Autonomous Vehicle Junction Queueing for Out-of-Turn Traffic
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems for controlling autonomous vehicles at junctions fail to accurately account for vehicles that arrive after the autonomous vehicle and proceed out of turn, or those that wait for the autonomous vehicle to proceed first, leading to inefficiencies and potential safety issues.
Innovation Solution
The system generates and continuously updates a queue of vehicles at the junction based on first-in-first-out (FIFO) principles, vehicle positions, and timeouts, using sensor data to assign scores that determine the order of vehicles and adjust as necessary, allowing the autonomous vehicle to proceed safely and efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems control autonomous vehicles at junctions using basic traffic rules, then the control logic is simple, but they fail to accurately account for vehicles that arrive after the autonomous vehicle and proceed out of turn, leading to safety issues
Solution Approach 1:
The system performs preliminary actions by continuously predicting trajectories of other vehicles before the autonomous vehicle reaches the junction and updates the queue order dynamically. This allows the system to anticipate potential safety issues from vehicles that may proceed out of turn, rather than reacting only after conflicts arise.
Solution Approach 2:
The system implements feedback by continuously monitoring the positions and trajectories of other vehicles, comparing predicted trajectories with actual movements, and updating the queue order and control decisions in real-time. This closed-loop feedback ensures safety even when other vehicles deviate from expected behavior.
2Measurement precision
If the system continuously updates the queue of vehicles at the junction, then the accuracy of trajectory prediction and collision avoidance improves, but the processing resources required increase
Solution Approach 1:
The system applies partial action by focusing computational resources on predicting trajectories only for vehicles that are relevant to the autonomous vehicle's path through the junction. Rather than exhaustively analyzing all possible vehicle interactions, it concentrates on the most critical predictions that directly impact safety and queue ordering.
Solution Approach 2:
The system uses dynamic updating of the queue order based on real-time trajectory predictions and actual vehicle movements. The prediction horizon and update frequency are adjusted dynamically based on the autonomous vehicle's proximity to the junction and the complexity of the traffic situation, optimizing processing resource usage.
Data Source
AI summary
Junction queueing for vehicles is described, in which vehicles may be queued based on arrival time at a junction, position relative to a stopping location at the junction, and/or an amount of time waiting for other vehicles to proceed through the junction (timeout). In some examples, the queue may be first generated based on the arrival times of any other vehicle relative to a particular vehicle generating the queue. The queue may be updated based on arrival times of other vehicles (e.g., after the particular vehicle), whether another vehicle has proceeded out-of-turn (e.g., based on a position at the junction), and/or a timeout for vehicles that wait for others to yield at the junction. In some examples, hysteresis and alterations of the score for safety reasons may alter queue order. The queue may be used to control the particular vehicle to traverse the junction.