Research On Reducing Vehicular CO₂ Emission Algorithms Based On VANET

In recent years,environmental problems such as the greenhouse effect is becoming increasingly serious.The burning of fossil fuels is now one of the main sources of CO2 emissions.However,as the increasing growth of vehicle numbers in the world,vehicular CO2 emissions are considered to be one of the main sources of global warming.CO2 emissions has been a great threat to our survival environment,such as sea level rise,which makes this work became more and more urgent.With the emergence of intelligent traffic system technology,the various countries'government departments,research institutes and industry have apply it to save energy and reduce exhaust emissions,particularly CO2 emissions.The intelligent transportation system can make the driver know the current road conditions in advance,avoid to arrive the intersection during the red light,In order to ensure optimal speed and avoid unnecessary stop,thus reduce fuel consumption and CO2 emissions.This paper reduces the average vehicle's stop number and waiting time and improve the vehicle's passing rate by analyzing and studying the traffic signal controlling.To allocate intersection passage reasonably,we put forward an adaptive traffic control algorithm.Based on the V2I(vehicle-to-infrastructure)and V2V(vehicle-to-vehicle)communications in VANET(vehicular ad-hoc network),we set up a double tube model to detect vehicles' information accurately,and propose an adaptive leaping signal control method via this model.The method allocates appropriate green time for each signal phase according to "demand assignment"principle.Using adaptive control algorithm,traffic control center dynamically adjusts the traffic signal phase and duration time of each lamp.Thus it can avoid "waiting in vain" phenomenon efficiently,and it improves the efficiency of green time.By comparing the experiment,the algorithm improves ride quality at the intersection,at the same time,it effectively reduces the CO2 emissions of the vehicle.By analyzing and studying the effect of the speed on vehicular CO2 emissions,this paper put forward a recommended speed calculation approach.In this scenario,the vehicle's on-board unit can communicate with the traffic lights RSU,therefore the vehicle can be learned that the phase information of traffic before reaching the intersection,so that they can set up and optimize the current speed.We consider the three different kinds of traffic lights,and calculate a recommmended speed.Experimental results show that this recommended speed can effectively reduce the stop ratio of vehicles through the intersection.