Autonomous Vehicle Latency Modeling for Realistic Control Simulation
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Solution Overview
Problem
Conventional motion planning and control systems for autonomous vehicles do not accurately account for latency and dampening in control commands, leading to potential inaccuracies and risks in real-world driving scenarios, as they are applied uniformly across all types of vehicles without considering individual differences.
Innovation Solution
A method is developed to capture and analyze control command data from autonomous vehicles to determine a latency model, which simulates the time delay and dampening effects in a virtual environment, allowing for more realistic testing and simulation of driving scenarios, including interactions with pedestrians and other obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional motion planning and control systems are applied uniformly to all vehicles, then the system complexity is reduced and ease of operation is improved, but the measurement precision and reliability of the control system deteriorate due to ignoring individual vehicle characteristics and latency
Solution Approach 1:
The patent applies local quality by transitioning from uniform motion planning to vehicle-specific motion planning. Each vehicle type (e.g., sedan, SUV, truck) has its own customized motion planning parameters that account for its unique characteristics such as latency, dampening, curvature capabilities, and acceleration profiles. This allows the control system to be precisely tailored to each vehicle's actual performance characteristics while maintaining a standardized platform architecture.
Solution Approach 2:
The patent implements dynamics by making motion planning parameters adaptive rather than static. The system dynamically adjusts planning parameters based on real-time vehicle state, environmental conditions, and detected latency characteristics. This allows the control system to optimize performance continuously rather than relying on fixed uniform parameters across all vehicles.
2Productivity
If simulation does not incorporate latency and dampening effects, then the simulation speed and productivity are improved, but the reliability and accuracy of the simulation results deteriorate
Solution Approach 1:
The patent introduces an intermediary latency model that bridges the gap between idealized simulation and real-world vehicle behavior. This model incorporates detected latency and dampening characteristics as intermediate layers between the control commands and the simulated vehicle response, allowing realistic behavior simulation without requiring complex hardware-in-the-loop testing while maintaining simulation speed.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting simulation parameters based on detected vehicle characteristics. The system modifies latency, dampening, curvature, and acceleration parameters to match the actual vehicle being tested, transforming the simulation from a generic model to an accurate vehicle-specific representation while maintaining computational efficiency.
Data Source
AI summary
A simulation of an autonomous driving vehicle (ADV) includes capturing first data that includes a control command output by an autonomous vehicle controller of the ADV, and capturing second data that includes the control command being implemented at a control unit of the ADV. The control command, for example, a steering command, a braking command, or a throttle command, is implemented by the ADV to affect movement of the ADV. A latency model is determined based on comparing the first data with the second data, where the latency model defines time delay and/or amplitude difference between the first data and the second data. The latency model is applied in a virtual driving environment.