Autonomous Vehicle Stopline Clearance at Multi-Way Stops
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating multi-way stop intersections due to uncertainties in the intentions and movements of other vehicles, which can lead to unsafe merging and right-of-way violations.
Innovation Solution
The system detects the autonomous vehicle's position at a primary stopline, determines its planned travel path, and uses clearance criteria to decide whether to proceed, while also considering the movements and expected paths of other vehicles to ensure safe merging and adherence to traffic rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous vehicle proceeds past the stopline when another vehicle is slowly crawling toward the intersection, then the autonomous vehicle can maintain higher productivity and reduce waiting time, but it risks collision with the crawling vehicle
Solution Approach 1:
The system performs preliminary detection of other vehicles' movements and intentions before making the go/no-go decision. By detecting slow crawling movements in advance and predicting potential collision risks, the system can proactively adjust the autonomous vehicle's action to avoid collisions while still maximizing throughput when safe.
2Reliability
If the autonomous vehicle waits for complete clearance before proceeding, then collision avoidance is ensured, but productivity and intersection throughput decrease
Solution Approach 1:
Instead of waiting for complete clearance of the intersection, the system performs partial clearance detection - determining whether the path ahead is sufficiently clear to proceed safely. This partial action approach allows the vehicle to proceed when another vehicle is slowly crawling (rather than waiting for complete intersection clearance), thereby maintaining higher productivity while still ensuring safety through risk assessment.
3Productivity
If the autonomous vehicle misinterprets another vehicle's slow movement as intent to merge, then unsafe merging may occur, but if it correctly identifies non-merging intent, safe proceeding is enabled
Solution Approach 1:
The system continuously monitors and detects the movement patterns of other vehicles, using this feedback to update its understanding of their intentions. By detecting slow crawling movements and analyzing their persistence and context, the system can distinguish between vehicles intending to merge versus those simply moving slowly, enabling correct decision-making that balances productivity and safety.
Data Source
AI summary
The subject matter described in this specification is directed to a system and techniques for operating an autonomous vehicle (AV) at a multi-way stop intersection. After detecting the AV is at a primary stopline of the multi-way stop intersection, a planned travel path though the multi-way stop intersection is obtained. If the planned travel path of the AV through the multi-way stop intersection satisfies a set of one or more clearance criteria, the AV proceeds past the primary stopline. The clearance criteria include a criterion that is satisfied in response to detecting the AV is clear to safely merge into a travel lane corresponding to the planned travel path.