This paper is published in Volume-7, Issue-4, 2021
Area
Traffic Management Systems
Author
Soham Bhure, Ritvik Patil, Sanket Umredkar
Org/Univ
Vishwakarma Institute of Technology, Pune, Maharashtra, India
Pub. Date
20 July, 2021
Paper ID
V7I4-1365
Publisher
Keywords
Traffic Density, Traffic Flow, Traffic API, Traffic Congestion, Equity, Optimization

Citationsacebook

IEEE
Soham Bhure, Ritvik Patil, Sanket Umredkar. Adaptive traffic management system using traffic API, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Soham Bhure, Ritvik Patil, Sanket Umredkar (2021). Adaptive traffic management system using traffic API. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Soham Bhure, Ritvik Patil, Sanket Umredkar. "Adaptive traffic management system using traffic API." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

Traffic congestion is rising in cities around the world. Contributing factors include expanding urban population, aging infrastructure, inefficient and uncoordinated traffic signal timings. According to researchers, Signal Timer issues (like out-of-sync timers) are at the top causing factors of traffic congestion along with a disproportionate number of vehicles and road-work/accidents. The purpose of this article is to illustrate one of the possible solutions to increase the efficiency of existing traffic signals by optimizing signal timings with the help of real-time traffic data using a traffic API. The proposed solution is bolstered by a mathematical equation that follows the principle of equity.