Adaptive Traffic Control System

Traffic flow prediction is a key part and core content of intelligent transportation system as well as the important basis for transportation information service, traffic control and guidance. Forecasting timely and accurately is premise of the intelligent transportation system realizing traffic management. Cross-road are the key component of transportation network. To solve this problem of dynamic traffic controlling we are using IoT and data mining techniques. The basic idea is to capture the density of the traffic in a particular lane using image capturing device. Taking this image as an input to the Mat lab we then convert this particular image into a grayscale image where we identify the density of traffic using intensity levels thereby controlling the traffic signals dynamically either by increasing or decreasing the timing of a signal. The objective of our system is to reduce the average waiting time that each vehicle has to wait, before it is allowed to pass, while also enduring uniformity in the waiting times.

Autorentext

Dr. G. Malini Devi, Associate Professor, Computer Science & Engineering from G. Narayanamma Institute of Technology and Science (for women), Hyderabad. She has 21 years of work experience. Author published 28 articles in International Scopus and SCI Journals and attended 12 conferences. She has professional memberships like IEI, IEAE.