
Convex Optimization ◽  
Quadratic Programming ◽  
Real Time ◽  
Trajectory Planning ◽  
Autonomous Driving ◽  
Curse Of Dimensionality ◽  
Planning Problem ◽  
Feasible Set ◽  
Planning Algorithm ◽  
Vehicle Trajectory

Abstract Trajectory planning is an essential module for autonomous driving. To deal with multi-vehicle interactions, existing methods follow the prediction-then-plan approaches which first predict the trajectories of others then plan the trajectory for the ego vehicle given the predictions. However, since the true trajectories of others may deviate from the predictions, frequent re-planning for the ego vehicle is needed, which may cause many issues such as instability or deadlock. These issues can be overcome if all vehicles can form a consensus by solving the same multi-vehicle trajectory planning problem. Then the major challenge is how to efficiently solve the multi-vehicle trajectory planning problem in real time under the curse of dimensionality. We introduce a novel planner for multi-vehicle trajectory planning based on the convex feasible set (CFS) algorithm. The planning problem is formulated as a non-convex optimization. A novel convexification method to obtain the maximal convex feasible set is proposed, which transforms the problem into a quadratic programming. Simulations in multiple typical on-road driving situations are conducted to demonstrate the effectiveness of the proposed planning algorithm in terms of completeness and optimality.

scholarly journals State Estimation for Cooperative Lateral Vehicle Following Using Vehicle-to-Vehicle Communication

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 651
Author(s):  
Wouter Schinkel ◽  
Tom van der Sande ◽  
Henk Nijmeijer
Keyword(s):  
State Estimation ◽  
Cooperative Control ◽  
The State ◽  
State Estimator ◽  
Estimation Process ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Control Schemes ◽  
Input Signals ◽  
Vehicle To Vehicle Communication

A cooperative state estimation framework for automated vehicle applications is presented and demonstrated via simulations, the estimation framework is used to estimate the state of a lead and following vehicle simultaneously. Recent developments in the field of cooperative driving require novel techniques to ensure accurate and stable vehicle following behavior. Control schemes for the cooperative control of longitudinal and lateral vehicle dynamics generally require vehicle state information about the lead vehicle, which in some cases cannot be accurately measured. Including vehicle-to-vehicle communication in the state estimation process can provide the required input signals for the practical implementation of cooperative control schemes. This study is focused on demonstrating the benefits of using vehicle-to-vehicle communication in the state estimation of a lead and following vehicle via simulations. The state estimator, which uses a cascaded Kalman filtering process, takes the operating frequencies of different sensors into account in the estimation process. Simulation results of three different driving scenarios demonstrate the benefits of using vehicle-to-vehicle communication as well as the attenuation of measurement noise. Furthermore, in contrast to relying on low frequency measurement data for the input signals of cooperative control schemes, the state estimator provides a state estimate at every sample.

scholarly journals Retraction: Kwon et al. Cooperative Control Algorithm for Friction and Regenerative Braking Systems Considering Temperature Characteristics. World Electr. Veh. J. 2015, 7, 287–298

2021 ◽  
Vol 12 (2) ◽  
pp. 68
Author(s):  
Keyword(s):  
Cooperative Control ◽  
Control Algorithm ◽  
Regenerative Braking ◽  
Temperature Characteristics

The journal retracts the article, ”Cooperative control algorithm for friction and regenerative braking systems considering temperature characteristics” [...]

scholarly journals Control system of 4-DOF palletizing robot based on improved R control multi-objective trajectory planning

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110027
Author(s):  
Jianqiang Wang ◽  
Yanmin Zhang ◽  
Xintong Liu
Keyword(s):  
Control System ◽  
Trajectory Planning ◽  
Robot Control ◽  
Machining Process ◽  
Planning System ◽  
Positioning Accuracy ◽  
Multi Objective ◽  
Planning Algorithm ◽  
Function Testing ◽  
Robot Control System

To realize efficient palletizing robot trajectory planning and ensure ultimate robot control system universality and extensibility, the B-spline trajectory planning algorithm is used to establish a palletizing robot control system and the system is tested and analyzed. Simultaneously, to improve trajectory planning speeds, R control trajectory planning is used. Through improved algorithm design, a trajectory interpolation algorithm is established. The robot control system is based on R-dominated multi-objective trajectory planning. System stack function testing and system accuracy testing are conducted in a production environment. During palletizing function testing, the system’s single-step code packet time is stable at approximately 5.8 s and the average evolutionary algebra for each layer ranges between 32.49 and 45.66, which can save trajectory planning time. During system accuracy testing, the palletizing robot system’s repeated positioning accuracy is tested. The repeated positioning accuracy error is currently 10−1 mm and is mainly caused by friction and the machining process. By studying the control system of a four-degrees-of-freedom (4-DOF) palletizing robot based on the trajectory planning algorithm, the design predictions and effects are realized, thus providing a reference for more efficient future palletizing robot design. Although the working process still has some shortcomings, the research has major practical significance.

