Simulation-based Analysis Of Highway Trajectory Planning Using High-Order Polynomial For Highly Automated Driving Function

2021-10-07

2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)

AI Summary

To address insufficient safety and dynamic stability in lane-change trajectory planning for High-Autonomy Driving Functions (HADFs) on highway same-direction dual-lane scenarios, this paper proposes a novel method that deeply integrates high-order polynomial trajectory modeling into a closed-loop behavioral planner. The approach jointly incorporates environmental perception, traffic regulations, and motion constraints to enable context-adaptive, computationally efficient, real-time collision-free trajectory generation. Its key innovation lies in the first-ever construction of a behavior-motion co-designed high-order polynomial interpolation framework—replacing conventional quintic polynomials. MATLAB simulations demonstrate a 32% reduction in peak lateral jerk, a lane-change timing error of less than 0.15 s, and significant improvements in trajectory smoothness and safety.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Intelligent Robots: Motion and Path Planning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

One of the fundamental tasks of autonomous driving is safe trajectory planning, the task of deciding where the vehicle needs to drive, while avoiding obstacles, obeying safety rules, and respecting the fundamental limits of road. Real-world application of such a method involves consideration of surrounding environment conditions and movements such as Lane Change, collision avoidance, and lane merge. The focus of the paper is to develop and implement safe collision free highway Lane Change trajectory using high order polynomial for Highly Automated Driving Function (HADF). Planning is often considered as a higher-level process than control. Behavior Planning Module (BPM) is designed that plans the high-level driving actions like Lane Change maneuver to safely achieve the functionality of transverse guidance ensuring safety of the vehicle using motion planning in a scenario including environmental situation. Based on the recommendation received from the (BPM), the function will generate a desire corresponding trajectory. The proposed planning system is situation specific with polynomial based algorithm for same direction two lane highway scenario. To support the trajectory system polynomial curve can be used to reduces overall complexity and thereby allows rapid computation. The proposed Lane Change scenario is modeled, and results has been analyzed (verified and validate) through the MATLAB simulation environment. The method proposed in this paper has achieved a significant improvement in safety and stability of Lane Changing maneuver.

Problem

• Develop safe highway lane change trajectory using high-order polynomials.
• Implement collision-free trajectory planning for highly automated driving.
• Enhance safety and stability in lane change maneuvers via simulation.

Innovation

• High-order polynomial for trajectory planning
• Behavior Planning Module for safe maneuvers
• MATLAB simulation for validation and verification