Fuel Station Scoring System for Travel Route Optimization
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Solution Overview
Problem
Existing technologies fail to optimize fueling costs and convenience by not considering the unit cost of fuel, location, and other factors when choosing a fuel station for vehicles during travel.
Innovation Solution
A method and system that determine candidate fuel stations along a travel route by calculating scores based on fuel cost, travel cost, and resource cost, ranking them for user selection, using a search corridor and integrating with mapping and location services to provide the most cost-effective or time-efficient options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If fuel cost alone is used to select a fuel station, then fuel expense is minimized, but travel time and convenience deteriorate due to detours
Solution Approach 1:
The system changes the parameter of cost evaluation from a single dimension (fuel price) to multiple dimensions by introducing composite scores that include fuel cost, travel time, and detour distance. This allows the system to find optimal fuel stations that balance multiple competing factors rather than simply minimizing one parameter.
Solution Approach 2:
The system applies different weighting factors to different cost components based on user preferences and specific trip conditions. For example, a commuter might weight travel time more heavily, while a long-distance traveler might prioritize fuel cost, allowing localized optimization for different use cases.
2Loss of information
If multiple factors (fuel cost, travel time, detour distance) are considered, then decision quality improves, but computational complexity increases
Solution Approach 1:
The system segments the complex decision-making process into distinct computational modules: one module calculates fuel costs, another calculates travel time, a third calculates detour distances, and a final module combines these into composite scores. This segmentation makes the overall complex computation more manageable and efficient.
Solution Approach 2:
The system performs preliminary calculations of route parameters, fuel prices, and station locations before the actual decision is needed. By pre-computing these values and storing them, the system reduces the computational burden during the actual fueling decision moment.
Data Source
AI summary
A system and method for planning fueling during a travel. The method comprises receiving information identifying a starting point and a destination for the travel; determining a route between the starting point and the destination; identifying one or more candidate fuel stations that are accessible from the route; determining scores for the one or more candidate fuel stations; and outputting information identifying the one or more candidate fuel stations along with their scores. Identifying one or more candidate fuel stations may include determining a search corridor; and identifying the one or more candidate fuel stations within the search corridor. Determining the search corridor may comprise selecting a search point located on the route; selecting a search radius; drawing a search circle with a radius equal to the search radius and centered at the search point; and including the search circle in the search corridor.