Adaptive Traffic Signal Control for Multi-Intersection Flow
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Solution Overview
Problem
Existing traffic light systems are limited in their ability to adjust traffic signals based on real-time vehicle flow dynamics, leading to inefficiencies and congestion, particularly during peak hours, and lack the capability to predict vehicle arrival and adjust signals accordingly to optimize traffic flow across multiple intersections.
Innovation Solution
A system utilizing real-time vehicle data, machine learning models, and graph-based analysis to generate dynamic traffic signal messages that adjust lane speed limits, directions, and signal colors based on vehicle occupancy and flow across a network of traffic signals, incorporating priority vehicles and historical data to optimize traffic flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-programmed timed control is used for traffic lights, then the control system is simple and reliable, but traffic efficiency deteriorates during peak hours due to inability to adapt to real-time traffic conditions
Solution Approach 1:
The patent implements dynamic traffic signal control by transitioning from fixed timed schedules to adaptive signal durations based on real-time vehicle detection. The system continuously monitors traffic flow using sensors and adjusts green light durations dynamically to match actual demand, allowing the control system to be both reliable (consistent operation) and productive (adapted to traffic conditions).
Solution Approach 2:
The system incorporates feedback loops where vehicle detectors monitor traffic flow and provide real-time data to the control unit. This feedback enables the system to adjust signal durations based on actual traffic conditions, resolving the contradiction between simple fixed control and adaptive efficient control by creating a self-regulating system that maintains reliability while improving productivity.
2Productivity
If traffic lights are made to change based on traffic demands using detectors, then traffic efficiency improves, but device complexity increases due to additional sensors and control mechanisms
Solution Approach 1:
The patent employs multi-functional detectors that serve both vehicle detection and traffic flow measurement purposes. The same sensor infrastructure is used for multiple control decisions (signal timing, lane management, priority vehicle detection), reducing overall system complexity while maintaining high traffic efficiency through intelligent use of unified detection data.
Solution Approach 2:
The system merges vehicle detection, traffic flow analysis, and signal control functions into an integrated control unit. By combining these previously separate functions into a single intelligent system, the patent reduces the complexity that would arise from multiple independent systems while maintaining the productivity benefits of demand-responsive control.
3Ease of operation
If traditional fixed-direction traffic signals are used, then the display system is simple, but adaptability deteriorates when lane directions need to change based on traffic patterns
Solution Approach 1:
The patent implements dynamic lane direction assignment where the function of each physical lane can change based on real-time traffic conditions. The control system can dynamically assign lanes for different directions (e.g., converting a right-turn lane to through-traffic lane) and communicate these changes to drivers via variable message signs, maintaining operational simplicity while achieving high adaptability.
Solution Approach 2:
The system adds the dimension of temporal variability to lane functions. Instead of fixed spatial assignments, lanes can assume different functional roles at different times. This is achieved through variable message signs that provide directional information and coordinated signal control that treats lane assignment as a time-varying parameter rather than a fixed constraint.
4Measurement precision
If traffic control focuses on individual intersections independently, then each signal can be optimized locally, but overall network efficiency deteriorates due to lack of coordination between consecutive traffic lights
Solution Approach 1:
The patent merges control of multiple consecutive intersections into a coordinated green wave system. The central control unit synchronizes signal timing across the network based on detected traffic flow patterns, creating coordinated green corridors that maintain local optimization while achieving network-wide efficiency improvements through inter-signal coordination.
Solution Approach 2:
The system performs preliminary actions by detecting traffic buildup at upstream intersections and pre-adjusting downstream signals to create green waves. When vehicles are detected approaching an intersection, the system anticipates their arrival and prepares subsequent signals to be green, reducing wait times and improving network efficiency while maintaining precise local control.
Data Source
AI summary
A method for managing operation of a traffic signal terminal based on traffic flow of vehicles in the proximity of the traffic signal terminal includes obtaining real-time vehicle data from a vehicle detection sensor unit. The method also includes determining, based on the real-time vehicle data, lane data associated with each traffic signal terminal of a set of traffic signal terminals. The method also includes obtaining, from a data storage system, traffic flow data that is indicative of traffic flow between the traffic signal terminals at various time intervals. The method also includes generating a first traffic signal message based on the lane data and the traffic flow data. The method also includes transmitting the first traffic signal message to the first traffic signal terminal to cause the first traffic signal terminal to display the first traffic signal message.