This paper proposes a novel recommendation system which can help commuters make green, safe and less congested travel decisions, while support the society to mitigate the external costs: traffic pollution, congestion and accidents. We have introduced a novel persuasive reward algorithm, which can be used by other researchers to balance between two conflict parties. This study has demonstrated, for the first time, that agent-based model has been used to evaluate the persuasiveness of recommendation systems. The result of the proposed system shows higher public-friendly score in comparison to the conventional approach. The simulation can capture the evolution of the distance of users' ranks when increasing the persuasive level.