Ambient Intelligence on Personal Mobility Assistants for Sustainable Travel Choices

Abstract

An increasing amount of attention is being paid by local public administrations, national and federal governments as well as by international institutions, such as the European Commission, to improve personal mobility within urban environments through the use of public transports. Improving mobility through increased use of public transportation is strategic to reduce energy consumption, to lower emissions and pollution levels, to improve public safety and to dramatically reduce congestions and road traffic. Reducing private transportation clearly brings significant benefits not only to citizens' quality of life and public health but it also results in a more efficient urban system as a whole, with consequent substantial economic benefits at the wider societal level. At the same time, it is difficult to change human habits and people using public transports should have an efficient and user friendly way to access the best travel options suitable for their needs. Based on this assumption, this paper presents a prototype for an ambient intelligent urban personal mobility assistant, i.e. a software for smartphones and tablets which promotes use of public transport by helping user to identify the best travel option across a multi-modal transport network, through a user-friendly interface that intelligently adjusts to user preferences, and behavior.