Autonomous Vehicle Lane Routing Feasibility Filter
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Solution Overview
Problem
Autonomous vehicles face challenges in selecting safe and smooth routes, particularly when generating new routes or rerouting, as existing systems may include infeasible paths that lead to unsafe and uncomfortable changes in direction.
Innovation Solution
A computer-implemented method and system that generates lane plan data, identifies and removes infeasible lane plans by determining smooth motion within a forthcoming distance, using a motion planning algorithm to produce solved lane plan data and control vehicle motion based on feasible lane plans, ensuring safe and comfortable navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple lane plans are generated to provide routing options, then the versatility and adaptability of route selection is improved, but the complexity of evaluating and selecting safe routes increases
Solution Approach 1:
The evaluation process is segmented into distinct phases: first evaluating lanes within a forthcoming distance for smoothness, then using those feasible lanes as constraints for the motion planning algorithm. This divides the complex overall evaluation into manageable segments that can be processed systematically.
Solution Approach 2:
The system performs preliminary evaluation of lane smoothness within a forthcoming distance before committing to full motion planning. By pre-identifying feasible lanes that maintain smooth motion, the system filters out infeasible options early, reducing the complexity of subsequent route selection.
2Loss of time
If the vehicle follows a direct route to destination, then the travel time is reduced, but the motion smoothness and safety may be compromised
Solution Approach 1:
The system dynamically adjusts route selection based on current vehicle state and forthcoming conditions. By evaluating lane smoothness relative to the forthcoming distance and current speed, the system adapts route choices to maintain motion continuity, preventing sudden directional changes even when taking direct routes.
Solution Approach 2:
The system uses feedback from the motion planning algorithm to identify infeasible lane plans that would cause unsafe motion. This feedback loop allows the system to reject direct but unsafe routes and select alternative paths that maintain both efficiency and smoothness.
3Reliability
If lane plans are filtered to ensure smooth motion, then the safety and comfort of vehicle operation is improved, but the number of available route options may be reduced
Solution Approach 1:
The system changes the parameter of evaluation from simple destination reachability to smoothness within a forthcoming distance. By adjusting the evaluation criteria to consider motion continuity and vehicle dynamics, the system identifies feasible lanes that satisfy both safety requirements and route diversity needs.
Solution Approach 2:
The system performs preliminary identification of feasible lanes before final route selection. This preliminary action maintains a set of pre-validated smooth lanes that can be quickly selected from, preserving route options while ensuring safety constraints are met.
Data Source
AI summary
Systems and method are provided for controlling a vehicle. The systems and methods calculate lane plan data including a set of lane plans defining a route from a start location to a destination location, solve a motion planning algorithm to produce solved lane plan data defining a solved lane plan and a trajectory therefor, receive forthcoming distance data representing a forthcoming distance, determine a feasible lane based on the solved lane plan data within the forthcoming distance, remove a lane plan from the lane plan data to produce feasible lane plan data including a feasible lane plan defining a route from the start location to the destination location, and control motion of the vehicle based on the feasible lane plan data.