학술논문

Adaptive Density-Based Traffic Management System utilizing Ultrasonic Units and RODEM Algorithm
Document Type
Conference
Source
2023 10th International Conference on Signal Processing and Integrated Networks (SPIN) Signal Processing and Integrated Networks (SPIN), 2023 10th International Conference on. :571-577 Mar, 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Costs
Adaptive systems
Roads
Signal processing algorithms
Manuals
Signal processing
Image capture
Traffic management system
Affordable system
RODEM Algorithm
ultrasonic sensor
embedded system networking
Language
ISSN
2688-769X
Abstract
In urban regions, many vehicles are used by people to commute daily; hence, a large amount of traffic can be observed on the roads daily: Managing this traffic is one of the most important responsibilities to avoid accidents, delays, and mishaps and to allow everyone to pass through as safely and quickly as possible. With an increase in the number of vehicles and thus traffic on roads, manual and fixed timing management systems are no longer adequate, prompting the development of camera-based traffic management systems. These systems are based on image capture and analysis to determine real-time traffic on roads and control traffic via traffic lights based on the analysis. Still, they are not scalable to a nation wide region, where our proposed systems enter the picture. In this work, we offer a RODEM-based low-cost, simple, traffic density-based management system that can effectively manage traffic and be installed and maintained on a large scale at a low cost. Our proposed sensing unit weighs significantly less and has a significantly smaller form factor than conventional systems In this work, we further expand on our RODEM algorithm and how our system can effectively address all the challenges mentioned.