Priority Based Traffic Signal System using Google Maps

International Journal of Electronics and Communication Engineering

© 2020 by SSRG - IJECE Journal

Volume 7 Issue 1

Year of Publication : 2020

Authors : Abhishek Sachan, Kushal Khanna, Shobhit Srivastava, Prof.A.B. Patil

10.14445/23488549/IJECE-V7I1P104

How to Cite?

Abhishek Sachan, Kushal Khanna, Shobhit Srivastava, Prof.A.B. Patil, "Priority Based Traffic Signal System using Google Maps," SSRG International Journal of Electronics and Communication Engineering, vol. 7,  no. 1, pp. 20-23, 2020. Crossref, https://doi.org/10.14445/23488549/IJECE-V7I1P104

Abstract:

In modern life, we have to face many problems: traffic congestion and it is becoming more serious day after day. The major cause leading to traffic congestion is the high number of vehicles caused by the population and the development of the economy. Traffic congestion is a condition on road networks that occurs as use increases and is characterized by slower speeds, longer trip times, and increased vehicular queuing. Nowadays, traffic lights mostly operate on fixed cycles in developing countries or are manually controlled by traffic inspect two or three times a day according to congestion characteristics. These manual and fixed solutions aim to sort out road sections with low traffic flows, but, for the major sections, such solutions are not effective due to short temporal and spatial congestion changes. We are using wi-fi enabled WeMos D1, an ESP 8266 module for transmission and reception of the data. This WeMos is interfaced with the Telegram bot to communicate to the system, and an API key is obtained via the Google Cloud Platform. Here, the latitudes and longitudes are put as a command in the telegram bots, which allow us to know the congestion and the traffic adjustments needed in a region. The traffic congestion levels then decide the time allocated to a particular direction at a traffic signal.

Keywords:

API: Application Program Interface
IR Sensor: Infrared Sensor
PIR Sensor: Passive Infrared Sensor
IDE: Integrated Development Environment

References:

[1] DESIGN AND IMPLEMENTATION OF A DENSITY-BASED TRAFFIC LIGHT CONTROL WITH SURVEILLANCE SYSTEM: Y. N. Udoakah and I. G. Okure, DEPT. OF ELECTRICAL/ELECTRONICS & COMPUTER ENGR’, UNIVERSITY OF UYO, UYO, AKWA IBOM STATE. NIGERIA
[2] Density Based Traffic Control System Using Image Processing: Uthara E. Prakash, Athira Thankappan, Vishnupriya K. T., Arun A. Balakrishnan Department of Electronics Cochin University of Science and Technology, India
[3] Traffic Density-Based Light Control System: Inam Ullah Khan, Muhammad Umar Khan, Hafiz Muhammad Salman, Syed Bilal Hussain Shah
[4] Density Based Traffic Light System: Sayan Ghosh, Shaurya Kumar, Gautam Ghosh
[5] Research on Google map algorithm and implementation: J. Cui, X. Wang
[6] Creating a Bot using the Telegram Bot API: Satish Manohar Talim
[7] Google timeline accuracy assessment and error prediction: Andrea Macarulla Rodriguez, Christian Tiberius, Roel van Bree, Zeno Geradts.
[8] S.Jayadharshan, R.M.Barath, Mr.P.Selvaprasanthm.E, "Mapping of Tourism Place in Puducherry using GIS" SSRG International Journal of Civil Engineering 5.6 (2018): 17-23.
[9] Akshay A. Adsod , Prof. Nitin R. Chopde. "A Review on: Web Mining Techniques", International Journal of Engineering Trends and Technology (IJETT), V10(3),108-113 April 2014.
[10] Nandish M S , Mr. Chetan Balaji , Prof. Shantala C P. "An Outdoor Navigation With Voice Recognition Security Application For Visually Impaired People", International Journal of Engineering Trends and Technology (IJETT), V10(10),500-504 April 2014.