Traffic congestion poses a critical challenge to urban transport systems, substantially increasing energy consumption and environmental impacts. This study investigates the mechanisms driving transport energy intensity by linking traffic microdynamics with macroscopic fuel consumption patterns, with particular emphasis on the role of traffic flow destabilization. The research is based on a case study of a complex urban intersection in Szczecin (Poland), integrating field observations, traffic microsimulation using the Eclipse SUMO (Simulation of Urban MObility), and energy modeling based on the HBEFA (Handbook Emission Factors for Road Transport) 4.2 methodology. The study provides empirical evidence that traffic flow destabilization constitutes a primary mechanism driving fuel consumption, independent of traffic volume, with implications transferable to other intersections in terms of underlying processes. Empirical traffic data collected during peak periods were used to calibrate the simulation model, and the resulting dataset was analyzed using a general linear model (GLM) to assess the effects of speed and vehicle type on fuel consumption. The results indicate that vehicle speed is the dominant factor influencing fuel consumption (η2p = 0.60), significantly outweighing the effect of vehicle type (η2p = 0.15). Vehicle speed emerged as the dominant determinant of fuel consumption, while vehicle type had a secondary but statistically significant effect. Results reveal a strong, near-linear relationship between time loss and fuel consumption, indicating that congestion-induced delay is a key proxy for energy intensity. These findings demonstrate that energy consumption is primarily driven by traffic flow instability rather than traffic volume alone, highlighting the potential of traffic management strategies aimed at stabilizing flow conditions, where even minor infrastructural interventions can substantially improve energy efficiency in urban transport systems.
Szaruga et al. (Sun,) studied this question.