Modular Vehicle Sensor System with Interchangeable Sub-Modules
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Solution Overview
Problem
Current sensor systems for autonomous vehicles lack flexibility and adaptability in sensing capabilities, particularly in changing operational design domains, and are not easily scalable or modifiable to accommodate different vehicle types and advanced driving features.
Innovation Solution
A modular sensor system design featuring a central module and interchangeable sub-modules with standardized connections, allowing for easy upgrades and reconfiguration of sensing capabilities, including LIDAR, cameras, and radar sensors, connected through multiple networks for synchronization and data transmission, with redundancy for handling synchronization failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed sensor system design is used during manufacturing, then manufacturing precision is maintained, but adaptability to different vehicle types and operational design domains deteriorates
Solution Approach 1:
The sensor system is divided into a central module and multiple interchangeable sub-modules, each designed for specific sensing functions. This segmentation allows the system to be configured differently for various vehicle types and operational design domains by simply swapping sub-modules, thereby improving adaptability without significantly increasing overall system complexity.
Solution Approach 2:
The central module and sub-modules are designed with universal standardized interfaces and mounting mechanisms that can accommodate different sensor types (LIDAR, cameras, radar). This multi-functionality enables the same base platform to serve multiple vehicle types and operational requirements, enhancing adaptability while maintaining manageable complexity through standardized designs.
2Adaptability or versatility
If sensor systems are customized for each vehicle type, then adaptability improves, but manufacturing cost and complexity increase
Solution Approach 1:
By segmenting the sensor system into standardized central and sub-modules, the patent enables mass production of common components that can be reused across different vehicle types. This reduces manufacturing complexity and cost while still allowing customization through modular assembly, thereby improving ease of manufacture without sacrificing adaptability.
Solution Approach 2:
The modular architecture allows smaller specialized sub-modules to be nested within or attached to the central module platform. This nesting approach enables scalable manufacturing where the core platform can be produced in volume, and customization is achieved by adding or removing nested sub-modules, thus improving both adaptability and manufacturing scalability.
3Adaptability or versatility
If multiple sensor types are integrated, then sensing capabilities improve, but system synchronization and data integration complexity increase
Solution Approach 1:
The patent merges multiple different sensor types (LIDAR, cameras, radar) into a unified modular sensor system with standardized data interfaces and synchronization protocols. This combining approach allows diverse sensing capabilities to work together seamlessly, improving overall sensing coverage while managing integration complexity through standardized communication frameworks at the module level.
Solution Approach 2:
The central module acts as an intermediary that manages data collection, synchronization, and integration from multiple heterogeneous sub-modules. This intermediary structure handles the complexity of coordinating different sensor types and data formats, thereby improving sensing capabilities coverage while containing integration complexity within the centralized management layer.
4Measurement precision
If sensor systems are designed for high performance, then measurement precision improves, but system cost and complexity increase
Solution Approach 1:
The patent applies local quality by equipping specific sub-modules with high-precision sensors tailored to their designated functions, rather than uniformly high performance across all modules. This allows measurement precision to be improved where critically needed while maintaining simpler, more cost-effective designs in other areas, thereby balancing sensing accuracy with manageable system complexity.
Data Source
AI summary
A sensor system for a vehicle includes a central module and a plurality of sub modules mounted in a frame of the vehicle, the sub modules being independently removable. The sub modules include sensors configured to capture image data and distance data in a vicinity of the vehicle. The central module is connected to each of the plurality of sub modules through a first network including a switching hub. The sub modules are individually connected to an external processor through a second network. The central processor is configured to synchronize the sub modules based on absolute time information through the first network, and the sub modules are configured to output the captured image data and distance data appended with synchronized time information to the external processor by communicating through the second network.