An intelligent traffic light control approach for reducing vehicles CO2 emissions in VANET

Abstract

This paper proposes an intelligent traffic light control scheme to reduce vehicles CO2 emissions based on VANET. Within the proposed scheme, real-time traffic information can be obtained by wireless communication between the vehicles and the traffic lights. The intelligent traffic light control approach can be decomposed into two steps. First, an adaptive traffic light control algorithm is proposed with purpose of reducing vehicles waiting time. We model four different phases, and design the demand function to allot the green light for each phases based on multiple traffic factors such as traffic density etc. In order to decrease vehicles stop times, we then derive recommendatory speed for each individual vehicle. This step is to maximize the throughput of the intersection so that the vehicle stopped by the light can be minimized. In addition, we introduce a CO2 emission-estimation model to calculate vehicles CO2 emissions. Finally, comparing with pre-timed control method, simulation results indicate that the proposed scheme can efficiently reducing vehicle's average waiting time, stop times and CO2 emissions.