Road Friction Fusion for Predictive Vehicle Maneuver Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver assistance and autonomous driving systems do not effectively incorporate road user intentions when planning vehicle maneuvers, leading to inadequate safety and control in varying road friction conditions.
Innovation Solution
Fusing road friction information with predictive motion trajectories of other road users to enhance safety constraint calculations and ego vehicle control, using sensor-based methodologies for real-time data processing and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If road friction information is integrated with road user intention prediction, then vehicle safety and maneuver control are improved, but system complexity increases
Solution Approach 1:
The patent combines road friction information processing with road user intention prediction into a unified safety constraint calculation system. The friction map generated from sensor data is integrated with the object map to create a risk map, which is then used by the motion planner to generate safe trajectories. This merging of previously separate functions (friction estimation, object detection, intention prediction) into a single fused system improves reliability while managing complexity through functional integration.
2Manufacturing precision
If real-time road friction mapping is implemented, then maneuver precision is improved, but computational load increases
Solution Approach 1:
The patent divides the road environment into discrete regions or cells, creating a grid-based friction map where each cell contains friction information for a specific location. This segmentation allows the system to process road friction data in manageable units rather than as a continuous complex field. The motion planner can then query friction values for specific regions of interest, reducing the overall computational load while maintaining precision for maneuvers in high-risk or low-friction areas.
Data Source
AI summary
A vehicle control method and system, including: receiving road friction information indicating road friction estimates for a plurality of regions surrounding the vehicle; detecting and determining a predicted trajectory for an object within the plurality of regions surrounding the vehicle; wherein the predicted trajectory for the object is determined based in part on the road friction estimates for the plurality of regions surrounding the vehicle; and modifying operation of the vehicle based on the predicted trajectory for the object. The predicted trajectory for the object is determined based in part on a risk map for the plurality of regions surrounding the vehicle that is generated from a road friction map for the plurality of regions surrounding the vehicle.


