Autonomous Vehicle Fleet Tracking for Suspicious Vehicle Identification
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Solution Overview
Problem
Current systems for identifying and tracking suspect vehicles are incomplete and unreliable, relying on human cooperation and imperfect technologies like toll plaza imaging and CCTV, resulting in low car theft recovery rates.
Innovation Solution
Utilizing a fleet of autonomous vehicles equipped with cameras and machine learning techniques to continuously scan for suspect vehicles, classify them based on driving patterns, and coordinate tracking without human intervention, enabling automated identification and detention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If toll plaza-based imaging systems are used to capture license plates, then some vehicle identification is achieved, but the system is incomplete and unreliable with low recovery rates
Solution Approach 1:
The patent combines multiple identification technologies (toll plaza imaging, CCTV, autonomous vehicle sensors) into a unified system that shares data and coordinates tracking across all platforms, creating a complete automated loop that overcomes the limitations of individual systems
Solution Approach 2:
The patent introduces a centralized server as an intermediary that receives data from various sources, processes information, and coordinates autonomous vehicles for tracking, enabling the system to function as an integrated whole rather than isolated components
2Measurement precision
If CCTV is used to inspect suspect vehicles, then location-based monitoring is achieved, but human operators are required to inspect images reducing efficiency
Solution Approach 1:
The patent replaces human operators with autonomous vehicles equipped with sensors and machine learning algorithms that automatically detect, classify, and track suspect vehicles, eliminating manual image inspection and significantly improving operational efficiency
Solution Approach 2:
The autonomous vehicles perform self-directed tracking and monitoring tasks using their own sensors and processing capabilities, requiring no human intervention for the core detection and tracking functions
3Loss of information
If manual law enforcement tactics are used to locate suspect vehicles, then some identifications are achieved, but the process is time-consuming and relies on human cooperation
Solution Approach 1:
The system pre-deploys autonomous vehicles in strategic locations and maintains continuous surveillance readiness, enabling immediate tracking of suspect vehicles as soon as they are identified, thereby reducing the time loss associated with mobilizing resources after identification
Data Source
AI summary
Systems and methods for identifying suspicious entities using autonomous vehicles are disclosed. In one embodiment, a method is disclosed comprising identifying a suspect vehicle using at least one digital camera equipped on an autonomous vehicle; identifying a set of candidate autonomous vehicles; enabling, on each of the candidate autonomous vehicles, a search routine, the search routine instructing each respective autonomous vehicle to coordinate tracking of the suspect vehicle; recording, while tracking the suspect vehicle, a plurality of images of the suspect vehicle; periodically re-calibrating the search routines executed by the autonomous vehicles based on the plurality of images; and re-routing the autonomous vehicles based on the re-calibrated search routines.