Crowdsourced Navigation Using Vehicle OBD Data
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Solution Overview
Problem
Conventional personal navigation devices (PNDs) rely on patchy and uneconomical data gathering methods, failing to provide accurate real-time navigation guidance, especially concerning traffic congestion, lane closures, and parking conditions, and do not account for vehicle-specific conditions like fuel efficiency and current vehicle status.
Innovation Solution
A method utilizing crowdsourcing data from vehicles, including on-board diagnostics and GPS information, to predict route conditions, such as lane closures, traffic patterns, and parking availability, and provide dynamic navigation guidance that considers real-time vehicle data for route optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional data gathering methods using sensor boxes and manual counts are used, then congestion data can be obtained for well-traveled road segments, but the data becomes patchy and uneconomical for most roads
Solution Approach 1:
The patent makes vehicles themselves generate and provide navigation data through their existing onboard systems (GPS, speedometers, odometers). Vehicles serve their dual purpose of transportation and data collection, eliminating the need for separate expensive monitoring infrastructure. This self-service approach allows comprehensive data collection across all roads without additional economic burden.
Solution Approach 2:
Instead of using expensive physical sensor boxes deployed on roads, the patent uses virtual copies of navigation data extracted from vehicles' existing onboard systems. The same GPS and telematics systems that vehicles use for their operation are leveraged to create navigation datasets, providing a cost-free replication of monitoring functionality.
2Ease of operation
If simple metrics like shortest route or shortest time based on recorded speed limits are used for route decisions, then navigation guidance can be provided, but accurate real-time navigation guidance especially concerning traffic congestion, lane closures, and parking conditions cannot be provided
Solution Approach 1:
The patent implements continuous feedback loops where navigation data from multiple vehicles is constantly collected, processed, and used to update route recommendations in real-time. The system monitors actual vehicle positions, speeds, and destinations to dynamically adjust navigation guidance, ensuring both ease of operation and high reliability through up-to-date information.
Solution Approach 2:
The patent creates a multi-functional navigation system that simultaneously provides shortest route calculation, real-time congestion detection, lane closure identification, and parking availability assessment. By making the navigation system universal, it handles multiple navigation challenges with a single integrated approach rather than separate specialized systems.
3Adaptability or versatility
If conventional PNDs are used, then basic navigation can be provided, but assistance for determining parking conditions at the destination and consideration of current vehicle conditions before planning a route cannot be provided
Solution Approach 1:
The patent merges parking condition assessment and vehicle condition monitoring with traditional navigation routing by analyzing the same onboard diagnostic data. The system combines GPS location, speed, destination information, and vehicle status data into a unified navigation decision framework, providing enhanced functionality without requiring separate complex subsystems.
Data Source
AI summary
Method, computer program product, and apparatus for providing navigation guidance to vehicles are disclosed. The method may include receiving crowdsourcing data from at least one vehicle, determining the parking information based on one or more locations visited by the at least one vehicle, after the at least one vehicle has reached a destination, and providing the parking information to the at least one vehicle. The crowdsourcing data includes on board diagnostics data (OBD) correlated with time stamps and GPS locations of the at least one vehicle, where the on board diagnostics data includes odometer information, speedometer information, fuel consumption information, steering information, and impact data.