Adaptive Cruise Control Dynamic Gain Scheduling
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Solution Overview
Problem
Conventional cruise control systems fail to react quickly enough to changes in the lead vehicle's operation, leading to unsafe separation between vehicles, particularly at low speeds in traffic jams where frequent stops occur.
Innovation Solution
An adaptive cruise control system that calculates and controls the autonomous vehicle's desired velocity by considering both the relative distance and velocity to the lead vehicle, using a dynamic gain value to enable full stop functionality, mimicking human defensive driving behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional cruise control systems maintain constant speed or constant following distance, then the controlled vehicle can operate autonomously, but the system fails to react quickly enough to changes in the lead vehicle's operation, causing unsafe separation
Solution Approach 1:
The patent implements dynamic gain scheduling that adjusts the controller gain based on the relative velocity between the lead vehicle and controlled vehicle. When the controlled vehicle is slower than the lead vehicle, a higher gain is applied to increase responsiveness and reduce following distance more aggressively. This dynamic adjustment allows the system to react more quickly to lead vehicle changes while maintaining stability during normal operation.
Solution Approach 2:
The system changes the control parameter (gain value) based on the operating condition (velocity differential). By switching between different gain values depending on whether the controlled vehicle is slower or faster than the lead vehicle, the system adapts its response characteristics to maintain safety across varying driving conditions.
2Ease of operation
If the controlled vehicle maintains a constant following distance, then the system is simple to operate, but it cannot fully stop when the lead vehicle stops at low speeds, particularly in traffic jams
Solution Approach 1:
The patent implements dynamic gain scheduling that adjusts the controller gain based on the relative velocity between the lead vehicle and controlled vehicle. When the controlled vehicle is slower than the lead vehicle, a higher gain is applied to increase responsiveness and reduce following distance more aggressively. This dynamic adjustment allows the system to react more quickly to lead vehicle changes while maintaining stability during normal operation.
Solution Approach 2:
The system changes the control parameter (gain value) based on the operating condition (velocity differential). By switching between different gain values depending on whether the controlled vehicle is slower or faster than the lead vehicle, the system adapts its response characteristics to maintain safety across varying driving conditions.
Data Source
AI summary
A system and method for adaptive cruise control for low speed following are disclosed. A particular embodiment includes: receiving input object data from a subsystem of an autonomous vehicle, the input object data including distance data and velocity data relative to a lead vehicle; generating a weighted distance differential corresponding to a weighted difference between an actual distance between the autonomous vehicle and the lead vehicle and a desired distance between the autonomous vehicle and the lead vehicle; generating a weighted velocity differential corresponding to a weighted difference between a velocity of the autonomous vehicle and a velocity of the lead vehicle; combining the weighted distance differential and the weighted velocity differential with the velocity of the lead vehicle to produce a velocity command for the autonomous vehicle; adjusting the velocity command using a dynamic gain; and controlling the autonomous vehicle to conform to the adjusted velocity command.