Autonomous Route Characterization for Low-Complexity Vehicle Navigation
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Solution Overview
Problem
Current autonomous navigation systems for vehicles face challenges in efficiently and cost-effectively updating route maps due to the complexity and cost of sensor systems, as well as the obsolescence of maps caused by changing road conditions, making real-time and widespread implementation impractical.
Innovation Solution
A vehicle-mounted autonomous navigation system that uses sensor devices to monitor and update virtual route characterizations based on manual navigations, associating a confidence indicator with these updates to enable autonomous navigation only when the confidence meets a threshold, thereby reducing the need for extensive data collection and map updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If real-time processing and driving capabilities are simulated to replicate human driving, then autonomous navigation responsiveness is improved, but capital costs and system complexity become excessively high
Solution Approach 1:
The system performs preliminary actions by collecting and processing route data in advance to create detailed virtual characterizations of routes before autonomous navigation is needed. This pre-processing eliminates the need for complex real-time decision-making systems, as the navigation computer can simply follow pre-determined instructions stored in the virtual route characterization.
Solution Approach 2:
The invention creates a virtual copy or replica of the physical route through detailed virtual characterization, including virtual representations of road geometry, signage, intersections, and other features. This virtual model allows the navigation system to operate by referencing the pre-created digital twin rather than processing real-time sensor data, dramatically reducing computational complexity.
2Measurement precision
If detailed maps with comprehensive route data are developed, then autonomous navigation accuracy is improved, but time and effort required for map development become excessive
Solution Approach 1:
The system employs self-service mechanisms where the navigation computer automatically collects, processes, and updates route data using sensors already present in the vehicle. Rather than requiring external teams to manually survey and map routes, the system performs its own data collection and virtual characterization updates autonomously, eliminating the need for dedicated sensor vehicles and manual processing.
Solution Approach 2:
The invention makes the navigation system multi-functional by enabling it to both navigate autonomously and simultaneously update its own virtual route characterizations. The same navigation computer that controls the vehicle can also process sensor data to improve route maps, eliminating the need for separate dedicated mapping systems and personnel.
3Reliability
If sensor suites are dispatched to re-traverse routes for map updates, then route map currency is improved, but operational costs and time expenditure increase
Solution Approach 1:
The navigation system performs self-updates by automatically collecting new route data during normal vehicle operation and using this data to update its virtual characterizations. The system serves itself by utilizing its own operational data to maintain current route information, eliminating the need for external update missions.
Solution Approach 2:
The system enables continuous data collection and incremental updates to virtual route characterizations during every vehicle traversal. Rather than periodic re-surveying missions, the navigation computer continuously refines its understanding of routes as the vehicle operates, maintaining currency through ongoing useful action during normal service.
4Loss of information
If extensive sensor data collection is performed, then route characterization completeness is improved, but capital costs for sensor systems become prohibitive
Solution Approach 1:
The invention makes existing vehicle sensors multi-functional by using them for both their primary navigation purposes and for collecting data to update virtual route characterizations. The same cameras, LIDAR, and other sensors used for real-time navigation also capture data for map updates, eliminating the need for additional dedicated mapping sensors.
Solution Approach 2:
The system uses its own operational sensors to service its own data needs, collecting route information during normal vehicle operation. The navigation computer processes data from its existing sensor suite to maintain and update virtual route characterizations, making the system self-sufficient without requiring external sensor deployments.
Data Source
AI summary
An autonomous navigation system which enables autonomous navigation of a vehicle along one or more portions of a driving route based on monitoring, at the vehicle, various features of the route as the vehicle is manually navigated along the route to develop a characterization of the route. The characterization is progressively updated with repeated manual navigations along the route, and autonomous navigation of the route is enabled when a confidence indicator of the characterization meets a threshold indication. Characterizations can be updated in response to the vehicle encountering changes in the route and can include a set of driving rules associated with the route, where the driving rules are developed based on monitoring the navigation of one or more vehicles of the route. Characterizations can be uploaded to a remote system which processes data to develop and refine route characterizations and provide characterizations to one or more vehicles.