Autonomous Vehicle Speed Control Unit Gain Determination
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Solution Overview
Problem
Conventional motion planning and speed control systems for autonomous vehicles do not accurately account for differences in vehicle types and driving conditions, leading to inefficient and potentially unsafe operation, as they rely on a one-size-fits-all approach without considering factors like road conditions, weather, and vehicle weight.
Innovation Solution
A system that collects real-time driving statistics data to determine a unit gain for speed control, using a predictive model to adjust throttle and brake commands based on actual acceleration and deceleration rates, allowing for dynamic adaptation to specific driving environments and vehicle conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional motion planning and control systems apply the same planning and control to all types of vehicles, then the system complexity is reduced, but the accuracy and smoothness of motion control deteriorates
Solution Approach 1:
The patent applies local quality by introducing vehicle-type-specific parameters and characteristics into the motion planning and control system. Different vehicle types (e.g., autonomous vehicles, conventional vehicles, two-wheelers) are assigned distinct motion characteristics, allowing each vehicle type to receive tailored control parameters rather than a universal approach, thereby improving accuracy without proportionally increasing overall system complexity.
Solution Approach 2:
The system dynamically adapts control parameters based on real-time vehicle type identification and characteristics. The motion planning module adjusts planning parameters and the control module adjusts control parameters dynamically according to the detected vehicle type, enabling the system to optimize performance for each vehicle type while maintaining a unified underlying architecture.
2Measurement precision
If unit gain calibration is performed manually for each vehicle under different circumstances, then the precision of speed control is improved, but the time and effort required for calibration increases
Solution Approach 1:
The system implements self-service through automated unit gain determination. The processor automatically determines unit gains for throttle and brake controls by analyzing actual vehicle behavior data collected during operation, eliminating the need for manual calibration procedures. This allows the vehicle to self-calibrate based on its own operational characteristics, significantly reducing calibration time while maintaining precision.
Solution Approach 2:
The calibration process utilizes feedback from actual vehicle performance data. The system collects data on actual acceleration and deceleration rates, compares them with expected values, and automatically adjusts unit gains based on this feedback loop. This automated feedback mechanism enables precise calibration without manual intervention, resolving the contradiction between precision and time consumption.
3Ease of operation
If speed control commands are generated without considering specific driving conditions, then the ease of operation is improved, but the safety and smoothness of vehicle operation deteriorates
Solution Approach 1:
The speed control system dynamically adapts to specific driving conditions by automatically adjusting control parameters based on detected vehicle type and operational context. The system maintains ease of operation through automated adaptation, eliminating the need for manual adjustments while simultaneously improving safety by tailoring control characteristics to match actual driving conditions and vehicle specifics.
Data Source
AI summary
In one embodiment, speeds of an autonomous driving vehicle (ADV) are captured in response to a series of speed control commands issued at different points in time represented by a series of command cycles. For each of the command cycles, a first speed-changing rate is calculated based on a corresponding speed of the ADV and a second speed-changing rate is calculated based on the corresponding speed and a corresponding speed control command using a predetermined algorithm or function. A unit gain of speed control is determined using a cost function based on the first speed-changing rates and the second speed-changing rates, such that the cost representing a difference between the first speed-changing rates and the second speed-changing rates. The unit gain is then utilized to generate subsequent speed control commands for operating the ADV.