Systems Simulation and Control Laboratory, Department of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
In this paper, vehicle’s fuel consumption and exhaust emissions are investigated in different
driving conditions based on driving segments clustering. Driving data collection is performed using global positioning systems in real traffic conditions. The driving data is clustered into five groups using k-means clustering technique. Vehicle’s fuel consumption and exhaust emissions (i.e. HC, NOx and CO) are investigated in different driving conditions using computer simulations. The relationship between driving features and vehicle’s fuel consumption and exhaust emissions is also presented. According to the simulation results, vehicle’s fuel consumption decreases as average velocity increases from very congested traffic condition to freeway traffic condition. The most HC is produced is low speeds. The results also demonstrate that high accelerations and decelerations cause high amount of NOx. About the CO emission, a moderate driving in
which the velocity and accelerations are not very high or very low, leads to the least amount of CO.