Lane-Level Route Planning With Contingency Paths for AVs
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Solution Overview
Problem
Traditional route planning systems lack lane-level information, making them inadequate for autonomous driving as they fail to account for specific lane changes and contingencies, relying on abstract road-level planning that does not consider the complexities required for autonomous vehicle navigation.
Innovation Solution
A lane-level route planning method that uses a navigation map incorporating probabilities and multi-objective planning to determine optimal routes, including lane changes and contingency plans, based on historical data and user preferences, to ensure safe and efficient autonomous vehicle navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If road-level route planning is used, then the route planning system is simple and easy to operate, but it lacks lane-level information required for autonomous driving
Solution Approach 1:
The patent segments the route planning process into two distinct levels: road-level planning for high-level route determination and lane-level planning for specific lane navigation. This segmentation allows the system to maintain simplicity at the road level while incorporating detailed lane-level information when needed for autonomous driving operations.
Solution Approach 2:
The patent adds a lane-level dimension to the traditional road-level route planning system. By introducing lane segments as an additional layer of abstraction above road segments, the system transforms from two-dimensional road network planning to three-dimensional planning that includes lane-specific information, enabling autonomous vehicles to navigate with precise lane-level guidance.
2Reliability
If lane-level route planning is implemented, then autonomous driving reliability is improved, but system complexity increases
Solution Approach 1:
The patent divides the complex route planning system into manageable segments: road segments for basic routing and lane segments for detailed lane-level navigation. This segmentation reduces system complexity by organizing information hierarchically, where lane segments are associated with specific road segments, allowing the system to process only relevant lane-level details when needed rather than managing all possible lane information simultaneously.
Solution Approach 2:
The patent performs preliminary actions by pre-computing and storing lane-level route information in advance. The system calculates lane-level routes ahead of time and stores them in a data structure that can be quickly retrieved and executed during autonomous driving operations, reducing real-time computational complexity while maintaining high reliability.
3Use of energy by moving object
If traditional road-level planning is used, then computational resources are conserved, but unsafe maneuvers may be required
Solution Approach 1:
The patent applies partial action by implementing lane-level planning only where and when it is needed for autonomous driving operations, rather than applying it universally to all route planning scenarios. The system selectively activates detailed lane-level processing for autonomous vehicles while maintaining simpler road-level planning for other contexts, optimizing computational resource usage while ensuring safety where required.
Data Source
AI summary
Route planning includes receiving a destination, obtaining a lane-level route to the destination using a map, and controlling an autonomous vehicle (AV) to traverse the lane-level route. The lane-level route includes a transition from a first segment of a first lane of a road to a second segment of a second lane of the road.