Non-Connected Vehicle Tracking Beyond Connected Vehicle View
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Solution Overview
Problem
Identifying and tracking non-connected vehicles over long distances is challenging due to their lack of internet access, which hinders accurate real-time traffic condition estimation, especially when they travel beyond the field of view of connected vehicles.
Innovation Solution
The system employs sensors like cameras, GPS, and LIDAR in connected vehicles to extract features and monitor driving patterns of non-connected vehicles, predicting their future locations based on real-time traffic conditions and trajectories, allowing identification and tracking even when they are out of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If connected vehicles are used to track non-connected vehicles, then tracking capability is improved, but the system fails when non-connected vehicles travel beyond the field of view of connected vehicles
Solution Approach 1:
The system extracts and stores vehicle features (color, shape, size, logos, accessories) and driving patterns (speed, acceleration, steering angle) of non-connected vehicles while they are within the field of view of connected vehicles. This preliminary data collection enables later identification and tracking even when the vehicles travel beyond the field of view, resolving the contradiction between limited coverage and tracking reliability.
2Length of moving object
If feature extraction and comparison methods are used to identify non-connected vehicles, then tracking distance is improved, but computational complexity increases
Solution Approach 1:
The system extracts only the most discriminative vehicle features (color, shape, size, logos, accessories) and key driving pattern parameters (speed, acceleration, steering angle) rather than processing all possible vehicle data. This selective extraction reduces computational complexity while maintaining sufficient accuracy for long-distance tracking and identification of non-connected vehicles.
Data Source
AI summary
A method for tracking a non-connected vehicle is provided. The method includes obtaining one or more features of the non-connected vehicle, assigning an ID to the non-connected vehicle, the ID including information about the one or more features of the non-connected vehicle, predicting one or more locations of the non-connected vehicle in response to the non-connected vehicle being out of a field of view of a connected vehicle at a first location, identifying a vehicle at a second location, the second location corresponding to one of the predicted one or more locations, and determining whether the identified vehicle at the second location corresponds to the non-connected vehicle based on a comparison of one or more features of the identified vehicle and the ID.