Vehicle Sensor Vector Data for Real-Time Traffic Flow Forecasting
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Solution Overview
Problem
Existing navigation systems rely on road sensors or user-reported data, which are inadequate for real-time detection of sudden traffic changes, especially in areas without sensor coverage or during accidents.
Innovation Solution
An electronic device in a vehicle uses sensors like gyro, GPS, and earth magnetic field sensors to generate vector data, which is transmitted to a server or other vehicles to predict dangerous situations by analyzing road, weather, and historical data, and informs drivers through varying alerts based on danger level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If road sensors or user-reported data are used for traffic detection, then device complexity is reduced, but measurement precision and reliability of real-time traffic condition detection deteriorate
Solution Approach 1:
The patent combines multiple data sources including road sensor data, user-reported data, and vehicle-mounted sensor data (from portable devices) into a unified traffic condition detection system. This merging allows the system to maintain low individual device complexity while achieving high overall measurement precision through data fusion and cross-validation of multiple sources.
2Measurement precision
If road sensors are installed to detect traffic flow, then measurement precision improves, but device complexity and infrastructure requirements increase
Solution Approach 1:
The patent makes portable devices (smartphones, tablets) serve multiple functions: they act as navigation terminals, traffic condition detectors, and data transmission devices. By utilizing existing multi-functional devices rather than dedicated single-function sensors, the system achieves traffic flow detection capabilities without increasing infrastructure complexity.
Solution Approach 2:
The system enables vehicles and portable devices to self-report their own traffic conditions and environmental sensor data without requiring external detection infrastructure. Each vehicle becomes its own sensor node, automatically collecting and transmitting data about its surroundings and traffic conditions.
3Ease of manufacture
If user-reported data is used for traffic information, then infrastructure cost is reduced, but reliability and response time to sudden traffic changes deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where traffic condition data from multiple sources (including user reports and sensor data) is continuously collected, analyzed, and used to update and improve the accuracy of traffic predictions. The system provides feedback to users about traffic conditions and uses this feedback loop to enhance reliability over time through machine learning and data validation.
Data Source
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AI summary
Disclosed are a method and an apparatus for forecasting the flow of traffic. The method includes: detecting measurement information of a vehicle by using a sensor; generating vector data based on the measurement information; and transmitting the generated vector data.