Multi-Vehicle Trajectory Planning with Priority Scheme Selection
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Solution Overview
Problem
Existing multi-vehicle collaborative trajectory planning methods suffer from poor solution quality and slow solution speed, failing to meet the demands of efficient and effective automatic driving scenarios.
Innovation Solution
A method involving determining multiple vehicle priority schemes, using sequential planning policies to generate collaborative planning schemes, and performing quality evaluations to select an optimal scheme, reducing the need to solve a complete set of priority sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a complete set of priority sequences is solved to ensure optimal collaborative trajectory planning, then the solution quality is improved, but the computation time and complexity increase significantly
Solution Approach 1:
The patent segments the complete priority sequence problem into multiple sub-problems by dividing vehicles into different groups (e.g., first group and second group) with different planning priorities. This allows the system to solve trajectories for different vehicle groups separately rather than solving all possible priority sequences simultaneously, thereby reducing computation time while maintaining solution quality.
Solution Approach 2:
The patent applies partial action by not solving the complete set of all possible priority sequences, but rather solving a subset of priority sequences that are most relevant to the current scenario. The system determines trajectories for different vehicle groups based on partial priority considerations, which reduces computational load while still achieving satisfactory collaborative planning results.
2Manufacturing precision
If multiple vehicles are planned simultaneously to ensure collaborative optimization, then the solution quality is improved, but the device complexity and calculation load increase
Solution Approach 1:
The patent divides the multi-vehicle planning problem into segmented groups (first vehicle group and second vehicle group) with different planning priorities. Each group is processed separately through different planning modules, reducing the complexity of simultaneous multi-vehicle optimization while maintaining collaborative effects through coordinated priority management.
Solution Approach 2:
The patent implements dynamic priority adjustment where the planning priority of different vehicle groups can be changed based on real-time conditions. The system dynamically switches between different priority schemes (e.g., first priority scheme for first group, second priority scheme for second group), allowing flexible adaptation without requiring complex static optimization of all vehicles simultaneously.
3Manufacturing precision
If traditional trajectory planning methods are used to ensure comprehensive coverage of all scenarios, then the solution quality is improved, but the productivity and efficiency decrease
Solution Approach 1:
The patent performs preliminary classification of vehicles into different groups based on their characteristics and priorities before trajectory planning. This preliminary action allows the system to apply optimized planning strategies specific to each group, improving both solution quality and efficiency by avoiding unnecessary computation for vehicles that don't require full collaborative optimization.
Solution Approach 2:
The patent changes the planning parameters by introducing group-based priority levels and different planning schemes for different vehicle groups. This parameter change enables the system to adjust computation intensity based on vehicle importance, improving productivity by focusing computational resources on critical vehicles while maintaining solution quality through appropriate priority management.
Data Source
AI summary
Provided is a multi-vehicle collaborative trajectory planning method, apparatus (600) and system, and a device, a storage medium, and a computer program product. The method comprises: determining a specific number of different multi-vehicle priority schemes for multiple vehicles (S101); determining, by using a sequential planning policy, a corresponding collaborative planning scheme for each multi-vehicle priority scheme (S102); performing quality evaluation on each collaborative planning scheme to obtain a quality evaluation result (S103); and according to the quality evaluation result, determining a target collaborative planning scheme from the specific number of collaborative planning schemes (S104).