Dual-Cockpit HIL Testbed for Shared Autonomous Vehicle Control
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Solution Overview
Problem
Existing methods for autonomous vehicle testing, such as hardware-in-the-loop, software-in-the-loop, and simulator-in-the-loop, fail to effectively simulate real-world scenarios involving a driver under test, a safety trained driver, and an autonomous system operating simultaneously, and do not adequately address the need for adaptive testing of various vehicle components from different suppliers.
Innovation Solution
A dual-cockpit testbench system that allows a safety trained driver to monitor and correct the driver under test and the autonomous system, incorporating both virtual and physical components, enabling comprehensive testing across all stages of vehicle development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual environments are used for autonomous vehicle testing, then testing coverage can be expanded, but real-world behavior and edge cases may be missed
Solution Approach 1:
The patent merges virtual environment testing with hardware-in-the-loop testing by integrating a virtual vehicle model with actual vehicle hardware components. This combination allows the system to benefit from both the expanded testing coverage of virtual environments and the authentic real-world behavior validation of physical hardware, resolving the contradiction between versatility and reliability.
Solution Approach 2:
The hardware-in-the-loop testbed acts as an intermediary between virtual simulation and real-world deployment. It includes a virtual vehicle that receives control inputs and generates outputs that are fed back to physical vehicle components, creating a bridge that validates real-world behavior while maintaining expanded testing capabilities.
2Reliability
If hardware-in-the-loop testing is used, then real-world behavior can be validated, but the system complexity increases
Solution Approach 1:
The testing system is segmented into distinct functional modules including a virtual vehicle model, control input interfaces, output feedback mechanisms, and a state management system. Each module handles specific aspects of the testing process independently, which reduces overall system complexity while maintaining comprehensive real-world behavior validation capabilities.
Solution Approach 2:
The hardware-in-the-loop testbed is designed with universal interfaces that can accommodate different vehicle components and configurations. The system can test various autonomous driving functions using the same infrastructure, reducing complexity by avoiding the need for separate dedicated testing systems for each function.
3Reliability
If dual cockpit configuration is implemented, then safety monitoring is improved, but device complexity increases
Solution Approach 1:
The dual cockpit configuration uses a second driver's station as a copy of the primary driver interface, allowing real-time monitoring and correction of driver inputs. This copying approach improves safety monitoring by providing redundant observation and control capabilities without requiring entirely new complex systems, as the second cockpit replicates essential functions.
Data Source
AI summary
Systems and methods described herein relate to using multimodal foundation models. In one embodiment, a method includes providing a testbench capable of receiving a first input set from a first device set operable by a first driver, a second input set from a second device set operable by a second driver, and a third input set from an autonomous driving component, generating states of operations where each state of operation determines how the first, second, and third input set are able to control a vehicle, determining a current state of operation for the vehicle, and configuring vehicle control by the first input set, the second input set, and third input set based on the current state of operation.