Vehicle Trajectory Estimation Using GPS Segmentation
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Solution Overview
Problem
Existing GPS data analysis methods for estimating vehicle trajectories are prone to errors due to corrupted data, with existing approaches either considering only first and last GPS measurements or all successive data points, leading to inaccurate results and increased computation time.
Innovation Solution
A method that segments GPS data into equal time intervals, associates each data point with a time interval, maps candidate points to neighborhood road segments, and determines the shortest path between these points to estimate the vehicle's trajectory, using a combination of shortest path and edit distance techniques for accurate trajectory estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all successive GPS data points are considered for trajectory estimation, then the coverage of the trajectory is improved, but the computation time and error increase due to convoluted paths
Solution Approach 1:
The patent segments the GPS data points into multiple groups based on time intervals and spatial proximity. Each segment is processed independently to determine local trajectories, which are then combined to form the complete trajectory. This segmentation reduces computation time by avoiding the need to process all data points simultaneously while maintaining accuracy through comprehensive coverage of segmented paths
2Loss of time
If only first and last GPS measurements are considered, then the computation time is reduced, but the trajectory estimation accuracy deteriorates due to loss of intermediate data
Solution Approach 1:
The patent applies partial action by selecting a representative subset of GPS data points that are neither too few (first and last only) nor too many (all points). The method identifies optimal intermediate points based on time intervals and spatial characteristics, using enough points to capture trajectory nuances while avoiding the computational burden of processing every single measurement
3Measurement precision
If more GPS data points are used for trajectory estimation, then the trajectory coverage is improved, but the computation complexity increases
Solution Approach 1:
The patent divides the complete set of GPS data points into manageable segments based on time intervals and spatial clusters. Each segment is processed through simplified trajectory estimation algorithms, reducing the computational complexity that would arise from processing all points as a single large dataset while maintaining comprehensive trajectory coverage through the combination of segmented results
Data Source
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AI summary
Accurate estimation of the trajectory of a vehicle by selecting optimal number of GPS data points and a shortest path technique applied for estimation is important and crucial. Method and system for estimating a trajectory from GPS data points is described. The method disclosed utilizes a plurality of GPS data points of a vehicle, an existing road map and a set of equal time intervals obtained by dividing an elapsed time during movement of the vehicle. Each GPS data point is associated to a time interval and a set of candidate points are mapped to each GPS data point correspondingly. A set of possible paths are determined between the set of candidate points in each time interval to estimate the trajectory of the vehicle using one of a shortest path technique and an edit distance technique.