Cloud Server Onboard Terminal Traffic Safety Pre-warning
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Solution Overview
Problem
Current technologies lack effective intelligent traffic safety pre-warning systems for vehicles on highways, relying heavily on driver experience and sensory limits, which are inadequate in low visibility conditions like rain and fog, leading to frequent accidents.
Innovation Solution
An intelligent traffic safety pre-warning method involving onboard-terminals that establish communication with a cloud server to process and upload data, calculate accident probabilities, and provide real-time warnings to drivers through human-computer interaction, while also broadcasting safety information to surrounding vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver relies on sensory observation and experience for driving safety, then driving control can be maintained, but safety is insufficient in low visibility conditions and frequent accidents occur
Solution Approach 1:
The patent introduces cloud servers and onboard terminals as intermediary systems between drivers and the driving environment. These systems collect, process, and analyze traffic data, road conditions, and vehicle information to provide safety warnings and recommendations, compensating for human sensory limitations in low visibility conditions
Solution Approach 2:
The system performs preliminary actions by continuously monitoring and analyzing potential hazards before they materialize into accidents. The cloud server processes data to predict risky situations and provides advance warnings to drivers, enabling proactive safety measures rather than reactive responses
2Reliability
If intelligent safety monitoring and danger pre-warning systems are implemented, then driving safety and predictability improve, but system complexity increases
Solution Approach 1:
The cloud server acts as a centralized intermediary that handles complex data processing, analysis, and prediction algorithms. This externalizes the computational complexity from individual vehicles to a shared infrastructure, reducing on-board system complexity while maintaining high safety performance
Solution Approach 2:
The cloud server provides multiple functions including data collection, analysis, prediction, warning generation, and traffic organization within a single unified system. This multi-functionality consolidates what would otherwise require multiple separate systems, managing complexity through integration
3Measurement precision
If real-time data processing and accident probability calculation are performed, then danger prediction accuracy improves, but computational resources and time consumption increase
Solution Approach 1:
The system continuously collects and pre-processes data in real-time, maintaining updated profiles of road conditions, traffic patterns, and vehicle states. This preliminary processing ensures that when hazard assessment is needed, the system can quickly query pre-processed data rather than starting from raw data collection
Solution Approach 2:
The system implements feedback loops where accident probability calculations and safety warnings are continuously updated based on new data. The cloud server processes incoming data streams, updates risk assessments, and provides real-time feedback to drivers, maintaining high precision through continuous refinement rather than periodic batch processing
Data Source
AI summary
The present invention discloses an intelligent traffic safety pre-warning method, a cloud server, onboard-terminals and a system. The method comprises: a step (101): the onboard-terminal establishes a communication connection with the cloud server; a step (102): the onboard-terminal acquires data, and uploads data calculated based on the acquired data to the cloud server; a step (103): the onboard-terminal receives feedbacks from the cloud server, the feedback comprising the probability that the current vehicle has an accident within a set range of the current road segment; and a step (104): the onboard-terminal receives the probability that the current vehicle has an accident within the set range of the current road segment, and then transmits the feedback to the driver by human-computer interaction. The method, the cloud server, the onboard-terminals and the system fill in the gaps in traffic safety, danger pre-warning, and low visibility driving safety guarantee in rain, fog and the like in the traffic field, and ensure that the driving behavior is safer.