Predictive Road Banking Control for Unmapped Road Steering
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Solution Overview
Problem
Existing vehicle systems struggle to accurately predict and compensate for road banking angles on unmapped roads, leading to reactive steering adjustments that can result in understeering or oversteering, especially at high speeds.
Innovation Solution
A system and method that utilizes vehicle sensors to create a road model map based on upcoming cross-slope characteristics, predicts bank angles at multiple look-ahead points, and generates steering control signals to proactively compensate for these angles, incorporating inputs from front camera modules, LIDAR, wheel speed sensors, and inertial measurement units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive steering adjustments are used on unmapped roads, then the system is simple to operate, but vehicle control stability deteriorates due to understeering or oversteering
Solution Approach 1:
The system performs preliminary action by predicting road banking angles at multiple look-ahead points before the vehicle reaches them. The predictive road banking system calculates anticipated bank angles and generates compensating steering signals in advance, allowing the vehicle to proactively adjust to upcoming curves rather than reacting after the curve is detected. This preliminary action prevents understeering and oversteering by preparing steering corrections before the vehicle encounters the actual road banking.
Solution Approach 2:
The system applies preliminary anti-action by generating steering control signals that compensate for anticipated road banking angles before the vehicle reaches the curved section. The predictive system calculates the expected bank angle and creates an opposing steering correction in advance, counteracting the potential harmful effect of road banking before it impacts vehicle control. This prevents the vehicle from losing stability due to reactive adjustments.
2Reliability
If predictive road banking control is implemented, then vehicle control stability improves through proactive compensation, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The system achieves universality by making the predictive road banking control system adaptable to both mapped and unmapped roads. The same predictive algorithm and sensor suite operate regardless of whether high-definition map data is available. When map data is present, it supplements sensor-based predictions; when absent, the sensor-based prediction becomes the primary source. This multi-functionality allows the system to maintain improved vehicle control stability across diverse road conditions without requiring entirely different system configurations.
Solution Approach 2:
The system uses an intermediary approach by combining multiple data sources (inertial sensors, camera vision, LIDAR, and optional high-definition maps) to predict road banking angles. Rather than relying on a single complex sensor system, the patent integrates information from multiple simpler sensors through a predictive algorithm. This intermediary layer of prediction synthesizes data from various sources to produce accurate bank angle estimates, reducing the complexity burden of any single sensing component while maintaining overall system reliability.
3Measurement precision
If multiple sensors are integrated for predictive control, then measurement precision of road banking angles improves, but device complexity increases
Solution Approach 1:
The system merges multiple sensor inputs (inertial measurement unit data, camera vision data, LIDAR data, and optional map data) into a unified road banking prediction. By combining these diverse sensing modalities, the system achieves high measurement precision for bank angle predictions. The inertial sensors provide direct acceleration and orientation data, camera vision offers visual context for road geometry, and LIDAR contributes depth information. The predictive algorithm integrates these merged sensor inputs to produce accurate bank angle estimates at look-ahead points, improving measurement precision while distributing complexity across multiple standard sensors rather than requiring a single complex device.
Data Source
AI summary
A system and method for predictive vehicle road bank control on an unmapped road. A sensor within a vehicle, based on received sensor data, determines upcoming cross-slope roadway characteristics of an unmapped road, where the unmapped road comprises an absence of known cross-slope roadway characteristics. The vehicle creates a road model map based on the upcoming cross slope roadway characteristics of the unmapped road and predicts, based on the road model map, one or more bank angles at multiple look-ahead points of the upcoming roadway. The vehicle, based on the predicting of one or more bank angles, generates one or more steering control signals to compensate for the one or more bank angles at the multiple look-ahead points.