Delivery Vehicle Function Control for Situation-Based Operation
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Solution Overview
Problem
Existing delivery-specific vehicle functions are not optimally controlled in real-time delivery situations, leading to inefficiencies and potential interference with work operations.
Innovation Solution
A method and device that control delivery-specific vehicle functions based on real-time delivery situations by analyzing driver work schedules, delivery maps, and zone characteristics, classifying delivery scenarios, and adjusting function settings accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If delivery-specific functions are activated in a vehicle, then work efficiency is improved, but the functions may interfere with work operations in certain situations
Solution Approach 1:
The patent implements dynamic control of delivery-specific functions by continuously monitoring delivery situation data and adjusting function activation status in real-time. The controller dynamically switches functions on or off based on current delivery conditions, transforming a static function activation system into a dynamic one that adapts to changing operational contexts, thereby improving efficiency while preventing interference with work operations.
Solution Approach 2:
The system changes the operational parameter of delivery-specific functions (activation status) based on delivery situation parameters. By monitoring parameters such as delivery location, time, and route information, the system adjusts the activation state of functions like cargo door control and temperature management, ensuring optimal performance without causing operational interference.
2Adaptability or versatility
If multiple delivery-specific functions are installed in a vehicle, then functional versatility is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal control system that manages multiple delivery-specific functions through a single integrated controller. This controller can activate or deactivate various functions (cargo door control, temperature management, route guidance) based on a unified set of delivery situation parameters, reducing control system complexity while maintaining functional versatility across different delivery scenarios.
Solution Approach 2:
The system extracts and processes only the essential delivery situation parameters needed for function control, separating critical control data from unnecessary information. By focusing on key parameters such as delivery location, time, and route status, the system simplifies the control logic while maintaining the ability to manage multiple delivery-specific functions effectively.
3Adaptability or versatility
If delivery-specific functions are controlled based on real-time delivery situations, then operational adaptability is improved, but information processing requirements increase
Solution Approach 1:
The system extracts only the essential delivery situation parameters required for function control, such as delivery location, time, and route status, from the overall data stream. By filtering and processing only these critical parameters rather than all available data, the system achieves real-time adaptability while minimizing the computational load and data processing requirements.
Solution Approach 2:
The system implements partial processing by focusing on the most critical delivery situation parameters that directly impact function activation decisions. Rather than analyzing all possible delivery data, the system processes only the essential subset of information needed for effective function control, reducing data processing load while maintaining operational adaptability.
Data Source
AI summary
Provided is a method and a device for controlling a function of a vehicle that controls a delivery-specific function of a vehicle in accordance with a delivery situation. The method may include receiving vehicle driver's work schedule data, delivery map data, and delivery stage data from a server, allocating a work schedule variable, a delivery stage variable, and a delivery destination characteristic variable in a memory, performing a computation based on the work schedule data, the delivery map data, and the delivery stage data to set values in the work schedule variable, the delivery stage variable, and the delivery destination characteristic variable, classifying the delivery situation into a plurality of cases based on the value set in the work schedule variable, the delivery stage variable, and the delivery destination characteristic variable, and controlling the delivery-specific function differently according to the plurality of cases.