Predictive Transmission via Road Shape Recognition
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Solution Overview
Problem
Current sensor technologies in autonomous vehicles struggle to accurately recognize road shapes, such as corners or slopes, leading to limitations in predictive transmission control, especially under adverse weather conditions or when sensors are obstructed.
Innovation Solution
A predictive transmission control method utilizing GPS and high-density map data to collect and update road shape information, dividing the road into sections based on vehicle position and distance, and setting a target gear based on the road shape's gradient and curvature information to enable accurate predictive transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor technology (cameras and radars) is improved to enhance autonomous vehicle capabilities, then the system can better recognize driving environment, but the hardware cost increases significantly and technical problems remain unresolved
Solution Approach 1:
The patent introduces high-density map data as an intermediary information source between the vehicle and the external environment. Instead of relying solely on expensive sensors to directly perceive road shapes, the system uses pre-collected map data containing road gradient, curvature, and elevation information as a mediator to provide predictive transmission control, thereby reducing dependence on complex sensor hardware.
Solution Approach 2:
The system performs preliminary recognition of road shapes using high-density map data before the vehicle actually encounters them. By pre-acquiring information about upcoming slopes, curves, and intersections from the map database, the transmission control system can prepare optimal gear selections in advance, eliminating the need for complex real-time sensor analysis during critical moments.
2Productivity
If sensors are used to recognize road shapes in real-time, then predictive transmission control can be implemented, but the system fails under adverse weather conditions and when sensors are obstructed
Solution Approach 1:
The patent creates a virtual copy of the road environment using high-density map data that replicates actual road geometry, gradients, and curvature information. This digital replica serves as a reliable alternative to physical sensor measurements, providing consistent road shape information regardless of weather conditions or sensor obstructions, thereby ensuring continuous predictive transmission control capability.
3Device complexity
If the transmission control system uses current vehicle speed and accelerator pedal position only, then the control logic is simple, but predictive transmission control cannot be achieved
Solution Approach 1:
The patent adds a new dimension of information by incorporating high-density map data into the transmission control system. Instead of relying solely on current vehicle state parameters (speed, accelerator position), the system integrates spatial and temporal road geometry information from maps, creating a multi-dimensional control approach that enables predictive capabilities while maintaining relatively simple control logic through rule-based gear selection strategies.
Data Source
AI summary
The present invention relates to a predictive transmission control method through road shape recognition, and more particularly, to a control method for carrying out predictive transmission by recognizing the shape of a road utilizing information of a high density map. The present invention provides a transmission control method which can provide an accurate predictive transmission by recognizing the shape of the front road based on GPS information.