Probe Vehicle Analysis Across Travel Zones
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Solution Overview
Problem
Mapping service providers face challenges in efficiently subdividing large geographic areas into travel zones for processing and analyzing probe data, which is crucial for accurate map and traffic data provision, especially with the integration of autonomous and electric vehicles, requiring advanced algorithms and systems capable of handling dynamic transportation scenarios.
Innovation Solution
A system and method for determining vehicle attributes and paths across travel zones, processing trip data, and providing outputs based on these attributes, utilizing a mapping platform that includes a vehicle identification engine and trip data aggregation engine to analyze probe and sensor data from multiple vehicles, enabling real-time traffic analysis and route optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large geographic areas are subdivided into travel zones for processing probe data, then processing efficiency and measurement precision are improved, but device complexity and computational overhead increase
Solution Approach 1:
The patent divides large geographic areas into multiple travel zones with unique identifiers, allowing probe data to be processed in smaller, manageable segments. Each zone can be independently analyzed, improving measurement precision while distributing computational load across multiple zones rather than processing all data as one large dataset.
Solution Approach 2:
The patent introduces a spatial dimension by organizing probe data according to geographic travel zones. This spatial indexing approach adds a organizational layer that enables efficient querying and analysis of probe data based on location, transforming the data structure from a flat collection to a spatially-organized dataset.
2Productivity
If distributed computing algorithms are used for scalable map creation, then processing speed and productivity are improved, but algorithm complexity and implementation difficulty increase
Solution Approach 1:
The patent segments the map creation process into zone-level operations, where each travel zone can be processed independently or in parallel. This segmentation enables distributed computing by allowing different computational nodes to handle different zones simultaneously, improving productivity while keeping individual algorithm instances relatively simple.
Solution Approach 2:
The patent performs preliminary organization of probe data into travel zones before processing. By pre-segmenting the geographic area and assigning probe data to appropriate zones in advance, the system simplifies subsequent processing operations and enables more straightforward parallel computation across multiple zones.
3Reliability
If probe data is collected from multiple sensors across many vehicles, then data quantity and reliability are improved, but data processing time and energy consumption increase
Solution Approach 1:
The patent segments probe data collection and processing by travel zones, allowing the system to process data from multiple vehicles and sensors in an organized manner. By grouping data by geographic zones rather than processing all data uniformly, the system maintains high reliability through comprehensive data collection while reducing processing time through localized, zone-specific analysis.
Data Source
AI summary
An approach is provided for probe vehicle analysis across travel zones. The approach involves, for example, determining probe data, sensor data, or a combination thereof collected from a plurality of sensors of a plurality of probe vehicles traveling in a geographic area of interest. The approach also involves for each probe vehicle of the plurality of probe vehicles, determining a vehicle attribute and a vehicle path for each probe vehicle from the probe data, the sensor data, or a combination thereof, and determining a start travel zone and an end travel zone of the vehicle path for each probe vehicle. The approach further involves processing the vehicle path for each probe vehicle to determine trip data crossing travel zones based on the start travel zone and the end travel zone. The approach further involves providing the trip data as an output based on the vehicle attribute.