PROJECT TITLE :
A Study on Energy Saving and $hbox_ $ Emission Reduction on Signal Countdown Extension by Vehicular Ad Hoc Networks
Research on the broadcasting of signal countdown messages (SCMs) to vehicles via vehicular unexpected network (VANET) technology has shown that it can reduce emissions and energy consumption; but, past studies have lacked thought of automobile following and vehicle gliding mode. In this paper, 2 green driving suggestion models, namely, the Maximize Throughput Model (MaxTM) and also the Minimize Acceleration and Deceleration Model (MinADM), are proposed to attenuate the emissions by considering real-time traffic info nearby the intersection. The 2 proposed ways are compared with an open traffic light-weight management model (OTLCM) . The main facts this paper demonstrate are that traffic models lack thought of automotive following, which would create the simulation result unrealistic, that the proposed MaxTM can reduce additional emissions than the MinADM and the OTLCM, and the full travel time in the MaxTM is also higher than the opposite two models so that the final traffic performance will be improved. Simulation results show that the performance of emissions of the MaxTM is 5p.c–102% higher than the MinADM and 13%–209% better than the OTLCM within the simulation cases, and the performance of emissions of the MaxTM is eight%–fourteenpercent higher than the MinADM and fifteen%–231% higher than the OTLCM in the real traffic cases.
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