Research on the broadcasting of signal countdown messages (SCMs) to vehicles via vehicular ad hoc network (VANET) technology has shown that it can reduce CO2 emissions and energy consumption; however, past studies have lacked consideration of car following and vehicle gliding mode. In this paper, two green driving suggestion models, namely, the Maximize Throughput Model (MaxTM) and the Minimize Acceleration and Deceleration Model (MinADM), are proposed to minimize the CO2 emissions by considering real-time traffic information nearby the intersection. The two proposed strategies are compared with an open traffic light control model (OTLCM). The main facts this paper demonstrate are that traffic models lack consideration of car following, which would make the simulation result unrealistic, that the proposed MaxTM can reduce more CO2 emissions than the MinADM and the OTLCM, and the total travel time in the MaxTM is also better than the other two models so that the general traffic performance can be improved. Simulation results show that the performance of CO2 emissions of the MaxTM is 5%-102% better than the MinADM and 13%-209% better than the OTLCM in the simulation cases, and the performance of CO2 emissions of the MaxTM is 8%-14% better than the MinADM and 15%-231% better than the OTLCM in the real traffic cases.
All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics