Shared Vehicle Fare Calculation System
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Solution Overview
Problem
Current vehicle sharing services face challenges in efficiently and reasonably calculating usage fares due to various conditions and unexpected situations, lacking a comprehensive method to account for different driving modes and passenger dynamics.
Innovation Solution
A method and system for controlling shared vehicles that calculates usage fares based on operation time periods in manual and automatic driving modes, incorporating discounts and extra charges, and dynamically converts between driving modes (manual, autonomous, and remote) to reflect changing conditions and passenger situations, using a server for remote control and fare calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a shared vehicle service is provided without considering various driving modes and conditions, then the service can be simplified and easier to operate, but the fare calculation becomes inaccurate and unfair
Solution Approach 1:
The patent segments the fare calculation system into multiple independent modules: manual driving mode calculator, autonomous driving mode calculator, remote driving mode calculator, and supplementary service calculator. Each module handles specific driving modes and conditions separately, allowing for precise calculation of each segment while maintaining overall system manageability through modular architecture.
Solution Approach 2:
The system dynamically adjusts the fare calculation based on real-time driving conditions, mode transitions, and operational parameters. The controller continuously monitors driving mode, passenger presence, and vehicle status to adaptively calculate fares, ensuring accuracy reflects actual usage patterns while the modular structure prevents overwhelming complexity.
2Measurement precision
If the system calculates fares based on multiple factors including driving modes and passenger conditions, then fare accuracy improves, but the calculation process becomes more complex and time-consuming
Solution Approach 1:
The system performs preliminary fare calculations based on expected driving modes and conditions before the actual trip begins. The controller pre-calculates base fares and identifies applicable rate structures, then only adjusts these pre-calculated values during the trip based on mode transitions and passenger changes, significantly reducing real-time computation requirements while maintaining accuracy.
Solution Approach 2:
The system implements continuous feedback loops where the controller monitors actual driving conditions and compares them against the preliminary calculation assumptions. When deviations occur (mode changes, passenger additions/removals), the system automatically adjusts the fare calculation and provides feedback to the user interface, enabling accurate final pricing without requiring complete recalculation from scratch.
3Adaptability or versatility
If the system provides comprehensive fare calculations including discounts and extra charges, then user satisfaction improves, but the operational complexity increases
Solution Approach 1:
The system automatically applies discounts and extra charges based on pre-defined rules and detected conditions without requiring manual intervention. The controller autonomously identifies eligible discount scenarios (multi-passenger rates, extended duration discounts) and applies extra charges (remote driving fees, premium service surcharges) based on actual operational data, reducing operational burden while maintaining comprehensive fare adjustment capabilities.
Solution Approach 2:
The patent creates a universal fare calculation framework that handles multiple driving modes (manual, autonomous, remote), various passenger configurations, and diverse service conditions through a single integrated system. This multi-functional approach consolidates what would otherwise require separate manual processes into one automated system, improving ease of operation while maintaining high adaptability across different scenarios.
Data Source
AI summary
A shared vehicle and a method of controlling the same are aimed to provide a vehicle sharing service capable of efficiently and reasonably calculating a fare for a shared vehicle in various ways. A method of controlling a shared vehicle includes: driving the shared vehicle in at least one driving mode of a manual driving mode in which a driver drives the shared vehicle and an automatic driving mode in which driving is performed without a driver's intervention; calculating a usage fare by a predefined calculation method based on an operation time period of the manual driving mode and an operation time period of the automatic driving mode; and charging a sum of a usage fare of the manual driving mode and a usage fare of the automatic driving mode, as a usage fare for the shared vehicle, on the driver.