Autonomous Vehicle Path Follower Correction via Lateral and Longitudinal Re-entry Planning
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Solution Overview
Problem
Existing motion planning algorithms for autonomous vehicles are either computationally intensive or not designed to handle multiple scenarios for urban and highway driving, leading to inefficiencies in processing and path correction.
Innovation Solution
The implementation of a lateral re-entry planner system and a longitudinal re-entry planner system to correct for path errors, generating path correction commands based on determined trajectories to optimize vehicle path following, thereby improving processing efficiency and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing motion planning algorithms are used for autonomous vehicles, then path planning can be performed, but processing efficiency is low and computational resources are excessive
Solution Approach 1:
The motion planning algorithm is divided into multiple independent modules including a path following module, a lateral re-entry module, and a longitudinal re-entry module. Each module handles specific aspects of path correction independently, reducing computational complexity and improving processing efficiency by avoiding redundant calculations across the entire system.
2Adaptability or versatility
If existing motion planning algorithms are used for autonomous vehicles, then basic path following can be achieved, but adaptability to multiple scenarios is insufficient
Solution Approach 1:
The motion planning system is designed with universal modules that can handle multiple driving scenarios including urban environments, highways, and various road conditions. The lateral and longitudinal re-entry modules provide multi-functional path correction capabilities that adapt to different scenarios without requiring separate specialized algorithms, thereby improving versatility while controlling system complexity.
Data Source
AI summary
Systems and methods are provided for generating a vehicle path to operate an autonomous vehicle. A method includes using a lateral re-entry planner system to correct for a lateral reentry error. A longitudinal re-entry planner system is used to correct a longitudinal reentry error. Path correction commands are generated based upon the corrections provided by the lateral re-entry planner system and the longitudinal re-entry planner system.