Map Database Self-Update via Vehicle Movement Data
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Solution Overview
Problem
Digital road map databases for vehicle navigation lack essential information such as stop signs, timed traffic lights, and time-dependent turn restrictions, and often contain inaccuracies due to human error or outdated data, limiting the accuracy and functionality of routing applications.
Innovation Solution
A vehicle positioning system records its movements to derive additional map details, such as stop signs and traffic light timing, and updates the database to correct existing information, including identifying connections and time-dependent intersections, thereby enhancing the database's accuracy and completeness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map database information is manually created and maintained, then initial database creation is possible, but the database lacks up-to-date information and contains inaccuracies due to human error
Solution Approach 1:
The system enables the map database to update itself automatically by having vehicles collect data during normal operation and autonomously update the database without manual intervention. Vehicles detect stop signs, traffic lights, and road connections through their own movement patterns and contribute this data to the database.
Solution Approach 2:
The system implements feedback loops where vehicle movement data is continuously collected, analyzed to detect traffic control devices and road features, and then used to update the database. The updated database in turn provides better routing information to vehicles, creating a self-improving system.
2Measurement precision
If the database includes detailed traffic control information and time-dependent restrictions, then routing accuracy improves, but the database complexity and difficulty of maintenance increase
Solution Approach 1:
The complex task of collecting and verifying detailed traffic control information is performed automatically by the distributed vehicle network rather than manual database maintainers. Vehicles autonomously detect and report traffic lights, stop signs, and time-dependent restrictions, eliminating the need for complex manual data entry and verification processes.
3Reliability
If the database is updated frequently to reflect road changes, then information currency improves, but the cost and complexity of manual updates increase
Solution Approach 1:
The database performs self-updating through the continuous collection of vehicle movement data. As vehicles traverse the road network, they automatically detect new road connections, changes in traffic control devices, and other infrastructure modifications, updating the database in real-time without external intervention.
Solution Approach 2:
The system maintains continuous data collection and updating as vehicles operate on the road network. Rather than periodic manual updates, the database is constantly refined through the ongoing movement of vehicles, ensuring information remains current without discrete update events.
Data Source
AI summary
Traffic information readings corresponding to a vehicle are received, the readings including at least a location. The traffic information readings are compared to information already within a map database, and are used to derive additional map information augmenting or correcting that already within the database, the additional map information subsequently being stored in the database. Additional information that is derived includes the presence of stop signs and traffic lights at intersections, the legality of turns at certain times of day, and the connectedness or non-connectedness of road segments.