Autonomous Vehicle Teleoperator Contact for Yielding Delays
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Solution Overview
Problem
Autonomous vehicles face delays and traffic congestion when navigating to pickup or destination locations due to being impeded by other vehicles or traffic conditions, leading to inefficient route management and potential blockages.
Innovation Solution
The autonomous vehicle determines when to contact a teleoperator by assessing the duration of impediment and intervening conditions, using sensor data and map data to decide whether to alter navigation policies, such as yielding or changing interactions with other vehicles, based on thresholds and specific scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle contacts a teleoperator frequently to resolve impediments, then the reliability of navigation is improved, but the loss of time for communication and human intervention increases
Solution Approach 1:
The system performs preliminary actions by implementing a threshold-based detection mechanism that identifies when impediments exceed predefined time thresholds before contacting the teleoperator. This preliminary filtering allows the autonomous vehicle to handle routine impediments independently, reserving human intervention for more critical situations and thereby reducing unnecessary communication delays.
Solution Approach 2:
The autonomous vehicle performs self-service by autonomously detecting and resolving common navigation impediments using onboard sensors and decision-making algorithms. The vehicle can independently determine when to yield to other vehicles or wait for conditions to change, only seeking human assistance when self-resolution is not feasible, thus maintaining operational continuity without constant teleoperator involvement.
2Ease of operation
If the autonomous vehicle yields to other vehicles to maintain traffic flow, then the ease of operation is improved, but the productivity of the autonomous vehicle decreases
Solution Approach 1:
The system applies dynamics by implementing adaptive yielding behavior that adjusts based on real-time conditions. The autonomous vehicle dynamically evaluates factors such as impediment duration, traffic flow patterns, and delivery urgency to determine whether yielding is appropriate. This dynamic decision-making allows the vehicle to maintain polite traffic interactions while minimizing unnecessary delays to delivery schedules.
Solution Approach 2:
The system changes parameters by modifying navigation policies based on detected conditions. When an impediment is detected, the vehicle adjusts its behavior parameters (such as speed, yielding timing, and route selection) to balance traffic flow courtesy with delivery efficiency. These parameter adjustments are made contextually, allowing the vehicle to yield when appropriate but maintain productivity when the impediment is temporary or resolvable through alternative means.
3Adaptability or versatility
If the autonomous vehicle implements complex navigation policies to handle all impediments, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The navigation system is segmented into distinct functional modules: sensor data acquisition, impediment detection, threshold evaluation, policy selection, and execution. Each module handles a specific aspect of impediment management, allowing the system to maintain high adaptability through modular design while reducing overall complexity by avoiding monolithic decision-making architecture. This segmentation enables independent optimization of each component.
Solution Approach 2:
The teleoperator contact system serves as an intermediary layer between the autonomous vehicle's navigation system and human decision-making. Rather than implementing all complex decision logic within the vehicle, the system uses the teleoperator as a mediator for edge cases and unusual impediments, allowing the onboard system to maintain simpler, more reliable core navigation logic while still achieving high adaptability through human assistance when needed.
Data Source
AI summary
Techniques and methods for contacting a teleoperator. For instance, while navigating to a location, progress of an autonomous vehicle may stop. This may be caused by the autonomous vehicle yielding to another vehicle, such as at an intersection or when the other vehicle is located along a route of the autonomous vehicle. While yielding to the other vehicle, the autonomous vehicle may determine that the progress has stopped for a threshold amount of time. Additionally, in some circumstances, the autonomous vehicle may determine that the progress not been stopped due to traffic or a traffic light. Based at least in part on the determinations, the autonomous vehicle may send sensor data to the teleoperator, where the sensor data represents an environment for which the autonomous vehicle is located. Additionally, the autonomous vehicle may send an indication of the other vehicle to the teleoperator.