Potential of fuel-saving and greenhouse gas emission reduction through eco-driving implementation: a case study for motorcycles in Hanoi, Vietnam

Driving behaviour plays a pivotal role in determining a vehicle's fuel consumption (FC) and emission levels, especially in urban traffic conditions. This aims to develop an eco-driving for motorcycles to improve the efficiency of fuel consumption (FC) and air pollution reduction in Hanoi, Vietnam. Based on the acquired on-road operation data, an artificial neural network (ANN) model was developed to estimate the FC of the motorcycle. The developed ANN model was utilised to estimate FC for 100 candidate driving cycles built using the Markov theory and real-world driving data. An eco-driving cycle for Hanoi's motorcycle was selected considering the least amount of consumed fuel. This eco-driving technique could save 22% FC. If the eco-driving technique is implemented for the motorcycle fleet in Hanoi, 452.93 kilotones (kt) CO2eq can be reduced and 145.8 kt of fuel can be saved annually. This means that in the context of the constraints on resources for upgrading transport infrastructure and vehicle technology in developing nations, the eco-driving strategy is an effective and viable method for enhancing transport operations in an environmentally sustainable manner.