Szilárd Aradi

26323470000

Publications - 4

Comparison of Lateral Controllers for Autonomous Vehicles Based on Passenger Comfort Optimization

Szilárd Aradi Ádám Szabó Ákos Bokor László Palkovics

Publication Name: Proceedings of the International Conference on Informatics in Control Automation and Robotics

Publication Date: 2024-01-01

Volume: 1

Issue: Unknown

Page Range: 46-54

Description:

This paper focuses on the design of lateral controllers for autonomous vehicles. To enhance passenger comfort while concurrently maintaining minimal deviation from the desired trajectory, the developed controllers are tuned by a Genetic Algorithm, whose cost function is following the ISO 2631 Standard. Three model-based controllers, a Linear Quadratic Regulator, a Linear Quadratic Servo algorithm, and a Model Predictive Con troller have been compared in a simulation environment. The test case consists of a suburban road section, where the vehicles must successfully traverse at different velocities while minimizing the lateral acceleration and jerk affecting the passengers. To take into account the velocity-dependent dynamics of the system, the controllers are based on a Linear Parameter-Varying model of the system. The results show that the devel oped controllers meet the specified requirements regarding the equivalent acceleration, Motion Sickness Dose Value, and deviation from the desired trajectory.

Open Access: Yes

DOI: 10.5220/0012923700003822

Local Motion Planning for Overtaking Maneuvers in a Rural Road Environment

Szilárd Aradi Árpád Fehér Dániel Losonczi László Palkovics

Publication Name: Proceedings of the International Conference on Informatics in Control Automation and Robotics

Publication Date: 2024-01-01

Volume: 2

Issue: Unknown

Page Range: 220-227

Description:

This paper introduces an application of local motion planning designed explicitly for overtaking maneuvers in a rural road environment. The approach integrates multiple driving strategies for enhanced passenger comfort, including the fastest path and minimum jerk trajectory. A robust trajectory planner technique is developed using the Frenet frame, effectively considering real traffic situations, curves, and moving obstacles. Comprehensive analyses are performed on vehicle dynamics, individual cost function components, and planning and tracing times to assess the performance and computational efficiency of the proposed methods. The simulation results highlight the approach’s strengths in maintaining dynamic feasibility, ensuring safety, and enhancing passenger comfort while identifying areas for potential improvements, such as computational overhead in complex scenarios.

Open Access: Yes

DOI: 10.5220/0013001600003822

Design of Gain-Scheduled Lateral Controllers for Autonomous Vehicles †

Szilárd Aradi Ádám Szabó Ákos Bokor László Palkovics

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

This paper focuses on the design and comparative analysis of speed-dependent lateral control systems for autonomous vehicles, focusing on optimizing vehicular dynamics and passenger comfort to ensure stability and safety. Adapting control systems to varying speeds becomes crucial for maintaining stability and maneuverability as autonomous technologies progress. This study evaluates their effectiveness in real-time navigation scenarios within a simulated environment by applying gain-scheduled linear quadratic regulators and model predictive control. The results show that while traditional controllers, such as Pure Pursuit, perform adequately under constant speed conditions, adaptive model-based algorithms significantly enhance the performance, especially in dynamic driving situations involving speed variations.

Open Access: Yes

DOI: 10.3390/engproc2024079038

Minimum Curvature Trajectory Planning for Autonomous Vehicles in a Hierarchical Framework

Szilárd Aradi Árpád Fehér Dániel Losonczi László Palkovics

Publication Name: 11th 2025 International Conference on Control Decision and Information Technologies Codit 2025

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 1331-1336

Description:

This paper presents an approach for global trajectory planning using quadratic optimization and dynamic programming. In the global route planning phase, the goal is to find a route with minimal curvature for any road geometry, while a speed profile is determined by dynamic programming based on the vehicle's dynamic constraints. The method has a low computational cost and is well-suited for integration within a hierarchical system architecture, where the trajectory can be further refined with local route planning to enable the vehicle to adapt to changing environmental conditions. The developed method ensures vehicle stability while achieving the highest possible speed. The approach is implemented in the Frenet coordinate system within a self-developed simulation environment that allows for a comprehensive evaluation of vehicle dynamics, trajectory feasibility, and performance metrics. The results show that the proposed method can generate smooth and dynamically feasible trajectories while balancing curvature minimization, safety, and computational efficiency, making it well-suited for real-world applications.

Open Access: Yes

DOI: 10.1109/CoDIT66093.2025.11321486