Autonomous Vehicle Cut-In Prediction and Speed Control
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Solution Overview
Problem
Current lane-changing technologies for autonomous vehicles are inadequate for level-4 autonomous driving, as they fail to proactively respond to situations where a rear overtaking vehicle intends to cut in, leading to passive deceleration and yielding, which can hinder traffic flow and discomfort drivers and passengers.
Innovation Solution
A vehicle running control system that predicts the intention of a rear vehicle to overtake by acquiring and analyzing traveling state information and road environment data, determining a candidate cut-in vehicle, and adjusting the autonomous vehicle's speed through deceleration, acceleration, or velocity maintenance based on the availability of a potential cut-in space and safety distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle performs passive deceleration and yielding when a rear vehicle attempts to cut in, then collision avoidance is ensured, but traffic flow is hindered and driver comfort is reduced
Solution Approach 1:
The system performs preliminary detection of rear vehicles' cut-in intentions by monitoring acceleration patterns and relative positions before the actual cut-in occurs. By identifying candidate cut-in vehicles based on acceleration exceeding threshold values and calculating potential cut-in spaces, the autonomous vehicle can proactively adjust its behavior to facilitate smooth merging while maintaining safety, rather than passively reacting after the cut-in attempt begins
Solution Approach 2:
The system dynamically adjusts the autonomous vehicle's acceleration and velocity based on real-time detection of rear vehicle intentions and calculated cut-in spaces. Instead of fixed passive yielding, the control processor continuously modifies driving parameters to balance collision avoidance with traffic flow maintenance, allowing flexible response to varying cut-in scenarios
2Reliability
If the autonomous vehicle maintains strict safety distances and passive yielding behavior, then collision risk is minimized, but driver and passenger comfort deteriorates
Solution Approach 1:
The system performs preliminary assessment of cut-in risks by detecting rear vehicle acceleration patterns and calculating potential cut-in spaces before they materialize. This allows the autonomous vehicle to maintain normal driving behavior when cut-in intentions are detected early, rather than immediately implementing conservative safety measures that would discomfort passengers
Solution Approach 2:
The system continuously monitors rear vehicle acceleration, relative position, and calculated cut-in spaces, using this feedback to dynamically adjust safety responses. When feedback indicates low-risk scenarios with sufficient cut-in space, the system maintains smoother driving behavior; when feedback indicates high-risk scenarios, it implements appropriate safety measures, creating a balanced approach to comfort and safety
Data Source
AI summary
A vehicle running control method includes: acquiring, at least one of a first traveling state information of an autonomous vehicle and a second traveling state information of adjacent vehicles traveling in a traveling lane or in a lane adjacent to the traveling lane through a sensor unit; determining, by a determination processor, a candidate cut-in vehicle that travels behind the autonomous vehicle among the adjacent vehicles based on the first and second traveling state information; searching, by a controller, for a potential cut-in space, which is determined based on the relative velocity of a preceding vehicle that is the closest to the autonomous vehicle among the adjacent vehicles and the distance between the preceding vehicle and the autonomous vehicle; and performing, by the controller, deceleration, acceleration, or velocity maintenance of the autonomous vehicle depending on whether the potential cut-in space is present.