Route Estimation Using Dynamic Data and Simulation
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Solution Overview
Problem
Conventional travel route estimation methods are inaccurate due to errors or interference in object position detection systems, particularly in urban environments, and fail to consider object dynamics and travel history, leading to quick and unrealistic route estimations.
Innovation Solution
A method that utilizes object dynamic data and enhanced route simulations by determining positions, simulating multiple possible routes, ranking them based on criteria like distance, velocity, acceleration, and travel history, and estimating the most probable route, ensuring accuracy and realism in route estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional route estimation methods are used, then the estimation process is fast, but the accuracy and realism of the estimated route deteriorates
Solution Approach 1:
The system performs preliminary actions by determining object position, velocity, and acceleration data before route estimation, and pre-simulates multiple possible routes between positions. This preparation of data and route options in advance enables more accurate estimation without excessive delay during the actual estimation process.
Solution Approach 2:
The system applies dynamics by incorporating object velocity and acceleration data into the route estimation process, and by simulating multiple possible routes rather than selecting a single static route. This dynamic approach considers the object's movement characteristics to determine the most probable route, improving accuracy while managing computation time through efficient simulation.
2Measurement precision
If position data is used alone for route estimation, then the process is simple, but the estimation accuracy deteriorates due to errors and interference
Solution Approach 1:
The system merges multiple data sources including object position data, velocity data, acceleration data, and travel history data into a unified route estimation process. By combining these different types of data, the system compensates for errors in position data alone and achieves more accurate route estimation despite increased data processing requirements.
Solution Approach 2:
The system uses feedback by comparing simulated routes against actual object movement characteristics (velocity, acceleration, travel history) to determine the most probable route. This feedback mechanism allows the system to validate and refine route estimates, improving accuracy while managing complexity through systematic data comparison.
3Measurement precision
If multiple simulation criteria are applied, then the route estimation accuracy improves, but the computational complexity increases
Solution Approach 1:
The system applies partial action by simulating multiple possible routes rather than exhaustively analyzing all possible routes. This selective simulation of relevant routes, rather than complete enumeration, achieves sufficient accuracy while controlling computational complexity through focused rather than exhaustive analysis.
Data Source
AI summary
The present disclosure is directed to methods for estimating a route of an object. The method includes determining a first position of an object at a first time, determining a second position of the object at a second time subsequent to the first time, automatically simulating a plurality of possible routes between the first position and the second position, ranking the plurality of possible routes between the first position and the second position, and estimating a most probable route from among the plurality of possible routes between the first position and the second position.