The Effect of Driver Behavior on Energy Consumption Using a Microscopic Traffic Model

Driver behavior significantly affects vehicle energy consumption and emissions which are critical global concerns. This paper proposes a microscopic traffic model to characterize energy consumption considering the physiological and psychological behavior of a driver. Physiological behavior reflects driver response to traffic conditions while psychological behavior includes driver sensitivity and awareness. Thus, the proposed model encompasses driver response, sensitivity, and awareness. Data was obtained using a sensor node installed at the roadside. Traffic was monitored for six days and the data was modeled using regression analysis. The models and vehicle fuel consumption rate are integrated into the proposed model. The Intelligent Driver (ID) model is based on a constant exponent so driver behavior does not vary with traffic conditions. Thus, fuel consumption is ignored. It is shown that the proposed model results in stable traffic, i.e. traffic returns to a steady state following a disturbance, whereas the ID model produces unstable traffic behavior. Further, it results in smaller fluctuations in speed, flow, and density. Thus, the proposed model can be used to lower fuel consumption and emissions, thereby reducing air pollution and contributing to climate change mitigation.