V2X Cloud Server Traffic Light Optimization
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Solution Overview
Problem
Existing V2X systems are inefficient in controlling traffic lights, failing to minimize waiting time and schedule delays for vehicles, particularly those that are behind schedule.
Innovation Solution
A method involving a cloud server that receives vehicle status information, filters vehicles not approaching traffic lights, calculates punctuality status using a schedule table, and optimizes traffic light control to prioritize vehicles that are delayed, minimizing overall waiting and schedule delay times by sending traffic light optimization results to vehicles closest to traffic lights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If existing V2X systems control traffic lights without prioritization, then all vehicles are treated equally, but waiting time and schedule delays are not minimized
Solution Approach 1:
The traffic light control system dynamically adjusts signal priorities based on real-time vehicle punctuality status. The cloud server continuously receives vehicle status information, calculates punctuality scores, and updates traffic light optimization strategies accordingly, allowing the system to adapt to changing traffic conditions and vehicle schedules
Solution Approach 2:
The system changes the control parameters of traffic lights based on vehicle punctuality status. By modifying the green light duration and timing parameters for specific vehicles or directions, the system minimizes waiting time for delayed vehicles while maintaining overall traffic flow efficiency
2Productivity
If traffic light optimization is based on comprehensive vehicle status analysis, then waiting time is reduced, but system complexity increases
Solution Approach 1:
The cloud server processes vehicle information in segments by filtering vehicles based on their proximity to traffic lights and punctuality status. Rather than processing all vehicle data uniformly, the system segments vehicles into relevant groups (e.g., delayed vehicles approaching intersections, on-time vehicles, vehicles not affected by current optimizations), reducing computational complexity while maintaining effectiveness
Solution Approach 2:
The cloud server acts as an intermediary between vehicles and traffic light controllers. It receives status information from vehicles, performs optimization calculations, and sends control instructions to traffic lights, thereby centralizing the complex processing logic and shielding the vehicle-traffic light interface from complexity
Data Source
AI summary
In one embodiment, a method of controlling traffic lights in a V2X environment includes the operations of receiving, at a cloud server, status information of a number of vehicles; and filtering out one or more vehicles that are not to encounter a traffic light on their routes in a predetermined distance ahead of the vehicles. The method further includes obtaining a punctuality status of each remaining vehicle according to a schedule table; and optimizing each traffic light in the V2X environment based on the punctuality status of the vehicle to obtain a traffic light optimization result. The cloud server can send the traffic light optimization result to a vehicle closest to each traffic light. The vehicle that receives the traffic light optimization result can relay the result to the traffic light that is closest to the vehicle.