Connected Vehicle Event Data Exchange for Automated Fault Response
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Solution Overview
Problem
Current vehicle and infrastructure systems are inefficient in identifying events such as accidents and near misses, determining at-fault parties, and initiating responses, often prolonging the recovery process and burdening involved vehicles.
Innovation Solution
A connected vehicle control and response system that uses sensors and communication protocols to detect events, determine fault, and automatically initiate responses by aggregating data from involved vehicles and infrastructure, employing machine learning algorithms to predict and mitigate future events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual event identification and fault determination processes are used, then system complexity is reduced, but response time increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing sensor data from vehicles and infrastructure before events occur. Event detection algorithms are pre-configured to automatically identify when specific conditions are met, eliminating the need for manual event identification and reducing response time significantly.
Solution Approach 2:
The system implements self-service through automated fault determination algorithms that analyze collected data and independently identify at-fault parties without human intervention. The automated response initiation capability allows the system to self-manage the entire incident processing workflow, reducing both recovery time and operational complexity.
2Productivity
If automated response initiation is implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: data collection from sensors, event detection algorithms, fault determination logic, and response initiation mechanisms. This modular architecture improves productivity by enabling parallel processing of incident management tasks while managing complexity through clear separation of concerns.
Solution Approach 2:
A centralized server acts as an intermediary between vehicles, infrastructure elements, and response systems. This mediator coordinates data flow and automates the incident management process, enhancing productivity by streamlining communication and decision-making while abstracting the complexity from individual components.
3Measurement precision
If comprehensive data collection from multiple vehicles and infrastructure is performed, then measurement precision improves, but loss of information increases due to data management challenges
Solution Approach 1:
The system employs a universal data collection framework that interfaces with multiple vehicle types and infrastructure elements through standardized protocols. This multi-functional approach enables precise event detection by aggregating data from diverse sources while maintaining data management efficiency through a unified processing architecture.
Solution Approach 2:
Manual data collection and analysis processes are replaced with automated electronic sensor networks and digital data processing systems. This substitution improves measurement precision through continuous automated monitoring while preventing information loss by eliminating human error in data transcription and management.
Data Source
AI summary
Event-based connected vehicle control and response systems, methods, and apparatus are disclosed. An example method comprises identifying the occurrence of an event, storing first data corresponding to apparatus operation for a first threshold amount of time prior to the event, during the occurrence of the event, and for a second threshold amount of time after the event, determining whether a responsive object is involved in or near the event, in response to determining that the responsive object is involved in or near the event, transmitting the first data to the responsive object, and receiving, from the responsive object, second data, analyzing the first data and the second data to determine a party at-fault for the event, aggregating the first data and second data into an event report, and causing, automatically, a response to be initiated through an entity associated with the party at-fault.