AV Tracking Subsystem for Dynamic Safety Buffer Adjustment
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Solution Overview
Problem
Autonomous Vehicles (AVs) face challenges in avoiding accidents caused by human-driven vehicles that do not comply with safety driving models, leading to potential chain-reaction collisions due to differences in response times and safe distance maintenance.
Innovation Solution
The AV system includes a tracking subsystem to detect and assess the compliance status of other vehicles, assigning safety risk grades and planning appropriate maneuvers to reduce collision risks by adjusting distance and response actions based on the compliance status of vehicles behind or lateral to it.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AV maintains a safe distance from the leading vehicle according to the safety driving model, then the AV's collision avoidance capability is improved, but the response time to unexpected hazards increases due to the additional safety buffer
Solution Approach 1:
The system performs preliminary assessment of following vehicles' compliance status before hazards occur. By pre-identifying non-compliant vehicles through tracking their distance maintenance patterns and response behaviors, the AV prepares contingency plans in advance, allowing faster reaction when hazards actually occur without compromising normal safe following distances.
Solution Approach 2:
The safety following distance is made dynamic rather than static. The system adjusts the safety buffer based on the compliance status of following vehicles - maintaining larger buffers when non-compliant vehicles are detected, and reducing buffers when following vehicles demonstrate compliant behavior. This dynamic adjustment optimizes both safety and response time under different conditions.
2Measurement precision
If the AV monitors and assesses the compliance status of all surrounding vehicles, then the detection accuracy of non-compliant vehicles is improved, but the system complexity and computational load increase
Solution Approach 1:
The system applies different monitoring intensities to different spatial zones and vehicle types. Following vehicles receive more intensive monitoring for compliance assessment compared to lateral or leading vehicles. The system also focuses computational resources on vehicles in critical positions (directly behind or very close laterally) rather than uniformly monitoring all surrounding vehicles, thereby reducing overall system complexity while maintaining high detection accuracy where needed.
Solution Approach 2:
The monitoring system is segmented into multiple independent modules: a tracking subsystem that identifies surrounding vehicles, a compliance assessment module that evaluates following behavior, and a risk evaluation module that determines overall safety. This segmentation allows each module to perform specialized functions with optimized computational requirements, reducing the complexity burden compared to a monolithic monitoring system.
3Reliability
If the AV takes aggressive evasive maneuvers to avoid collisions with non-compliant vehicles, then the collision avoidance effectiveness is improved, but the comfort and safety of AV passengers deteriorates due to sudden movements
Solution Approach 1:
The system prepares multiple contingency plans in advance for different levels of non-compliance risk. When non-compliant vehicles are detected, the AV pre-calculates gradual evasion trajectories and prepares phased response strategies. This allows the AV to execute smoother, more gradual maneuvers rather than sudden aggressive actions, maintaining collision avoidance effectiveness while reducing passenger discomfort.
Solution Approach 2:
The system maintains additional safety buffers and prepares cushioning maneuvers in advance when non-compliant vehicles are detected. Rather than making sudden sharp evasive movements, the AV uses pre-positioned safety margins and gradual course corrections to absorb potential collision risks, thereby protecting passengers from abrupt movements while still preventing collisions.
Data Source
AI summary
An Autonomous Vehicle (AV) system, including: a tracking subsystem configured to detect and track relative positioning of another vehicle that is behind or lateral to an AV configured to comply with a safety driving model, and to check a safety driving model compliance status of the other vehicle; and a risk reduction subsystem configured to plan, based on the safety driving model compliance status of the other vehicle, an AV action, wherein if the safety driving model compliance status of the other vehicle is unknown or is known to be non-compliant, the AV action is administration of a safety driving model compliance test to the other vehicle, or is a maneuver by the AV to reduce risk of collision with a leading vehicle positioned in front of the AV.