Navigation System Fuel Route Optimization
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Solution Overview
Problem
Existing navigation systems fail to determine fuel-efficient routes for vehicles as they do not account for the effect of speed on fuel efficiency and do not consider the number of stops and slowdowns, which are crucial factors in minimizing fuel usage.
Innovation Solution
A navigation system that calculates fuel-efficient routes by incorporating estimated speeds, number of stops, and slowdowns, using GPS data and aggregated vehicle efficiency data, while also considering user preferences and real-time information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a navigation system determines a route based only on altitude information, then the route determination is simple, but the fuel consumption calculation is inaccurate because it does not account for speed effects and stopping behavior
Solution Approach 1:
The patent segments the route into multiple sections with different characteristics (altitude changes, speed zones, intersection densities). By dividing the route calculation into discrete segments, the system can apply specific fuel consumption models to each segment based on its dominant characteristics, improving overall accuracy without requiring a single overly complex model for the entire route.
Solution Approach 2:
The system performs preliminary calculations of estimated fuel consumption for multiple candidate routes before presenting them to the driver. By pre-calculating fuel usage incorporating speed effects, altitude changes, and stopping behavior, the navigation system prepares optimized route options in advance, allowing the driver to make informed decisions without experiencing real-time calculation delays.
2Measurement precision
If the system incorporates multiple factors (speed, stops, slowdowns) to determine fuel-efficient routes, then fuel consumption accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent changes key parameters such as vehicle speed, acceleration rates, and stopping frequencies to reflect real-world driving conditions. By dynamically adjusting these parameters based on route characteristics and vehicle behavior, the system achieves more accurate fuel consumption estimates without requiring an excessively complex computational model.
Solution Approach 2:
The navigation system utilizes data already available from the vehicle's onboard systems (GPS location, speed sensors, engine data) to perform fuel consumption calculations. By leveraging existing vehicle data streams, the system avoids the need for additional specialized sensors or external data sources, reducing overall system complexity while maintaining calculation accuracy.
3Productivity
If the navigation system calculates routes considering real-time information and driver behavior data, then route optimization improves, but the data processing requirements increase
Solution Approach 1:
The system processes only the most critical data elements necessary for fuel-efficient routing, such as speed variations, stopping events, and altitude changes, rather than analyzing every available data point. By focusing on the most impactful factors, the system achieves effective route optimization without the computational burden of processing complete real-time datasets.
4Reliability
If the system estimates fuel usage based on aggregated vehicle data, then individual vehicle variations are accounted for, but the generalization error increases
Solution Approach 1:
The patent applies local quality by using aggregated vehicle data to establish baseline fuel consumption characteristics for different vehicle types, then adjusts these baselines with route-specific factors (altitude, speed, traffic conditions). This approach maintains reliability through representative aggregated data while improving precision for individual vehicles through localized route condition adjustments.
Data Source
AI summary
Apparatus, methods, processors and computer readable media for determining a suggested route having an estimated minimum fuel usage for a vehicle based on a estimated fuel efficiency for the vehicle for different speeds of the vehicle and based on estimated speeds for the route. The estimated fuel efficiency for the vehicle is based on aggregated data for the vehicle. Alternatively, the estimated fuel efficiency is based on actual data for the vehicle. In some embodiments, suggested routes are constrained by user route preferences, and real-time route information. Alternatively or additionally, the estimated fuel usage is based on actual driver behavior data.