Driving Scenario Parameter Allocation for Vehicle Torque Handover
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Solution Overview
Problem
Existing intelligent driving systems lack flexibility in adapting to complex driving environments, leading to inefficiencies in torque information processing between intelligent driving apparatuses, vehicle control apparatuses, and motors.
Innovation Solution
A method for allocating travel parameters based on current driving scenarios, enabling intelligent control apparatuses to determine the scenario and send parameters directly to motors or vehicle control apparatuses accordingly, enhancing precision and safety by reducing response time and ensuring smooth handover of control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle control apparatus directly sends torque information to the motor in intelligent driving mode, then the working mode is simple, but the system cannot adapt to increasingly complex driving environments
Solution Approach 1:
The patent implements dynamic scenario recognition that automatically identifies the current driving scenario (intelligent driving, manual driving, fault scenario, etc.) and dynamically adjusts the control architecture. The system transitions between different working modes based on real-time conditions, enabling adaptability to complex environments while maintaining operational simplicity through automated scenario-based switching
2Adaptability or versatility
If the intelligent driving apparatus calculates and sends torque information directly to the motor, then the response is direct, but the system lacks flexibility in parameter allocation for different scenarios
Solution Approach 1:
The system performs preliminary scenario recognition and classification before executing parameter allocation. By pre-defining multiple driving scenarios and their corresponding optimal parameter allocation strategies, the system prepares response protocols in advance, enabling rapid and flexible parameter distribution without real-time decision delays
3Reliability
If the system uses a fixed working mode between intelligent driving apparatus, vehicle control apparatus, and motor, then the control logic is simple, but it is not applicable to various driving scenarios
Solution Approach 1:
The patent implements dynamic scenario recognition that automatically identifies the current driving scenario (intelligent driving, manual driving, fault scenario, etc.) and dynamically adjusts the control architecture. The system transitions between different working modes based on real-time conditions, enabling adaptability to complex environments while maintaining operational simplicity through automated scenario-based switching
Solution Approach 2:
The system changes operational parameters based on detected scenarios. When different scenarios are recognized (intelligent driving low-speed, intelligent driving non-low-speed, manual driving, fault scenarios), the system adjusts parameter allocation paths, response thresholds, and control strategies accordingly, ensuring reliable operation across diverse conditions without requiring complex manual reconfiguration
Data Source
AI summary
Example travel parameter allocation methods and devices are disclosed. One example allocation method includes obtaining a travel parameter and determining a current driving scenario. The travel parameter is sent to a motor or a vehicle control apparatus based on the current driving scenario. The current driving scenario includes an intelligent driving scenario, an intelligent driving low-speed scenario, an intelligent driving non-low-speed scenario, a manual driving normal scenario, or a manual driving fault scenario.