Teleoperation Map Updates for Autonomous Vehicle Trajectory Changes
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating through unpredictable events or road conditions, such as construction zones or school zones, where direct human intervention is necessary but current systems lack efficient methods for teleoperation to modify vehicle trajectories in real-time.
Innovation Solution
A method and system for controlling autonomous vehicles through teleoperation, where teleoperation inputs modify existing trajectories based on real-time sensor data and environmental conditions, generating updated map data to guide the vehicle around obstacles or adjust speed limits, without direct control of steering or braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If teleoperation input is received to modify vehicle trajectory in real-time, then safety and adaptability are improved, but system complexity and communication requirements increase
Solution Approach 1:
The patent introduces map data as an intermediary between the teleoperation system and the autonomous vehicle. Instead of directly controlling vehicle operations, the teleoperation system modifies map data which then guides the vehicle's trajectory automatically. This mediator approach improves safety through human oversight while reducing the complexity of direct real-time control systems.
Solution Approach 2:
The system performs preliminary actions by pre-processing teleoperation inputs into updated map data before the vehicle encounters the situation. The map data is prepared in advance with modified trajectories, speed limits, or route changes based on teleoperator decisions, allowing the vehicle to execute pre-planned safe paths without requiring complex real-time control interventions.
2Adaptability or versatility
If teleoperation input modifies existing trajectory based on real-time information, then adaptability to unexpected events is improved, but communication bandwidth and processing requirements increase
Solution Approach 1:
The patent extracts only the essential trajectory modification information from teleoperation inputs and encodes it into compact map data updates. Instead of transmitting complete real-time control signals or detailed sensor data, the system extracts and transmits only the necessary path modification parameters, reducing communication bandwidth requirements while maintaining adaptability.
Solution Approach 2:
The system changes parameters by representing trajectory modifications as updates to map data parameters (such as path coordinates, speed limits, or route markers) rather than transmitting continuous control signals. This parameter transformation reduces the amount of information that needs to be communicated while preserving the adaptability to handle unexpected events.
3Measurement precision
If updated map data is generated and incorporated with sensor data to determine new trajectory, then navigation accuracy is improved, but computational load increases
Solution Approach 1:
The system performs preliminary computation by pre-integrating teleoperation inputs into updated map data before the vehicle needs to make navigation decisions. The computationally intensive task of combining trajectory modifications with environmental context is done in advance, allowing the vehicle to execute pre-computed paths with high accuracy while reducing on-vehicle computational load during critical navigation phases.
Data Source
AI summary
This disclosure provides systems and methods for controlling a vehicle by teleoperations based on map creation. The method may include: receiving, at the autonomous vehicle, a teleoperation input from a teleoperation system through a communication link, wherein the teleoperation input comprises a modification to at least a portion of an existing trajectory of the autonomous vehicle; and using a processor: generating an updated map data based on the received teleoperation input from the teleoperation system, wherein the updated map data comprises the modification to the least the portion of the existing trajectory; determining a modified trajectory or a new trajectory for the autonomous vehicle based at least in part on the updated map data and by incorporating sensor data from one or more sensors on the autonomous vehicle, wherein the sensor data comprises environmental data associated with a physical environment of the autonomous vehicle; and controlling the autonomous vehicle according to the modified trajectory or the new trajectory.