Purpose-Built Vehicle Control for Module-Aware Autonomous Driving
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Solution Overview
Problem
Existing purpose-built vehicles (PBVs) lack the ability to adaptively adjust their driving methods and modes based on the type of work modules connected, leading to inefficiencies in operation and autonomous driving performance.
Innovation Solution
The PBV is equipped with a work module identification unit and a communication unit, allowing it to identify the connection type of attached work modules and select appropriate autonomous driving models based on the driving mode, including first and second connection types and driving modes such as individual and collaborative driving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the PBV uses a fixed autonomous driving model, then the system complexity is reduced, but the adaptability to different work modules and driving modes deteriorates
Solution Approach 1:
The system dynamically selects autonomous driving models based on the connected work module type and driving mode. The processor identifies the work module connection type and automatically switches between different autonomous driving models (first, second, or third model) to match the operational requirements, making the system adaptive without permanent complexity
Solution Approach 2:
A single autonomous driving system serves multiple functions by supporting different autonomous driving models for different work modules and driving modes. The system can handle individual driving, collaborative driving, and various work module configurations using a unified architecture that selects the appropriate model, avoiding the need for separate dedicated systems for each scenario
2Reliability
If the PBV uses a fixed autonomous driving model, then the device complexity is reduced, but the autonomous driving performance deteriorates
Solution Approach 1:
The system dynamically adapts its autonomous driving behavior by selecting from multiple pre-trained models based on real-time conditions. When a work module is connected, the processor identifies the connection type and switches to the appropriate autonomous driving model, ensuring optimal performance for each specific operational scenario without requiring manual reconfiguration
Solution Approach 2:
Multiple autonomous driving models are pre-trained and stored in the system memory before operation. Each model is specifically trained for different work module types and driving modes (individual or collaborative). During operation, the system simply selects the pre-prepared model that matches the current conditions, avoiding the complexity of real-time model training while maintaining high performance
3Adaptability or versatility
If the PBV identifies work module connection types, then the adaptability improves, but the device complexity increases
Solution Approach 1:
The work module identification unit automatically detects and identifies the type of work module connected to the PBV without requiring manual input or complex external systems. The processor analyzes signals from the identification unit and autonomously determines the connection type and selects the appropriate autonomous driving model, making the system self-configuring and reducing operational complexity
Data Source
AI summary
A purpose-built vehicle (PBV) includes: a work module identification unit to identify that at least one work module is loaded onto or coupled to the purpose-built vehicle, a communication unit to communicate data, and at least one processor connected to the work module identification unit and the communication unit. The at least one processor identifies that a work module is loaded onto or coupled to the purpose-built vehicle, identifies the connection type of the work module via the work module identification unit, and, based on the connection type of the work module and an autonomous driving model corresponding to the driving mode of the purpose-built vehicle, controls the purpose-built vehicle.