Roadside Checkpoint Selection for Vehicle Data Latency Validation
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Solution Overview
Problem
Autonomous and semi-autonomous vehicles face risks due to inadequate data transmission and reception capabilities, which can lead to inefficient communication with surrounding vehicles and infrastructure, potentially causing accidents if they cannot transmit and receive data in a timely and accurate manner.
Innovation Solution
A system comprising a vehicle data transmission diagnostics (VDTD) server that determines the need for a data latency risk evaluation, selects a roadside evaluation unit (REU) along a vehicle's route to serve as a data latency evaluation checkpoint, and transmits evaluation data packets to assess the vehicle's data transmission capabilities, ensuring timely and accurate data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles continuously transmit and receive data from multiple sources, then the vehicle's awareness of environmental features improves, but data transmission latency and processing delays increase
Solution Approach 1:
The system performs preliminary actions by pre-selecting roadside evaluation units along the vehicle's route and pre-establishing communication protocols before data transmission issues arise. The VDTD server proactively monitors data latency risks and prepares evaluation checkpoints in advance, allowing the vehicle to maintain continuous data flow without interruption or delay.
Solution Approach 2:
Roadside evaluation units serve as intermediaries between the autonomous vehicle and the centralized server. These REUs establish and maintain communication links, allowing data to be transmitted and evaluated locally without requiring continuous direct connection to the centralized server, thereby reducing transmission latency while maintaining reliability.
2Loss of information
If the vehicle acts as a data hub collecting data from multiple sources, then the comprehensiveness of environmental information improves, but the complexity of data processing and transmission increases
Solution Approach 1:
The data processing function is segmented between the autonomous vehicle, roadside evaluation units, and centralized server. The vehicle collects comprehensive environmental data from multiple sources, while roadside evaluation units handle local data validation and processing, and the centralized server performs higher-level analysis. This segmentation reduces the processing burden on any single component while maintaining information completeness.
Solution Approach 2:
The system implements partial processing at the vehicle level by using roadside evaluation units to validate and process only the most critical data streams locally. Not all data requires full processing at the vehicle - some can be handled by intermediaries or transmitted in aggregate form, reducing overall system complexity while preserving essential environmental information.
3Reliability
If network connectivity is required for centralized server communication, then vehicle control and monitoring improve, but vulnerability to network interruptions increases
Solution Approach 1:
The system prepares for potential network failures by establishing roadside evaluation units as backup communication channels before interruptions occur. These REUs can maintain vehicle monitoring and control functions even when the primary centralized server connection is lost, cushioning the system against network vulnerability while preserving control reliability.
4Speed
If data transmission speed is increased to reduce latency, then real-time processing capability improves, but data accuracy and validation may be compromised
Solution Approach 1:
Validation checkpoints are established in advance along the vehicle's route at roadside evaluation units. Data transmitted at high speeds passes through these pre-positioned validation points that can quickly verify data integrity without requiring slow, deliberate processing. The preliminary placement of multiple validation points allows rapid throughput while maintaining accuracy.
Solution Approach 2:
The system implements periodic validation at roadside evaluation units rather than continuous validation at every processing stage. Data transmission occurs continuously at high speed, with periodic checks at predetermined intervals and locations. This periodic action maintains data accuracy while allowing sustained high transmission speeds between validation points.
Data Source
AI summary
A system for validating automated vehicle data transmission capabilities of a vehicle is provided. The system includes a vehicle data transmission diagnostics (VDTD) server in communication with the vehicle and a plurality of roadside evaluation units. The VDTD server includes at least one processor and at least one memory device, and is programmed to: (i) determine that a data latency risk evaluation (DLRE) should be performed for the vehicle, (ii) transmit a DLRE request to the vehicle, (iii) receive, from the vehicle, a response to the transmitted DLRE request including trip data, the trip data including a selected route to be taken by the vehicle, (iv) interrogate the plurality of roadside evaluation units based upon the received trip data, and (v) select, based upon the interrogation, one of the plurality of roadside evaluation units to be a data latency evaluation checkpoint for the vehicle during the upcoming trip.