Composite Street Shadows for Real-Time Vehicle Environment Updates
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Solution Overview
Problem
Modern vehicles face challenges in accurately and efficiently updating environmental information due to dynamic and unpredictable real-world conditions, leading to discrepancies between real-world conditions and the information used by vehicle systems, which can affect proper functioning.
Innovation Solution
A vehicle information system generates and maintains street shadows using cloud-based computing and roadside resources, incorporating long-lived features into cloud-based computing and caching short-lived features at roadside resources, with dynamic lifetime inference models to classify and distribute events and objects based on their expected lifetimes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If periodic updates from a central server are used to update environmental information, then the system structure is simple and easy to maintain, but the update speed is insufficient to account for short-lived environmental conditions
Solution Approach 1:
The patent segments environmental information into two categories: long-lived features (stored in cloud-based street shadows) and short-lived features (cached at roadside resources). This segmentation enables different update strategies for different types of environmental data, allowing fast updates for short-lived conditions while maintaining simplicity for stable features.
Solution Approach 2:
The patent introduces a new dimension to the update system by implementing a hierarchical architecture with both cloud-based central servers and distributed roadside resources. This multi-dimensional approach allows simultaneous periodic updates from the cloud and real-time updates at the edge, resolving the contradiction between update speed and system complexity.
2Reliability
If all environmental information is cached at roadside resources, then update speed improves, but information storage requirements and system complexity increase
Solution Approach 1:
The patent applies local quality by storing different types of environmental information at different locations: long-lived features are stored in the cloud while short-lived features are cached locally at roadside resources. This localized storage strategy improves information accuracy for time-sensitive data without requiring all systems to store all information, thus managing complexity.
Solution Approach 2:
The system performs preliminary action by pre-caching short-lived environmental features at roadside resources before they are needed by vehicles. This advance preparation ensures that when vehicles require this information, it is already available locally, improving reliability without requiring complex real-time retrieval mechanisms.
3Loss of time
If cloud-based computing is used for all processing, then system management is simplified, but response time to dynamic environmental conditions increases
Solution Approach 1:
The patent introduces roadside resources as intermediaries between cloud-based computing and vehicles. These intermediaries cache and manage short-lived environmental information locally, enabling fast response to dynamic conditions without requiring all processing to occur in the cloud, thus reducing response time while managing computational distribution.
Solution Approach 2:
The system implements dynamics by allowing the location and management of environmental information to be flexible rather than static. Short-lived features can be cached at roadside resources when needed and cleared when no longer relevant, while long-lived features remain in the cloud. This dynamic allocation optimizes response time without permanent complex distributed infrastructure.
Data Source
AI summary
A vehicle information system maintains a street shadow representing attributes of an environment in which a vehicle is located or travels through. The attributes may include objects or events in the surrounding environment. In some embodiments, cloud-based computing devices maintain a primary street shadow, and roadside resources maintain information about short-lived objects or events that may be added to the primary street shadow to augment it. Additionally, a vehicle may further augment the street shadow representation with locally detected events and/or objects. Also, events and objects detected by a vehicle are provided to the roadside resource. The roadside resource may infer an estimated lifetime of the events and objects, and cache short-lived events and objects for distribution to other vehicles, and also provide long-lived events and objects to the cloud-computing devices for use in updating the primary street shadow.