LAUSR

Densely populated cities have led to increased traffic congestion and, consequently, increased greenhouse gas emissions from vehicles. Thus, it is important to develop traffic models to overcome congestion and increased air pollution. In the literature, traffic model characterizations rely predominantly on traffic dynamics and ignore traffic emissions. In this study, a new macroscopic model targeting traffic emissions and drivers’ presumption based on traffic emissions is proposed to overcome traffic congestion and pollution. The traffic emissions characterization was based on the CO2 data employed in the second traffic system. For the performance analysis, the results of the proposed and Zhang’s traffic models were compared. The results were obtained using the ROE technique to predict traffic evolution. The scheme was implemented in MATLAB. Compared with Zhang’s traffic model, the suggested traffic model based on emissions reflected traffic behavior more realistically.