MPC trajectory planner for autonomous driving solved by genetic algorithm technique

نویسندگان

چکیده

Autonomous vehicle's technology is expected to be disruptive for automotive industry in next years. This paper proposes a novel real-time trajectory planner based on Nonlinear Model Predictive Control (NMPC) algorithm. A nonlinear single track vehicle model with Pacejka's lateral tyre formulas has been implemented. The numerical solution of the NMPC problem obtained by means implementation genetic algorithm strategy. Numerical results are discussed through simulations that shown reasonable behavior proposed strategy presence static or moving obstacles as well wide rage road friction conditions. Moreover made possible reported computational time analysis.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Path and velocity trajectory selection in an anticipative kinodynamic motion planner for autonomous driving

This paper presents an approach for plan generation, selection and pruning of trajectories for autonomous driving, capable of dealing with dynamic complex environments, such as driving in urban scenarios. The planner first discretizes the plan space and searches for the best trajectory and velocity profile of the vehicle. The main contributions of this work are the use of G-splines for path gen...

متن کامل

Multi-objective Genetic Manipulator Trajectory Planner

This paper proposes a multi-objective genetic algorithm to optimize a manipulator trajectory. The planner has several objectives namely the minimization of the space and join arm displacements and the energy required in the trajectory, without colliding with any obstacles in the workspace. Simulations results are presented for robots with two and three degrees of freedom, considering the optimi...

متن کامل

Genetic Trajectory Planner for a Manipulator with Acceleration Parametrization

This paper presents a genetic trajectory planning method of a robot manipulator producing the optimal trajectory between two end points. Genetic algorithm based methods seldom require a priori knowledge of a problem. Furthermore, they do not tend to fall into local optima and proceed toward the global optimum. However, they have di culty in handling equality constraints of trajectory boundary c...

متن کامل

Multi-objective robust optimization model for social responsible closed-loop supply chain solved by non-dominated sorting genetic algorithm

In this study a supply chain network design model has been developed considering both forward and reverse flows through the supply chain. Total Cost, environmental factors such as CO2 emission, and social factors such as employment and fairness in providing job opportunities are considered in three separate objective functions. The model seeks to optimize the facility location proble...

متن کامل

Safe Trajectory Synthesis for Autonomous Driving in Unforeseen Environments

Path planning for autonomous vehicles in arbitrary environments requires a guarantee of safety, but this can be impractical to ensure in real-time when the vehicle is described with a high-fidelity model. To address this problem, this paper develops a method to perform trajectory design by considering a low-fidelity model that accounts for model mismatch. The presented method begins by computin...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Vehicle System Dynamics

سال: 2021

ISSN: ['0042-3114', '1744-5159']

DOI: https://doi.org/10.1080/00423114.2021.1999991