Cooperative Control of Vehicle Swarms for Acoustic Target Localization by Energy Flows

2004 ◽  
Vol 126 (4) ◽  
pp. 891-895 ◽  
Author(s):  
J. L. Dohner and ◽  
G. R. Eisler ◽  
B. J. Driessen ◽  
J. Hurtado
Keyword(s):  
Cooperative Control ◽  
Control Algorithm ◽  
Open Space ◽  
Target Localization ◽  
Pressure Measurements ◽  
Energy Flows ◽  
Acoustic Target ◽  
Robotic Vehicles ◽  
Novel Algorithm

A control algorithm has been developed and experimentally validated for guiding swarms of robotic vehicles to acoustic targets. This novel algorithm uses pressure measurements from a set of sensors, each attached to a vehicle of the swarm, to deduce energy flows from the environment, and to move in the direction of maximum reflected intensity while controlling constraints between vehicles. The algorithm was validated using a collective of eight hand-placed microphones in an open-space area with a 50-m separation between an emitter and scatterer.

Vehicle coupled bifurcation analysis of steering angle and driving torque

2021 ◽  
pp. 095440702098540
Author(s):  
Xianbin Wang ◽  
Shuming Shi
Keyword(s):  
Bifurcation Analysis ◽  
Hybrid Method ◽  
Vehicle Dynamics ◽  
Front Wheel ◽  
Steering Angle ◽  
Driving Mode ◽  
Vehicle System ◽  
Autonomous Equation ◽  
Real Coded Genetic Algorithm ◽  
Driving Torque

The mechanism of vehicle dynamics steering bifurcation has almost been confirmed. But the present steering bifurcation mechanism cannot explain the bifurcation phenomena caused by the driving torque. As a result, the vehicle coupled bifurcation analysis of the steering angle and driving torque has not been studied. Based on the five degrees of freedom (5DOF) vehicle system dynamics model with driving torque involved, the vehicle dynamics equilibriums under different driving torque and driving mode were searched by a hybrid method in this paper. The hybrid method combined the real-coded Genetic Algorithm with Quasi-Newton gradient method. According to the definition of static bifurcation of nonlinear systems, the equilibrium bifurcation of 5DOF vehicle system was confirmed. Then, the 5DOF vehicle system model was transformed into autonomous equation with the front wheel steering angle as intermediate variable. From the two aspects of constant steering angle amplitude and constant driving torque, the bifurcation diagrams of different driving mode were calculated. The vehicle coupled bifurcation characteristics of steering angle and driving torque were analyzed. The results show that the values of the driving torque will directly affect the bifurcation characteristics of vehicle dynamics system. The coupled feature of the front wheel steering angle and driving torque effect on vehicle bifurcation is obvious.

Study of Hydraulic Servo System Based on Fuzzy Sliding Mode Algorithm

2013 ◽  
Vol 753-755 ◽  
pp. 2674-2678
Author(s):  
Kun Yang ◽  
Cai Jun Liu ◽  
Shu Min Liu
Keyword(s):  
Control Algorithm ◽  
Sliding Mode ◽  
Servo System ◽  
Time Varying ◽  
External Interference ◽  
System A ◽  
Hydraulic Servo ◽  
Fuzzy Sliding Mode ◽  
Hydraulic Servo System ◽  
Position Servo

Based on the situation that the hydraulic position servo system is easily influenced by the external interference and the parameters of which are different with time-varying, the fuzzy control can soften the buffeting and the sliding algorithm has no the same problems as the hydraulic position servo system, a brandly-new fuzzy sliding control algorithm is designed. In the simulation process, within the parameters of simulated time-varying and outside strong interference, the results show that the hydraulic servo system based on fuzzy sliding mode control algorithm has a greater resistance to internal and external interference and time-varying parameters.

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