Using Deep Q-Network agent to optimize a traffic signal at a single intersection
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Updated
Nov 11, 2023 - Python
Using Deep Q-Network agent to optimize a traffic signal at a single intersection
OpenLendaのPythonでのONNX推論サンプル
An advanced traffic management system (TMS) is a context-aware solution that relies on real-time data from connected road infrastructure and predictive analytics to effectively coordinate traffic across city arteries.
Despite the fact that computer vision is today a highly developed field, capabilities for recognition and classification are not frequently used in day-to-day activities. Therefore, in this project we will make use of the current traffic infrastructure with some additional requirements, to create and demonstrate an advanced traffic light management
build a traffic light with Raspberry Pi (Zero) and Pimoroni Blinkt!
Control a traffic light via HTML using a Raspberry and a 4 channel relay.
Traffic light recognition
RPiP9 把 Raspberry Pi 上常見的模組搜集而成。
Optimize traffic flow at intersections with a Deep Q-Learning agent. Utilizes reinforcement learning to control traffic signals efficiently.
Reinforcement Learning for Traffic Signal Optimization. We significantly reduce travel time compared to existing signal timing methods by training RL agents with omnipresent induction sensor data.
Manage traffic by controlling traffic lights to pass all the cars
In this project, 4 different YOLOv3 models with different accuracy in different FPS values were created in the image processing area. The YOLOv3 models used are YOLOv3-tiny, YOLOv3-320, YOLOv3-416 and YOLOv3-618, respectively.
Detection of the direction of green light arrow(up, right and left).
🚦 Raspberry Pi project to revive an old traffic light
Traffic Light Project: Implementing real-time traffic density calculation and object detection using YOLOv3-tiny. Seeking to enhance car detection accuracy with a curated dataset from Zenodo.
IoT based project to monitor traffic using Raspberry Pi, Pi Camera, RFID MFRC522 Module and GPIO pins.
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