Vehicle Group Formation Based on Driver Mode
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Solution Overview
Problem
Existing vehicle group formation systems fail to consider the driver's preferred running mode, leading to suboptimal arrival times and mileage efficiency.
Innovation Solution
A running control apparatus that compares action plans of vehicles to determine whether to form a group, allowing vehicles to run solo or in a group based on the driver's required mode, using parameters like target speed patterns and routes, and generating action plans to satisfy the driver's preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If vehicles form a group based on similarity of vehicle information, then traffic flow efficiency and mileage are improved, but the driver's preferred running mode is not reflected and arrival time is not optimized
Solution Approach 1:
The patent changes the parameter for group formation from static vehicle information similarity to dynamic action plan comparison. Action plans include temporal change of target position, target speed patterns, and target routes, which are generated based on driver preferences. This allows the system to adapt to different driver modes (e.g., time-saving vs. mileage-saving) while still forming efficient vehicle groups.
Solution Approach 2:
The system dynamically adjusts group formation decisions based on real-time action plan comparisons. Instead of fixed grouping criteria, the system continuously evaluates whether forming a group with another vehicle or vehicle group better satisfies the driver's preferred running mode, allowing flexible adaptation to changing conditions and driver preferences.
2Loss of energy
If vehicles form a group to improve mileage, then fuel efficiency increases, but the vehicle cannot respond to driver's need for faster arrival
Solution Approach 1:
The patent introduces driver preference parameters that can weight time savings versus mileage savings differently. The action plans incorporate temporal change of target position and target speed patterns that reflect driver priorities. When drivers prioritize time savings, the system generates action plans that allow faster arrival even if group formation is not optimal for mileage, and vice versa.
Solution Approach 2:
The system dynamically selects between group formation and solo travel based on real-time comparison of action plans. If joining a group results in better fuel economy according to the driver's preferences, the system chooses group formation. If faster arrival is prioritized, the system allows solo travel or selects groups that enable quicker arrival, thus dynamically optimizing the trade-off between energy loss and time loss.
3Ease of operation
If the system forms vehicle groups automatically, then group formation is smooth, but it cannot allow vehicles to run solo when needed
Solution Approach 1:
The system uses feedback from action plan comparisons to determine whether group formation is beneficial. By continuously comparing the action plans of potential group members against the driver's preferred running mode, the system receives feedback on whether joining a group aligns with driver intentions. This feedback mechanism allows the system to smoothly form groups when appropriate while also allowing solo travel when the feedback indicates it's better for the driver's preferences.
Data Source
AI summary
Information for generating a target speed pattern is computed from information acquired from various sensors and a running mode input switch, so as to generate the target speed pattern (S16). A process for determining whether to form a vehicle group or not calculates the difference between the target vehicle pattern of the own vehicle and a target speed pattern of another vehicle or vehicle group obtained through inter-vehicle communication, so as to determine whether to form the vehicle group or not (S22, S28, S32). This can determine whether to run solo or form a vehicle group according to a driver's demand.