Autonomous Vehicle Theft Detection Using Torque-Based Weight Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles carrying goods face challenges in detecting theft in real-time, as existing systems lack effective methods to monitor weight changes during various driving conditions, which can lead to undetected thefts.
Innovation Solution
An in-vehicle control computer system that estimates the weight of goods and vehicles using torque values, acceleration, pitch angles, and gravity, sending alerts to law enforcement or command centers if significant weight differences are detected, and can initiate vehicle stoppage or parking upon theft detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If weight sensors are installed in the vehicle to detect theft, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces mechanical weight sensors with a computational approach using existing vehicle sensors (accelerometers, gyroscopes, torque sensors) to calculate weight. The control computer processes sensor data through mathematical models to determine vehicle weight, eliminating the need for dedicated mechanical weight measurement devices while maintaining detection precision.
2Reliability
If real-time weight monitoring is implemented during driving, then reliability of theft detection is improved, but use of energy increases
Solution Approach 1:
The system performs weight monitoring at periodic intervals rather than continuously. The control computer calculates vehicle weight at predetermined time points during driving, comparing weights between intervals to detect theft. This periodic approach maintains detection reliability while significantly reducing energy consumption compared to continuous monitoring.
3Measurement precision
If multiple sensors and complex calculations are used to estimate weight during driving, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent makes existing vehicle sensors serve multiple functions. Accelerometers and gyroscopes used for navigation and stability control are also utilized for weight estimation. The torque sensor serves both engine control and weight calculation purposes. This multi-functionality approach improves measurement precision through data fusion while avoiding the need for additional dedicated sensors.
Solution Approach 2:
The control computer acts as an intermediary that processes and integrates data from multiple sensors to calculate weight. Rather than directly measuring weight, the system uses the control computer to compute weight from torque, acceleration, and orientation data, providing a unified processing layer that simplifies the overall system architecture.
4Adaptability or versatility
If weight comparison is performed at different times during driving, then adaptability to various driving conditions is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The system compensates for driving condition variations by dynamically adjusting calculation parameters. The control computer modifies weight estimation calculations based on detected driving conditions, terrain slope, vehicle load distribution, and sensor data quality. This allows accurate weight comparison across different driving scenarios while managing detection difficulty through adaptive parameter adjustment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time detection of theft by accurately estimating weight changes, ensuring timely alerts and potential vehicle stoppage, thereby reducing theft risks during autonomous operations.
Implementation Method 1
estimating the first weight of goods included in the autonomous vehicle based at least on a first drive force, a first acceleration value, and a first pitch angle of the autonomous vehicle
Implementation Method 2
a third function comprising the first acceleration value, gravity, and the first pitch angle
Data Source
AI summary
Techniques are described for determining an occurrence of theft in a vehicle. An example processor implemented method comprises receiving, by a computer located in an autonomous vehicle and at a first time, a first torque value that indicates a first amount of torque applied by an engine of the autonomous vehicle to drive the autonomous vehicle, receiving, at a second time that is later in time than the first time, a second torque value that indicates a second amount of torque applied by the engine of the autonomous vehicle, determining that a difference between a first value and a second value is greater than a pre-determined value, where the first value and the second value are functions of at least the first torque value and at least the second value respectively, and displaying, in response to the determining, a message that indicates a theft detection in the autonomous vehicle.