Remote Support Queues for Autonomous Car Problem Situations
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Solution Overview
Problem
The monitoring and operation of large numbers of autonomous vehicles present challenges distinct from managing smaller numbers or non-autonomous vehicles, including inefficient interaction and reduced traffic flow efficiency, as existing methods do not effectively organize state monitoring and control among multiple vehicles.
Innovation Solution
A multi-tiered system with customized interfaces for fleet managers and vehicle managers, utilizing data analytics to allocate vehicles based on urgency and shared characteristics, allowing for efficient distribution of monitoring and operation management, and a communication system to transmit instruction data when vehicles operate outside defined parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human supervision monitors autonomous vehicles on a one to one basis, then vehicle safety and communication are improved, but monitoring efficiency deteriorates when the number of vehicles passes a certain threshold
Solution Approach 1:
The monitoring system is segmented into multiple levels: first level control stations monitor groups of vehicles, while a second level control station oversees multiple first level stations. This hierarchical segmentation allows efficient monitoring of large numbers of vehicles while maintaining safety through distributed control.
Solution Approach 2:
The system transitions from a flat one-to-one monitoring structure to a multi-dimensional hierarchical structure with multiple levels of control stations. This dimensional change enables scalable monitoring where the number of vehicles can increase without linearly increasing the number of human operators needed.
2Ease of operation
If existing methods monitor autonomous vehicles individually, then vehicle-specific control is maintained, but organization of state monitoring becomes inefficient for multiple vehicles
Solution Approach 1:
The system segments monitoring responsibilities by creating distinct levels: first level control stations handle individual vehicle states, while the second level control station manages the organization and coordination among multiple first level stations, reducing overall system complexity.
Solution Approach 2:
The second level control station acts as an intermediary that coordinates between multiple first level control stations and the central system. This intermediary layer organizes state monitoring efficiently by managing the distribution and aggregation of vehicle data across the network.
3Productivity
If autonomous vehicles interact in groups, then transportation network efficiency is improved, but unexpected disruptions occur when programming parameters are exceeded
Solution Approach 1:
The communication system provides continuous feedback between autonomous vehicles and control stations, allowing real-time detection when vehicles operate outside defined parameters. This feedback mechanism enables corrective action to prevent disruptions while maintaining the benefits of group interactions for network efficiency.
Data Source
AI summary
Methods and systems for providing remote support and negotiating problem situations of autonomous operation of vehicles based on signal states and vehicle information are described. A system comprises a memory and a processor configured to execute instructions stored in the memory to: assign vehicles to support queues based on state data, generate a map display including locations of the vehicles, and generate a state display including the support queues, vehicle manager indicators corresponding to the support queues and state indicators corresponding to the state data.