Cloud Coordinated Vehicle Data Collection Subsystem
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Solution Overview
Problem
Current vehicle data collection systems lack flexibility and upgradability, requiring physical connections and being costly to manufacture and operate, while also failing to efficiently manage data processing tasks across onboard and remote systems.
Innovation Solution
A cloud-coordinated vehicle data collection system with onboard and remote subsystems, utilizing control modules with processors, memory, and I/O ports, that include intelligent data transmission, processing, and task allocation modules to select communication channels, process data, and adjust resource allocation dynamically, minimizing costs and honoring task deadlines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical network connections are used for data collection, then system reliability is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent implements a universal communication interface that supports multiple communication protocols (CAN, LIN, Ethernet, WiFi, Bluetooth) within a single data collection system. This allows the system to adapt to different vehicle platforms and communication requirements without requiring separate physical connection systems for each protocol, thereby reducing overall system complexity while maintaining reliable data transmission through protocol-appropriate connection methods.
Solution Approach 2:
The patent introduces a gateway device as an intermediary between various vehicle subsystems and the central data collection system. This gateway handles protocol conversion, data filtering, and preliminary processing, reducing the complexity of direct physical connections between all components and enabling flexible communication paths that maintain reliability without requiring complex point-to-point physical wiring for every connection.
2Productivity
If onboard data processing is increased, then data processing speed is improved, but energy consumption and computational resource requirements increase
Solution Approach 1:
The patent segments data processing tasks into three categories: critical safety data processed immediately onboard, important operational data processed in near-real-time onboard, and historical/analytics data processed remotely in the cloud. This segmentation allows the system to maintain high processing speed for critical functions while minimizing onboard energy consumption by offloading less time-sensitive processing to remote servers with unlimited computational resources.
Solution Approach 2:
The patent implements selective data processing where only essential vehicle parameters are processed onboard at high speed, while non-critical data is sampled at lower frequencies or processed asynchronously. This partial processing approach maintains adequate productivity for safety-critical functions while significantly reducing onboard energy consumption and computational resource requirements.
3Adaptability or versatility
If multiple communication systems are supported, then adaptability is improved, but system complexity increases
Solution Approach 1:
The patent designs a unified communication architecture that integrates multiple communication protocols (CAN, LIN, Ethernet, WiFi, Bluetooth) through a single multi-functional gateway device. This universal interface approach allows the system to support various vehicle platforms and communication requirements without requiring separate dedicated hardware for each protocol, thereby achieving high adaptability while controlling system complexity through consolidation.
Solution Approach 2:
The patent extracts communication protocol handling from the core data collection logic and places it in dedicated protocol adaptation layers within the gateway. This extraction allows each communication protocol to be implemented as an independent module, making the system highly adaptable to different protocols while managing complexity through modular design where each protocol handler operates independently.
4Reliability
If data transmission frequency is increased, then data freshness is improved, but communication bandwidth consumption and cost increase
Solution Approach 1:
The patent implements differential data transmission where critical safety-related parameters (braking, steering, collision detection) are transmitted at high frequency to ensure data freshness, while non-critical parameters (climate control, infotainment) are transmitted at lower frequencies. This partial high-frequency approach maintains data freshness for essential functions while minimizing communication bandwidth consumption and energy costs for overall system data transmission.
Solution Approach 2:
The patent applies different transmission frequency qualities to different data streams based on their importance. Critical data receives high-frequency transmission with low latency requirements, while non-critical data uses lower-frequency transmission. This local quality differentiation ensures data freshness where needed while reducing communication energy consumption for the overall system by avoiding uniform high-frequency transmission across all data types.
Data Source
AI summary
A system for cloud coordinated vehicle data collection includes an onboard vehicle data management subsystem and a remotely-located back-office subsystem. Each subsystem includes one or more control modules having a processor, a memory, and input/output (I/O) ports. The control modules execute program code portions stored in memory. A first program code portion collects vehicle data from onboard vehicle data sources. A second program code portion determines which of several distinct communications systems will be used to transmit the vehicle data to the remotely-located back-office subsystem. A third program code portion causes the remotely-located back-office subsystem to allocate data processing tasks to specific computing resources. A fourth program code portion causes the onboard vehicle data management subsystem and the remotely-located back-office subsystem to continuously adjust data processing task allocation between onboard vehicle control modules and remotely located back-office control modules by minimizing costs and honoring task deadlines and resource consumption constraints.