Prediction of a vehicle maximum forward speed to pass double lane change manoeuvre

2013 ◽  
Vol 1 (1) ◽  
pp. 49
Author(s):  
Xiaobo Yang
Keyword(s):  
Lane Change ◽  
Forward Speed ◽  
Double Lane Change

A Comparison of Trajectory Planning and Control Frameworks for Cooperative Autonomous Driving

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Icaro Bezerra Viana ◽  
Husain Kanchwala ◽  
Kenan Ahiska ◽  
Nabil Aouf
Keyword(s):  
Trajectory Planning ◽  
Cooperative Behavior ◽  
Autonomous Driving ◽  
General Idea ◽  
Mixed Integer ◽  
Quadratic Program ◽  
Change Scenario ◽  
Planning Problem ◽  
Lane Change ◽  
Double Lane Change

Abstract This work considers the cooperative trajectory-planning problem along a double lane change scenario for autonomous driving. In this paper, we develop two frameworks to solve this problem based on distributed model predictive control (MPC). The first approach solves a single nonlinear MPC problem. The general idea is to introduce a collision cost function in the optimization problem at the planning task to achieve a smooth and bounded collision function, and thus to prevent the need to implement tight hard constraints. The second method uses a hierarchical scheme with two main units: a trajectory-planning layer based on mixed-integer quadratic program (MIQP) computes an on-line collision-free trajectory using simplified motion dynamics, and a tracking controller unit to follow the trajectory from the higher level using the nonlinear vehicle model. Connected and automated vehicles (CAVs) sharing their planned trajectories lay the foundation of the cooperative behavior. In the tests and evaluation of the proposed methodologies, matlab-carsim cosimulation is utilized. carsim provides the high-fidelity model for the multibody vehicle dynamics. matlab-carsim conjoint simulation experiments compare both approaches for a cooperative double lane change maneuver of two vehicles moving along a one-way three-lane road with obstacles.

scholarly journals Lateral control of an autonomous vehicle using integrated backstepping and sliding mode controller

2018 ◽  
Vol 233 (1) ◽  
pp. 141-151 ◽  
Author(s):  
Armin Norouzi ◽  
Milad Masoumi ◽  
Ali Barari ◽  
Saina Farrokhpour Sani
Keyword(s):  
Optimization Algorithm ◽  
Sliding Mode ◽  
Autonomous Vehicle ◽  
Lane Change ◽  
Lateral Control ◽  
Lane Changing ◽  
Dynamic Constraints ◽  
Bicycle Model ◽  
Double Lane Change ◽  
Backstepping Controller

In this paper, a novel Lyapunov-based robust controller by using meta-heuristic optimization algorithm has been proposed for lateral control of an autonomous vehicle. In the first step, double lane change path has been designed using a fifth-degree polynomial (quantic) function and dynamic constraints. A lane changing path planning method has been used to design the double lane change manoeuvre. In the next step, position and orientation errors have been extracted based on the two-degree-of-freedom vehicle bicycle model. A combination of sliding mode and backstepping controllers has been used to control the steering in this paper. Overall stability of the combined controller has been analytically proved by defining a Lyapunov function and based on Lyapunov stability theorem. The proposed controller includes some constant parameters which have effects on controller performance; therefore, particle swarm optimization algorithm has been used for finding optimum values of these parameters. The comparing result of the proposed controller with backstepping controller illustrated the better performance of the proposed controller, especially in the low road frictions. Simulation of designed controllers has been conducted by linking CarSim software with Matlab/Simulink which provides a nonlinear full vehicle model. The simulation was performed for manoeuvres with different durations and road frictions. The proposed controller has outperformed the backstepping controller, especially in low frictions.

Driving simulator parameterization using double-lane change steering metrics as recorded on five modern cars

2012 ◽  
Vol 26 ◽  
pp. 96-112 ◽  
Author(s):  
Diomidis Katzourakis ◽  
Joost C.F. de Winter ◽  
Stefan de Groot ◽  
Riender Happee
Keyword(s):  
Driving Simulator ◽  
Lane Change ◽  
Double Lane Change

scholarly journals Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

2020 ◽  
Author(s):  
Kai Yang ◽  
Xiaolin TANG ◽  
Yechen Qin ◽  
Yanjun Huang ◽  
Hong Wang ◽  
...  
Keyword(s):  
Feedback Control ◽  
Model Predictive Control ◽  
Comparative Study ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
State Feedback ◽  
Maximum Velocity ◽  
State Feedback Control ◽  
Lane Change ◽  
Double Lane Change

Abstract A comparative study of model predictive control (MPC) schemes and robust A state feedback control (RSC) method for trajectory tracking, is proposed in this paper. Both MPC-based and RSC-based tracking controllers are designed on the basis of a 3-DOF vehicle model, including longitudinal, lateral and yaw motions. The main objective of this paper is to compare both controllers’ performance in tracking expected trajectory under different scenarios. Therefore, three cases, namely, verification test, double lane change test and curve test, were built in Carsim-Simulink joint platform. The simulation results indicate that MPC controller performed better in terms of accuracy and responding time under well driving conditions. However, in the test of double lane change manoeuvre where the road adhesion was set as 0.2, the maximum velocity RSC can execute was 14m/s, while that for MPC was 10m/s. In addition, in the curve test, the maximum velocity MPC can carry out was only 9m/s and that for RSC was 12m/s. In conclusion, RSC was robust and stable when the driving conditions was worse, while MPC was prone to be unstable.

