Vehicle Location Correction Using Sensor Feature Measurements
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Solution Overview
Problem
Current vehicle location determination methods, such as GPS and dead reckoning, face accuracy issues due to signal obstructions and sensor inaccuracies, leading to significant positional errors, especially in environments with obstructed line-of-sight to satellites and over long distances.
Innovation Solution
A method and system that corrects dead reckoning location errors by using feature information from identifiable surrounding objects, obtained through sensors like LIDAR, cameras, and radar, employing triangulation, trilateration, and sensor fusion, along with statistical bias and neural networks to predict and correct location errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS is used to determine vehicle location, then location information is obtained, but accuracy degrades significantly under weak signal conditions such as when line-of-sight to satellites is obstructed
Solution Approach 1:
The patent introduces dead reckoning as an intermediary method to bridge the gap when GPS fails. The system uses onboard sensors (accelerometers, gyroscopes, wheel encoders) to calculate position changes from a known starting point, serving as a mediator that provides continuous location estimation when direct satellite signals are blocked by tall buildings, mountains, or canyons
Solution Approach 2:
The system performs preliminary action by continuously tracking and storing the vehicle's position, speed, and orientation data from sensors even when GPS is available. This preliminary data collection and error compilation creates a foundation that can be quickly applied when GPS signals become weak or obstructed, reducing the lag in maintaining accurate positioning
2Reliability
If dead reckoning is used to determine vehicle location, then location can be calculated without GPS signals, but sensor inaccuracies accumulate over time resulting in significant positional error
Solution Approach 1:
The patent implements feedback by continuously monitoring dead reckoning position estimates against available GPS data when signals are strong. The system compiles correction data from the differences between these two methods and uses statistical bias analysis and neural networks to predict and correct accumulated errors, creating a closed-loop system that self-corrects over time
Solution Approach 2:
The system dynamically changes parameters by adjusting the weighting and fusion of different sensor data sources based on environmental conditions. When GPS is available, the system uses it to recalibrate dead reckoning parameters; when GPS is obstructed, it relies more heavily on sensor fusion algorithms that adaptively weight accelerometer, gyroscope, and wheel encoder data to minimize drift
3Measurement precision
If multiple sensors are used for location determination, then accuracy is improved in challenging environments, but system complexity increases
Solution Approach 1:
The patent applies universality by designing a multi-functional sensor system where the same onboard sensors (accelerometers, gyroscopes, wheel encoders) serve multiple purposes: they provide data for both dead reckoning navigation and for compiling correction data to improve GPS accuracy when available. This multi-functionality reduces the need for additional specialized sensors while maintaining high accuracy across different operating conditions
Data Source
AI summary
Systems and methodologies for determining location of a vehicle is provided. The method includes obtaining a first location of the vehicle at a first time. A dead reckoning location of the vehicle is determined at a second time. Additionally, feature information is obtained at the second time. The feature information may be provided by a digital map or database, that includes records for at least some of the vehicle's surrounding objects. These records may include, for example, relative positional attributes in addition to the traditional absolute positions. Location measurements are obtained for one or more features that are identifiable based on the feature information. The dead reckoning location of the vehicle is corrected based on the location measurements.