Autonomous Vehicle Multi-Link Communication With Adaptive Video Compression
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Solution Overview
Problem
Autonomous vehicles face challenges in reliable communication, especially when traveling to unmapped destinations or in situations requiring human operator intervention, due to varying communication capacities and travel speeds, which can lead to unstable communication links and inefficient data transmission.
Innovation Solution
The implementation of multiple telecommunication devices and adaptive data compression techniques in autonomous vehicles, allowing them to dynamically determine communication capabilities and adjust compression rates based on travel speed and communication stability, ensuring reliable data transmission and simultaneous use of multiple communication channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple telecommunication devices are used for communication, then communication reliability is improved, but device complexity increases
Solution Approach 1:
The communication system is divided into multiple independent telecommunication devices (e.g., cellular modem, Wi-Fi device, satellite communicator) that can operate separately or together. Each device handles specific communication tasks, and the system selectively activates appropriate devices based on availability and requirements, improving reliability without requiring all devices to be simultaneously active.
Solution Approach 2:
The system dynamically changes communication parameters such as data transmission rates, compression levels, and protocol selections based on current communication conditions and device capabilities. This allows the system to optimize performance across multiple devices while managing complexity through adaptive parameter adjustment rather than fixed complex configurations.
2Productivity
If adaptive data compression is applied, then data transmission efficiency is improved, but processing complexity increases
Solution Approach 1:
The data compression level is dynamically adjusted based on real-time communication conditions, travel speed, and available bandwidth. When communication capacity is high or travel speed is low, compression is reduced to maintain quality. When communication capacity is limited or travel speed is high, compression is increased to ensure timely transmission, optimizing efficiency without requiring maximum processing complexity at all times.
Solution Approach 2:
The system changes compression parameters (compression ratio, algorithm selection, quality settings) based on measured communication capability and travel speed. This adaptive approach allows the system to achieve high transmission efficiency when needed while reducing processing overhead when conditions permit, balancing productivity gains against processing complexity.
3Reliability
If communication capability is increased to maintain stable links at high travel speeds, then communication reliability is improved, but energy consumption increases
Solution Approach 1:
The system applies partial communication action by selectively transmitting only essential data during high-speed travel rather than continuously transmitting all sensor data at maximum quality. Critical safety and navigation data are transmitted with higher priority and stability, while less critical data is transmitted with lower bandwidth or deferred, maintaining communication stability without maximizing energy consumption.
Solution Approach 2:
Communication parameters such as transmission power, data rate, and protocol selection are dynamically changed based on travel speed and signal conditions. At high speeds, the system adjusts parameters to maintain link stability while avoiding excessive power consumption by selecting appropriate compression levels and transmission frequencies that balance reliability with energy usage.
4Speed
If data compression rate is increased to compensate for limited communication capacity, then data transmission speed is improved, but data quality deteriorates
Solution Approach 1:
Different data streams receive different compression rates based on their importance and requirements. Critical data such as safety sensor information, navigation data, and operator communication streams are transmitted with lower compression (higher quality), while less critical data such as environmental monitoring or historical logs use higher compression rates, optimizing transmission speed while preserving essential data quality.
Solution Approach 2:
The compression rate is dynamically adjusted based on available communication capacity and travel conditions. When communication capacity increases or travel speed decreases, compression is reduced to improve data quality. When communication capacity is limited or travel speed is high, compression is increased to maintain transmission speed, creating a dynamic balance between speed and quality based on real-time conditions.
Data Source
AI summary
An autonomous land vehicle in accordance with aspects of the present disclosure includes a land vehicle conveyance system, at least two telecommunication devices, an imaging device configured to capture image data of a surrounding environment, a video encoder configured to encode the image data, one or more processors, and at least one memory storing instructions. The telecommunication devices can perform wireless communication independently of each other and can simultaneously perform wireless communication. The instructions, when executed by the processor(s), cause the vehicle to travel using the conveyance system, determine a communication capability of the telecommunication devices while the conveyance system performs travel, determine a compression rate for the video encoder based on the communication capability, encode the image data using the video encoder based on the compression rate to generate encoded data, and communicate the encoded data using at least one telecommunication device based on the communication capability.