Autonomous Vehicle Slowdown Control for Critical Headway
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Solution Overview
Problem
Existing techniques for autonomous vehicles (AVs) fail to effectively perform slowdown manoeuvres when the headway between the AV and an obstacle becomes too small, leading to computational limitations and inability to generate control signals.
Innovation Solution
A method and system for AVs that detect obstacles and compare the headway with a threshold value, implementing either a constraint optimization-based slowdown manoeuvre or an adaptive cruise control mode to ensure safe and comfortable deceleration, using kinematic functions with defined jerk and acceleration limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If constraint optimization process is used for slowdown manoeuvre, then comfort constraints are satisfied, but computational limitations occur when headway is too small
Solution Approach 1:
The system dynamically switches between two control modes (constraint optimization and adaptive cruise control) based on the current headway distance. When headway is sufficient, constraint optimization is used for comfort; when headway becomes too small, the system transitions to ACC mode to ensure computational reliability and safety.
Solution Approach 2:
The invention changes the control parameter regime based on headway threshold comparison. By monitoring the headway parameter and comparing it with a threshold, the system adjusts which control algorithm is active, thereby adapting to different operational conditions and resolving the contradiction between comfort and computational reliability.
2Reliability
If headway threshold is used to select control mode, then safety is improved, but system complexity increases
Solution Approach 1:
The control space is segmented into two distinct regions based on headway threshold: a safe region where constraint optimization is applied and a critical region where adaptive cruise control is applied. This segmentation allows the system to handle different safety requirements with appropriate control strategies without requiring a completely new complex system.
Solution Approach 2:
The headway threshold comparison acts as an intermediary mechanism that mediates between the two control modes. Rather than directly managing the complexity of switching between complex control algorithms, the simple threshold comparison serves as an intermediary decision layer that selects which control mode to activate, thereby managing system complexity while maintaining safety.
Data Source
AI summary
A computer-implemented method of determining control signals for controlling an autonomous vehicle to implement a slowdown manoeuvre, comprising: detecting an obstacle at a distance ahead of the autonomous vehicle; comparing the distance with a threshold value and implementing a slowdown manoeuvre in dependence on the comparison, the slowdown manoeuvre selected from: a first slowdown manoeuvre carried out by a kinematic function, which is a time derivative of acceleration, in which a constraint optimisation has been applied to optimise a cost function of the slowdown manoeuvre subject to a set of hard constraints that require a final acceleration, speed and position to satisfy respective acceleration, speed and position targets, given an initial speed and acceleration of the vehicle, and impose a jerk magnitude upper limit; and a second slowdown manoeuvre implemented in an adaptive cruise control mode which aims to reach a target headway between the autonomous vehicle and the obstacle.