Teleoperator-Guided Vehicle Navigation in Flagger-Controlled Traffic
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating around flaggers directing traffic, as existing systems lack effective collaboration with human operators to adapt driving policies and ensure safety.
Innovation Solution
The vehicle uses sensors to detect flaggers, sends data to a teleoperator for verification, and receives guidance to adjust navigation policies, allowing collaborative driving to ensure safe passage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle uses sensors to identify objects and determine navigation actions independently, then the system maintains high automation and operational speed, but it lacks the ability to adapt to complex flagger-directed traffic scenarios safely
Solution Approach 1:
A teleoperator serves as an intermediary between the autonomous vehicle and the flagger, receiving video feeds and sensor data from the vehicle, interpreting flagger hand signals and gestures, and providing real-time guidance commands to the vehicle. This mediator enables safe human-in-the-loop collaboration without requiring full manual control, resolving the contradiction between automation and safety in complex social traffic scenarios.
2Reliability
If the vehicle stops at a threshold distance from the flagger to await instructions, then collision safety is improved, but navigation time and productivity decrease
Solution Approach 1:
The system implements continuous feedback loops where the vehicle monitors flagger gestures and hand signals in real-time, the teleoperator provides ongoing guidance based on interpreted signals, and the vehicle adjusts its navigation actions dynamically. This feedback mechanism allows the vehicle to maintain safe distances while reducing unnecessary stopping time by responding promptly to flagger instructions, balancing safety with navigation efficiency.
3Reliability
If the vehicle follows strict predefined policies for flagger interactions, then safety and predictability are improved, but adaptability to varying flagger behaviors and gestures decreases
Solution Approach 1:
The system transitions from static predefined policies to dynamic adaptive behavior through real-time teleoperator guidance. The teleoperator interprets various flagger gestures and hand signals dynamically, providing context-appropriate commands that adapt to different flagger behaviors, road conditions, and traffic scenarios. This dynamic approach maintains safety through human judgment while improving adaptability to varying flagger instructions.
Data Source
AI summary
This disclosure is directed to techniques for collaborative driving during flagger interactions. For instance, a vehicle navigating along a path may detect a flagger using sensor data. Based on detecting the flagger, the vehicle may stop at a location that is at least a threshold distance from the flagger and also send the sensor data to one or more computing devices associated with a teleoperator. The vehicle may then receive a guidance from the one or more computing devices, where the guidance is to proceed past the location. In some examples, the vehicle receives the guidance when the teleoperator activates and holds an input device. Based on receiving the guidance, the vehicle may begin to navigate passed the location and by the flagger. In some examples, the vehicle continues to navigate as long as the teleoperator activates the input device.