Vehicle Agent Cooperation for Driving Assistance
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Solution Overview
Problem
Existing vehicle-to-vehicle communication systems do not provide adequate driving assistance during overtaking or lane changes, as they primarily focus on informing drivers of the position of other vehicles without coordinating future driving intentions.
Innovation Solution
A cooperation method between agents on different vehicles, where agents estimate and share driving schedules and attributes through communication units, enabling them to provide driving assistance information to each other's drivers, including alerts for overtaking or lane changes based on the driving tendencies and responses of both drivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If agents only share current position information of vehicles, then the system complexity remains low, but driving assistance effectiveness deteriorates during overtaking or lane changes
Solution Approach 1:
The system performs preliminary estimation of future driving schedules by analyzing current driving tendencies before actual overtaking or lane change maneuvers occur. This allows agents to prepare driving assistance information in advance, improving reliability during critical maneuvers without requiring complex real-time processing
Solution Approach 2:
The system dynamically adjusts the level of information sharing based on driving context. During normal driving, only essential position information is exchanged, but during overtaking or lane change scenarios, more detailed future driving schedule information is shared, optimizing the balance between assistance effectiveness and system complexity
2Reliability
If agents share detailed future driving schedule information, then driving safety improves, but information transmission complexity increases
Solution Approach 1:
The system extracts only the essential future driving schedule information needed for safety-critical maneuvers such as overtaking and lane changes, rather than transmitting complete driving data. This extraction approach maintains driving safety while minimizing information transmission overhead
Solution Approach 2:
Different levels of information detail are provided based on local driving contexts. During overtaking or lane change operations, detailed future driving schedule information is shared, while during normal driving, simplified position information suffices, optimizing the balance between safety and transmission efficiency
3Object-affected harmful factors
If agents cooperate to provide driving assistance information, then collision prevention improves, but communication requirements increase
Solution Approach 1:
Agents perform preliminary analysis of driving tendencies and estimate future driving schedules before collision-risk scenarios develop. This preliminary cooperation allows drivers to take preventive actions earlier, reducing collision risk without requiring complex real-time communication during critical moments
Solution Approach 2:
The system uses standardized information formats and protocols as intermediaries to facilitate agent cooperation. By mediating the exchange of driving schedule information through defined interfaces, the system reduces communication complexity while maintaining effective collision prevention capabilities
Data Source
AI summary
A cooperation method between agents includes allowing a first agent installed on a first vehicle and a second agent installed on a second vehicle to cooperate with each other, specifying first information regarding future driving of a first driver aboard the first vehicle, by the first agent, acquiring the first information, by the second agent, and notifying a second driver aboard the second vehicle of first driving assistance information derived based on the first information.