Vehicle Navigation Fuel Consumption Prediction
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Solution Overview
Problem
Current vehicle navigation systems lack precision in predicting fuel consumption and time of arrival due to their failure to account for driving style, traffic, and road conditions, leading to an exchange relationship between these variables that is difficult to reconcile effectively.
Innovation Solution
The system calculates fuel consumption and time of arrival by recording a destination user input, storing a driving speed profile, and incorporating environmental information such as traffic, road conditions, and weather, allowing for precise predictions and user interface outputs that suggest adjustments to achieve a desired balance between fuel consumption and time of arrival.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the vehicle accelerates to achieve earlier time of arrival, then the time of arrival is improved, but the fuel consumption increases
Solution Approach 1:
The system dynamically adjusts driving parameters (speed, acceleration, route selection) based on real-time conditions including traffic data, road gradient, and weather information to optimize the balance between arrival time and fuel consumption. The navigation apparatus calculates multiple scenarios with different parameter combinations to find the optimal solution.
Solution Approach 2:
The system incorporates feedback loops where actual fuel consumption and arrival time data are continuously monitored and compared against predictions. This feedback is used to refine the exchange relationship model and improve future predictions, allowing the system to learn from actual driving patterns and environmental conditions.
2Measurement precision
If traditional navigation methods are used without considering driving style and environmental conditions, then the system complexity is reduced, but the prediction precision of fuel consumption and time of arrival deteriorates
Solution Approach 1:
The system segments the prediction model into distinct components: driving style analysis, traffic condition assessment, road condition evaluation, and weather impact calculation. Each component processes specific data types and can be independently optimized or updated, making the overall complex system more manageable and maintainable.
Solution Approach 2:
The navigation apparatus is designed to perform multiple functions simultaneously: route planning, fuel consumption prediction, time of arrival calculation, and provision of driving suggestions. By integrating these functions into a single system, the patent avoids the need for separate devices while achieving comprehensive prediction capabilities.
Data Source
AI summary
The present disclosure is related to vehicle navigation systems. The teachings may be embodied in methods for predicting fuel consumption and time of arrival, including: recording a destination user input; calculating a distance to the destination from a current location of the vehicle; recording a driving speed profile for the destination user input or for a route to the destination, as calculated by the vehicle navigation apparatus; storing the driving speed profile together with a driver feature; recording a user input comprising a desired speed, time of arrival, or fuel consumption trend; recording a second destination user input; and calculating the fuel consumption and the time of arrival for the new destination user input on the basis of a route to the further destination, as calculated by the vehicle navigation apparatus, and a consumption value representing fuel consumption of the stored driving speed profile applied to the route.