IoV Driving Behavior Correction via Real-Time Vehicle Data
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Solution Overview
Problem
Current methods for monitoring and correcting illegal driving behaviors are limited by static cameras, which fail to provide real-time comprehensive monitoring and often miss detecting dangerous driving behaviors, leading to potential accidents and unaddressed consequences.
Innovation Solution
A driving behavior correction method and system utilizing the Internet of Vehicles technology, which acquires real-time vehicle and surrounding vehicle information to determine dangerous or illegal driving behaviors, issuing prompts to drivers and uploading illegal behaviors to the cloud for recording, thereby enabling comprehensive and timely intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static camera at a fixed position is used to monitor driving behavior, then the monitoring means is simple, but the monitored road section is limited and real-time monitoring cannot be achieved
Solution Approach 1:
The patent transitions from static camera monitoring to dynamic vehicle-mounted monitoring systems that move with vehicles, enabling real-time tracking of driving behavior across the entire road network rather than fixed locations. The system dynamically adapts to different vehicles and driving conditions.
Solution Approach 2:
The patent adds the dimension of vehicle mobility to monitoring, transforming the system from fixed-point observation to mobile, continuous monitoring across multiple spatial dimensions. Multiple vehicles become distributed monitoring nodes throughout the road network.
2Ease of operation
If a static camera at a fixed position is used to monitor driving behavior, then the monitoring means is simple, but the detection of illegal driving behavior may be omitted
Solution Approach 1:
The vehicle-mounted monitoring system serves multiple functions: it monitors the host vehicle's driving behavior, captures surrounding vehicle information, and provides real-time warnings. This multi-functional approach improves detection accuracy while maintaining operational simplicity.
Solution Approach 2:
The system uses cloud platforms as intermediaries to process and analyze driving behavior data, enabling accurate detection of illegal behaviors through centralized processing while keeping individual vehicle systems relatively simple.
3Reliability
If real-time monitoring of driving behavior is implemented, then comprehensive monitoring can be achieved, but the system complexity increases
Solution Approach 1:
The monitoring system is segmented into distinct functional modules: information acquisition modules for capturing driving behavior and surrounding vehicle data, analysis modules for processing the data, and warning modules for providing real-time alerts. This segmentation manages complexity while maintaining real-time monitoring capability.
Solution Approach 2:
The cloud platform serves as an intermediary that handles complex data processing and analysis tasks, allowing individual vehicle systems to remain relatively simple while achieving comprehensive real-time monitoring through distributed architecture.
4Measurement precision
If comprehensive real-time monitoring of all vehicles is implemented, then all illegal driving behaviors can be detected, but information processing requirements increase
Solution Approach 1:
The system extracts only relevant driving behavior information from the vast amount of data generated by multiple vehicles, focusing on illegal behaviors and safety-critical events. This selective extraction reduces information processing load while maintaining comprehensive detection capability.
Solution Approach 2:
The cloud platform performs multiple information processing functions simultaneously: data collection from multiple vehicles, analysis of driving behaviors, identification of illegal activities, and generation of warnings. This multi-functional processing efficiently manages information load.
Data Source
AI summary
The disclosure relates to an Internet of Vehicles technology, and particularly to a driving behavior correction method and device based on the Internet of Vehicles. The driving behavior correction method based on the Internet of Vehicles comprises: a first information acquirer acquiring information about a vehicle in real time, and a second information acquirer acquiring vehicle condition information about the other surrounding vehicles on a travelling road in real time; and a determination unit arranged in the vehicle or at a cloud determining in real time, according to the information about the vehicle and the vehicle condition information about the surrounding vehicles, whether a driving behavior of the vehicle is dangerous, and if so, issuing a driving behavior correction prompt to the driver of the vehicle, which can intervene in and correct the driving behavior of the driver in real time.