Autonomous Vehicle Procession Detection for Traffic Rule Exceptions
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Solution Overview
Problem
Autonomous vehicles face challenges in detecting and responding to processions, which involve groups of vehicles or persons moving together, as these situations invoke different traffic rules and require specific responses to ensure safe and effective autonomous driving.
Innovation Solution
A method using sensor data analysis to determine if objects are disobeying predetermined rules, identifying a procession based on thresholds of objects and time, and controlling the vehicle to respond appropriately, such as yielding, by integrating perception systems with map data and traffic rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous vehicle uses standard traffic rules for decision-making, then normal traffic operation is maintained, but the vehicle cannot properly respond to processions which require different traffic rules
Solution Approach 1:
The system segments the detection process into distinct stages: identifying individual rule-breaking objects, determining if they form a group, classifying the group type (procession vs. other), and applying appropriate traffic rules. This segmentation allows the system to handle complex procession detection through manageable sub-tasks without overwhelming computational complexity
Solution Approach 2:
The system introduces an intermediary classification layer between standard traffic rule processing and specific procession response. This intermediary layer analyzes group characteristics and determines whether objects form a procession, serving as a bridge that adapts standard traffic rules to procession-specific requirements without requiring complete rule rewriting
2Reliability
If the vehicle detects and responds to processions by yielding and making special maneuvers, then safety is improved, but traffic flow efficiency may be reduced due to aggressive maneuvers and stops
Solution Approach 1:
The system dynamically adjusts vehicle behavior based on real-time procession detection. Rather than static pre-programmed responses, the autonomous vehicle continuously monitors for procession conditions and adapts its traffic rule application accordingly, allowing flexible balance between safety yielding and traffic flow maintenance
Solution Approach 2:
The system changes operational parameters (such as speed, stopping distance, right-of-way decisions) based on procession detection results. When a procession is identified, the vehicle modifies its normal operating parameters to appropriate values for procession interaction, enabling safe response while minimizing disruption to overall traffic flow
3Measurement precision
If the vehicle requires multiple objects disobeying rules over a period of time to confirm a procession, then false positives are reduced, but detection response time increases
Solution Approach 1:
The system performs preliminary detection of rule-breaking objects and maintains a buffer of observed objects before confirming procession status. This preliminary action allows the system to quickly identify potential processions while requiring sufficient evidence (multiple objects over time) to confirm, balancing early detection with false positive prevention
Solution Approach 2:
The system uses feedback from continuous monitoring of road objects to refine procession detection. As objects are observed disobeying rules, the system feeds this information back into the detection algorithm, which adjusts its confidence level and response timing based on the accumulating evidence, optimizing both accuracy and response time
Data Source
AI summary
The technology relates to detecting and responding to processions. For instance, sensor data identifying two or more objects in an environment of a vehicle may be received. The two or more objects may be determined to be disobeying a predetermined rule in a same way. Based on the determination that the two or more objects are disobeying a predetermined rule, that the two or more objects are involved in a procession may be determined. The vehicle may then be controlled autonomously in order to respond to the procession based on the determination that the two or more objects are involved in a procession.