Passing Lane Collision Avoidance via Dynamic State Codes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle transportation networks lack effective methods to determine whether an expected path for a remote vehicle converges with that of a host vehicle, leading to potential collisions and inefficiencies in traversal.
Innovation Solution
A method involving a host vehicle receiving remote vehicle information via wireless communication, determining relative position and dynamic state codes, and identifying passing lane collision conditions to initiate appropriate control actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a host vehicle traverses a vehicle transportation network without determining convergence of expected paths with remote vehicles, then the traversal continues without interruption, but collision risk increases and safety is compromised
Solution Approach 1:
The system performs preliminary determination of expected paths and convergence assessment before actual collision risk materializes. By calculating relative position codes and dynamic state codes in advance, the system identifies potential collision conditions proactively, allowing preventive control actions to be taken before the vehicles actually converge on conflicting paths.
Solution Approach 2:
The patent introduces an intermediary communication system that exchanges vehicle information between host and remote vehicles. This intermediary mechanism enables the determination of relative positions and expected path convergence without requiring direct sensing between vehicles, facilitating safer traversal through information-mediated awareness of other vehicles' intentions and positions.
2Measurement precision
If the host vehicle determines relative position code and dynamic state code for every remote vehicle, then collision detection accuracy improves, but computational load and processing time increase
Solution Approach 1:
The system segments the determination process into distinct code types: relative position code and dynamic state code. This segmentation allows the system to process different aspects of vehicle interaction separately and efficiently, determining only the specific codes relevant to collision risk rather than analyzing all possible parameters for every remote vehicle simultaneously.
Solution Approach 2:
The patent transforms continuous vehicle position and state data into discrete code representations. By converting relative positions and dynamic states into coded formats, the system reduces computational complexity while maintaining sufficient precision for collision detection, enabling faster processing without significant loss of measurement accuracy.
3Reliability
If the host vehicle identifies expected passing lane collision condition and implements control action, then safety is improved, but traversal efficiency may be reduced due to lane changes or speed adjustments
Solution Approach 1:
The system dynamically adjusts control actions based on real-time assessment of collision risk and vehicle conditions. Rather than applying fixed restrictive measures, the control system adapts its responses to maintain safety while minimizing impact on traversal efficiency, allowing the host vehicle to optimize its path and speed based on the specific convergence conditions detected.
Solution Approach 2:
The patent implements a feedback mechanism where the results of control actions are continuously monitored and fed back into the collision detection system. This allows the system to learn from previous interventions and refine future control decisions, gradually improving traversal efficiency while maintaining safety standards through experience-based optimization of passing lane maneuvers.
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, 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 passing lane collision condition based on the relative position code, the remote vehicle dynamic state code, the host vehicle dynamic state code, and a current acceleration rate for the host vehicle, in response to identifying the expected passing lane collision condition, identifying a vehicle control action, and traversing a portion of the vehicle transportation network in accordance with the vehicle control action.