Autonomous Vehicle Route Control With Beacon-Based Redirection
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Solution Overview
Problem
Existing autonomous transportation networks (ATN) rely on central control management, leading to communication bottlenecks, scalability issues, and challenges in handling multiple vehicles and prioritizing access for priority vehicles.
Innovation Solution
An autonomous transportation network that allows autonomous vehicles to calculate and transmit their routes independently, with a control management center capable of simulating traffic demand and independently calculating routes, reducing the need for constant communication and enabling resilient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If central control management is used to control each autonomous vehicle, then vehicles can be managed and routed, but communication bottlenecks and network overload occur
Solution Approach 1:
The patent divides the centralized control system into distributed autonomous units. Each vehicle is equipped with an onboard controller that independently calculates routes and makes decisions, segmenting the control function from the central management system. This reduces communication overhead while maintaining operational control.
Solution Approach 2:
Each autonomous vehicle performs self-routing and self-control through onboard controllers that independently calculate optimal paths and execute maneuvers without continuous central intervention. The vehicles serve themselves by making autonomous decisions based on local conditions and mission parameters.
2Reliability
If continuous communication between vehicles and control center is maintained, then real-time monitoring is achieved, but network bandwidth requirements increase
Solution Approach 1:
Instead of continuous communication, the system uses periodic status reports and event-triggered updates. Vehicles communicate with the control center at intervals or when significant events occur (route changes, anomalies), reducing data transmission volume while maintaining adequate monitoring capability.
Solution Approach 2:
The patent extracts critical control functions from the central system and places them onboard each vehicle. This eliminates the need for continuous data exchange for routine operations, keeping communication to essential updates and commands only.
3Productivity
If centralized route calculation is used, then coordinated traffic management is achieved, but processing load on control center increases
Solution Approach 1:
The route calculation function is segmented from the central control and distributed to individual vehicle onboard controllers. Each vehicle independently calculates its own route based on mission parameters and local conditions, eliminating the computational burden from the control center while maintaining coordinated traffic management through standardized protocols.
Solution Approach 2:
Each vehicle's onboard controller performs self-routing by independently calculating optimal paths based on stored maps, mission parameters, and local traffic conditions. This self-service approach to route calculation distributes computational load across all vehicles rather than concentrating it at the control center.
4Adaptability or versatility
If more autonomous vehicles are added to the network, then service coverage increases, but communication infrastructure complexity increases
Solution Approach 1:
Each vehicle independently manages its own communication needs through onboard controllers that autonomously establish connections, report status, and receive commands. This self-service communication approach allows the network to scale without proportionally increasing infrastructure complexity, as each vehicle manages its own communication footprint.
Data Source
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Figure 3A~3B
AI summary
An autonomous transportation network (10) and method (100a, 100b, 100c) of operation is disclosed. The autonomous transportation network (10) comprises a plurality of autonomous vehicles (20) with an onboard processor (27) and vehicle memory (28) for locally calculating (240, 310) a route (50) between an origin (30) and a destination (40) and a vehicle antenna (25) for transmitting the calculated route (50). A control management center (100) comprises a control management processor (120) and a central memory (140) and independently calculates (250, 520) the routes (50) of the plurality of autonomous vehicles (20). A plurality of beacons (17) is connected to the control management center (100) and receives redirection information from the control management center (100) for transmission to one or more of the plurality of autonomous vehicles (20).