Influence-Based Traffic Rule Control Server for Vehicle Groups
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Solution Overview
Problem
Existing traffic networks with communication systems for groups of vehicles lack efficiency in managing traffic rules to minimize the impact of high-influence groups stopping, leading to increased network disruption.
Innovation Solution
A server calculates the influence degree of vehicle groups based on predicted moving body information and transmits control signals to traffic rule display devices to ensure groups with higher influence can continue traveling, thereby reducing network disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the server applies uniform traffic rules to all vehicle groups, then the traffic rule display device operation is simple, but the traffic network efficiency deteriorates due to inability to prioritize high-influence groups
Solution Approach 1:
The server calculates influence degrees for different vehicle groups and applies differentiated traffic rule control based on these calculated values. High-influence groups receive prioritized treatment compared to low-influence groups, enabling localized quality differentiation in traffic management rather than uniform treatment.
Solution Approach 2:
The system introduces an influence degree parameter to quantify and compare different vehicle groups. By changing the control parameter from simple group identification to influence-degree-based prioritization, the system achieves more efficient traffic network management while maintaining relatively simple display device operation.
2Productivity
If the server calculates and prioritizes high-influence groups, then the traffic network efficiency improves, but the system complexity increases due to influence degree calculation requirements
Solution Approach 1:
The server performs preliminary calculation of influence degrees for vehicle groups before applying traffic control. By pre-calculating and storing these influence values, the system simplifies subsequent real-time decision-making at the traffic rule display device, reducing operational complexity despite the additional calculation step.
Solution Approach 2:
The influence degree serves as an intermediary parameter between the complex reality of vehicle group dynamics and the simplified traffic control decisions. This intermediary abstraction allows the system to handle complex traffic scenarios without requiring complex real-time calculations at the control device.
3Ease of operation
If the server stops all vehicle groups at the traffic signal, then the traffic rule display device operates simply, but the harmful factors increase due to disruption of high-influence group travel
Solution Approach 1:
The traffic rule display device dynamically adjusts its operation based on the calculated influence degrees of different vehicle groups. Instead of static uniform stopping, the system implements dynamic control that allows high-influence groups to continue traveling while stopping low-influence groups, reducing harmful disruptions.
Solution Approach 2:
The system converts the potentially harmful effect of stopping all vehicles into a beneficial selective stopping approach. By using influence degree calculations, the system transforms what would be uniform disruption into targeted control, allowing essential travel to continue while managing traffic flow.
Data Source
AI summary
The server refers to the predicted moving body information to identify the first group and the second group. The server calculates the influence degree for each group. The server calculates a display state of the traffic rule display device in which the highly influence degree group among the first group and the second group can continue traveling. The server transmits the calculated request to be in the display state.