Autonomous Vehicle Route Constraints for Changing Road Conditions
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating through environments where map data is not updated to reflect changing travel conditions, such as road closures or events, leading to inefficiencies and potential safety hazards.
Innovation Solution
A computer-implemented method and system that access map data and constraint files to determine composite constraint data, which defines permissible and exclusion areas for navigation, allowing autonomous vehicles to dynamically adjust their routes based on real-time traffic flow information and events, ensuring safe and efficient navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicles rely on static map data for navigation, then the navigation system is simple and stable, but it cannot reflect changing travel conditions such as road closures or events
Solution Approach 1:
The patent implements dynamic constraint data that can be updated in real-time to reflect changing travel conditions. Constraint files are received from remote computing devices and applied to modify the navigation constraints dynamically, allowing the system to adapt to road closures, events, and other changing conditions without requiring a complete redesign of the navigation system.
Solution Approach 2:
The patent pre-defines constraint data structures and constraint files that contain navigational restrictions for various geographic areas and travel ways. These constraint files are prepared in advance and can be quickly applied when changing conditions are detected, enabling rapid adaptation without real-time computation during critical moments.
2Reliability
If map data is frequently updated to reflect changing conditions, then navigation accuracy improves, but data transmission and processing requirements increase
Solution Approach 1:
The patent extracts only the essential navigational constraint information from complete map data updates. Instead of transmitting entire updated maps, the system transmits targeted constraint files that contain specific geographic identifiers, travel way identifiers, and constraint types relevant to changing conditions, significantly reducing data transmission requirements while maintaining navigation reliability.
Solution Approach 2:
The patent applies constraint data at specific local locations rather than globally updating all navigation data. Constraint files target specific geographic areas, travel ways, or intersections affected by changing conditions, allowing the system to maintain high navigation reliability in affected areas while minimizing overall data transmission and processing requirements.
3Productivity
If autonomous vehicles determine routes using only onboard map data, then navigation is independent and fast, but routes may not optimize for current traffic conditions or events
Solution Approach 1:
The patent implements a feedback mechanism where constraint data is continuously updated based on changing travel conditions. Remote computing devices monitor traffic conditions, events, and road status, then transmit updated constraint files to autonomous vehicles. This feedback loop enables route optimization for current conditions without requiring complex real-time processing onboard each vehicle.
Solution Approach 2:
The patent introduces constraint files as an intermediary data structure that bridges onboard navigation systems and external traffic information sources. These constraint files contain pre-processed navigational restrictions that simplify the integration of external traffic data into the onboard routing algorithm, reducing data processing complexity while improving route optimization efficiency.
Data Source
AI summary
Systems and methods for controlling the motion of an autonomous vehicle are provided. In one example embodiment, one or more computing devices on-board an autonomous vehicle receive one or more constraint files including constraint data descriptive of one or more geographic identifiers (e.g., a polygon) and an application type (e.g., partial inclusion, complete inclusion, partial exclusion, complete exclusion) associated with each of the one or more geographic identifiers. Map data descriptive of the identity and location of different travel ways within the surrounding environment of the autonomous vehicle is accessed. A travel route for navigating the autonomous vehicle is determined, wherein the travel route is determined at least in part from the map data evaluated relative to the constraint data. Motion of the autonomous vehicle can be controlled based at least in part on the determined travel route.