A novel decision-making unit for automated maneuver of articulated vehicles in real traffic situations

2019 ◽  
Vol 234 (1) ◽  
pp. 152-171 ◽  
Author(s):  
Saeed Shojaei ◽  
Ali Rahmani Hanzaki ◽  
Shahram Azadi ◽  
Mohammad Amin Saeedi
Keyword(s):  
Decision Making ◽  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Time Range ◽  
Lane Change ◽  
Mode Control ◽  
Articulated Vehicle ◽  
Double Lane Change ◽  
Real Traffic

In this paper, a new decision-making algorithm for double lane change maneuver of an articulated vehicle in real dynamic circumstances is studied. A novel method for determining the decision conditions is used based on the articulated vehicle kinematics and dynamics. Through this method, several points of the articulated vehicle are considered in various situations when conducting double lane change maneuver, and the critical points are determined. A new realistic dynamic method is used based on a 16-degrees of freedom dynamic model of the articulated vehicle. The sliding mode control method is utilized to increase the method efficiency. Therefore, the least safe time to perform the double lane change maneuver is extracted based on the sliding mode control method as tracking control. A new Articulated Vehicle Least safe time formulation is determined for dynamic circumstances. Based on the results of simulated test, the acceptable time range is also established for conducting the lane change maneuver. The lane change maneuver is generalized to the double lane change maneuver. Decision-making algorithm is introduced based on real traffic situations. The dynamic approach and the decision-making algorithm are verified. Results show the validity of the reflected method meaning that the decision-making algorithm is acceptable.

Optimization of vehicle suspension parameters based on ride comfort and stability requirements

2021 ◽  
pp. 095440702098305
Author(s):  
Ryan Rodrigues Moreira Resende da Silva ◽  
Igor Lucas Reinaldo ◽  
Daniel Pinheiro Montenegro ◽  
Gustavo Simão Rodrigues ◽  
Elias Dias Rossi Lopes
Keyword(s):  
Ride Comfort ◽  
Computational Cost ◽  
Optimization Methods ◽  
Lane Change ◽  
Stochastic Algorithm ◽  
Lateral Dynamics ◽  
Vehicle Suspensions ◽  
Suspension Parameters ◽  
Double Lane Change ◽  
Safety And Stability

The use of optimization methods in engineering is growing, allowing the best possible way to fulfill the requirements of the project. For vehicle suspensions, there are various conditions, which involve comfort, safety, stability, maneuverability, among others. A safety and stability evaluation is carried out by several tests, including Double Lane Change. In this maneuver, the vehicle must change lanes quickly twice, allowing it to be assessed for stability in sudden movements. For ride comfort, it is common for the design to be based on the vehicle’s natural vibration frequencies. In this context, this work aims to present a methodology for optimizing the suspension parameters of a vehicle, based on the natural frequencies of vibration and the simulation of a Double Lane Change maneuver. For that, it is employed vertical and lateral dynamics mathematical models, with hypotheses that allow the adequate adaptation to the represented phenomena. Finally, Particle Swarm Optimization (PSO) is used, which is a stochastic algorithm, based on nature. It has low computational cost, with reasonable results, allowing the parameters to be estimated and comprising the two objectives simultaneously.

Utilization of Actuators to Improve Vehicle Stability at the Limit: From Hydraulic Brakes Toward Electric Propulsion

2011 ◽  
Vol 133 (5) ◽  
Author(s):  
Mats Jonasson ◽  
Johan Andreasson ◽  
Stefan Solyom ◽  
Bengt Jacobson ◽  
Annika Stensson Trigell
Keyword(s):  
Nonlinear Optimization ◽  
Electric Propulsion ◽  
Complex Interaction ◽  
Final Evaluation ◽  
Vehicle Stability ◽  
Control Allocation ◽  
Lane Change ◽  
Safety Critical ◽  
Double Lane Change ◽  
Nonconvex Constraints

The capability of over-actuated vehicles to maintain stability during limit handling is studied in this paper. A number of important differently actuated vehicles, equipped with hydraulic brakes toward more advanced chassis solutions, are presented. A virtual evaluation environment has specifically been developed to cover the complex interaction between the driver and the vehicle under control. In order to fully exploit the different actuators setup, and the hard nonconvex constraints they possess, the principle of control allocation by nonlinear optimization is successfully employed. The final evaluation is made by exposing the driver and the over-actuated vehicles to a safety-critical double lane change. Thereby, the differently actuated vehicles are ranked by a quantitative indicator of stability.

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