Litcius/Paper detail

Smart Control of Traffic Light Using Artificial Intelligence

Mihir Gandhi, Devansh S. Solanki, Rutwij S. Daptardar, Nirmala Shinde Baloorkar

202071 citationsDOI

Abstract

Traffic congestion is becoming one of the critical issues with increasing population and automobiles in cities. Traffic jams not only cause extra delay and stress for the drivers, but also increase fuel consumption and air pollution. Although it seems to pervade everywhere, megacities are the ones most affected by it. And its ever-increasing nature makes it necessary to calculate the road traffic density in real-time for better signal control and effective traffic management. The traffic controller is one of the critical factors affecting traffic flow. Therefore, the need for optimizing traffic control to better accommodate this increasing demand arises. Our proposed system aims to utilize live images from the cameras at traffic junctions for traffic density calculation using image processing and AI. It also focuses on the algorithm for switching the traffic lights based on the vehicle density to reduce congestion, thereby providing faster transit to people and reducing pollution.

Topics & Concepts

Traffic congestionFloating car dataFuel efficiencyTraffic flow (computer networking)Computer scienceTraffic congestion reconstruction with Kerner's three-phase theoryTraffic waveTraffic optimizationTraffic bottleneckTraffic conflictMegacityVehicle Information and Communication SystemTransport engineeringReal-time computingEngineeringRoad trafficComputer networkAutomotive engineeringEconomyEconomicsAutonomous Vehicle Technology and SafetyTraffic control and managementTraffic Prediction and Management Techniques