Shared Vehicle Mobility Insights for Navigation Systems
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Solution Overview
Problem
Current navigation systems face challenges in integrating shared vehicles into multimodal or intermodal navigation routes due to the lack of real-time data on shared vehicle availability and location near points of interest, limiting users' flexibility and options for transportation.
Innovation Solution
A system that retrieves and processes shared vehicle data to provide mobility insight data, including usage and availability patterns, which are then presented in a location-based user interface, enabling users to make informed decisions about their travel options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If shared vehicle services are integrated into navigation routes, then user flexibility and transportation options are improved, but the system complexity and data processing requirements increase due to lack of real-time vehicle availability data
Solution Approach 1:
The patent introduces shared vehicle data as an intermediary element that mediates between the navigation system and the user. This data acts as a bridge, providing real-time information about vehicle availability, location, and usage patterns, thereby enabling the navigation system to integrate shared vehicles into routes without requiring direct complex interactions with vehicle operators or infrastructure
Solution Approach 2:
The system performs preliminary actions by pre-processing and storing shared vehicle data, including usage patterns and availability information, before navigation queries are made. This allows the navigation system to quickly access and utilize shared vehicle information when calculating routes, rather than querying vehicle status in real-time during route planning
2Loss of information
If real-time shared vehicle data is processed to provide mobility insights, then user decision-making capability is improved, but data retrieval and processing time increase
Solution Approach 1:
The system applies partial action by selectively processing and retrieving only the most relevant shared vehicle data needed for navigation decisions, such as vehicle availability in the vicinity of POIs, usage patterns for specific time periods, and proximity information. This avoids processing all possible vehicle data, reducing time costs while maintaining sufficient information completeness for user decision-making
Solution Approach 2:
The patent implements local quality by focusing data processing on specific locations (points of interest) and time periods relevant to user trips. Instead of processing global shared vehicle data uniformly, the system retrieves and processes vehicle information localized to areas and times when users are likely to need transportation, thereby reducing overall data processing time while providing locally relevant mobility insights
3Measurement precision
If shared vehicle usage patterns are analyzed for multiple POIs, then the accuracy of mobility insights is improved, but the quantity of data to be processed increases
Solution Approach 1:
The system segments the analysis of shared vehicle usage patterns by dividing it into discrete components associated with individual points of interest. Each POI's mobility insights are calculated separately based on its specific usage patterns, allowing the system to process data in manageable segments rather than attempting to analyze all vehicle data globally at once, thereby maintaining accuracy while controlling data volume
Data Source
AI summary
An approach is provided for providing mobility insight data related to shared vehicles for a point of interest (POI). The approach involves retrieving shared vehicle data for the POI. The shared vehicle data indicates one or more shared vehicle events that have occurred, that are occurring at a given time, or a combination thereof within a threshold proximity of the POI. The approach also involves processing the shared vehicle data to determine mobility insight data. The mobility insight data includes a shared vehicle usage pattern, a shared vehicle availability pattern, or a combination thereof under one or more contexts for travel to or from the POI. The approach further involves presenting the mobility insight data in a location-based user interface.