Blind Spot Collision Avoidance via Discrete Path Codewords
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Solution Overview
Problem
Existing vehicle transportation networks lack effective methods to determine whether the paths of host vehicles and remote vehicles are convergent, leading to potential blind spot collisions and inefficiencies in traversing the network.
Innovation Solution
A method involving a host vehicle receiving remote vehicle information via wireless communication, determining relative position and dynamic state codes, and identifying expected blind spot collision conditions to initiate appropriate vehicle control actions, such as deceleration rates and advisory or warning actions, to avoid collisions and optimize path traversal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a host vehicle traverses a vehicle transportation network without determining convergent paths with remote vehicles, then the vehicle can move freely without complex path analysis, but blind spot collisions may occur and safety is compromised
Solution Approach 1:
The patent segments the complex path determination problem into discrete codewords representing specific path configurations (e.g., straight, left turn, right turn, blind spot entry). By dividing continuous path possibilities into discrete categories, the system can efficiently compare and determine convergence without analyzing entire continuous trajectories, thus improving reliability while managing complexity.
Solution Approach 2:
The system performs preliminary determination of expected paths and convergent conditions before actual collision risk materializes. By pre-calculating potential convergent paths using codeword comparisons and determining blind spot collision conditions in advance, the system enables timely safety interventions while maintaining relatively simple real-time processing requirements.
2Measurement precision
If the host vehicle determines relative position codes and dynamic state codes for all remote vehicles, then convergent paths can be accurately identified, but computational load and processing time increase
Solution Approach 1:
The patent segments remote vehicle information into discrete codewords representing relative position and dynamic state. Instead of processing continuous coordinate data and velocity vectors, the system uses pre-defined codewords that categorize path configurations, significantly reducing computational complexity while maintaining sufficient precision for convergence detection.
Solution Approach 2:
The system transforms continuous physical parameters (position coordinates, velocity, acceleration) into discrete coded representations. This parameter transformation enables efficient comparison and convergence determination through codeword matching, reducing processing time while preserving the essential information needed for accurate path convergence detection.
3Reliability
If the host vehicle implements comprehensive vehicle control actions based on blind spot collision conditions, then collision avoidance is maximized, but vehicle maneuverability and speed may be reduced
Solution Approach 1:
The system implements control actions selectively based on detected blind spot collision conditions rather than continuously. When no convergent paths are detected, the host vehicle maintains normal operation without unnecessary interventions. Control actions are applied partially only when and where collision risk exists, maximizing safety while preserving traversal efficiency during normal conditions.
Solution Approach 2:
The system continuously monitors remote vehicle positions and paths, providing feedback on convergent conditions. Based on this feedback, control actions are dynamically adjusted - applying deceleration or routing changes only when convergence is detected, and maintaining normal operation when paths are non-convergent. This feedback mechanism ensures collision avoidance while minimizing impact on traversal efficiency.
Data Source
AI summary
A method and apparatus for use in traversing a vehicle transportation network may include a host vehicle receiving a remote vehicle message including remote vehicle information, identifying host vehicle information, determining a relative position code indicating whether an expected path for the remote vehicle and an expected path for the host vehicle are convergent based, determining a remote vehicle dynamic state code based on the remote vehicle information, determining a host vehicle dynamic state code based on the host vehicle information, identifying an expected blind spot collision condition based on the relative position code, the remote vehicle dynamic state code, and the host vehicle dynamic state code, in response to identifying the expected blind spot collision condition, identifying a vehicle control action based on the host vehicle dynamic state code, and traversing a portion of the vehicle transportation network in accordance with the vehicle control action.