Intersection Video Traffic Signal Control for Low-Volume Flow

The patent replaces conventional mechanical/sensor-based traffic signal control with a computer vision-based system that uses cameras to detect vehicles and pedestrians. The system processes image data through detection algorithms to determine traffic volume and dynamically adjusts signal timing, thereby improving traffic flow efficiency while managing system complexity through automated decision-making.

The traffic signal control system autonomously monitors traffic conditions by analyzing video feeds, determines when signal changes are needed based on detected traffic volume, and automatically adjusts signal timing without requiring complex manual control mechanisms. This self-service approach improves productivity by eliminating unnecessary waiting times while keeping the control logic relatively simple.

The system continuously captures video data of the intersection, detects the number of vehicles and pedestrians, and uses this feedback information to dynamically adjust traffic signal timing. When traffic volume is detected to be below a threshold, the system automatically extends green light duration or adjusts signal timing to reduce waiting times, enabling real-time adaptation to traffic fluctuations while maintaining ease of operation through automated control.

The traffic signal control system transitions from a static fixed schedule to a dynamic control mechanism that adjusts signal timing in real-time based on detected traffic conditions. The system modifies green light duration and signal changes according to the number of detected vehicles and pedestrians, thereby improving adaptability to real-time traffic fluctuations while keeping the user interface simple and easy to operate.

The patent replaces simple sensor input with a computer vision-based system that uses cameras to capture and analyze intersection conditions. The system processes image data through detection algorithms to identify vehicles and pedestrians, calculate traffic volume, and dynamically adjust signal timing. This substitution improves traffic flow efficiency by providing more comprehensive real-time data while managing device complexity through automated processing.

The system uses a single camera-based imaging device to perform multiple functions: detecting vehicles, detecting pedestrians, calculating traffic volume, and triggering signal changes. This multi-functional approach improves traffic flow efficiency by consolidating data collection into a single system while managing overall complexity through integrated processing rather than multiple separate sensors.