Cordeiro, JoaoCheang, ThomasMa, Fei ChunFei ChunMa2024-03-252024-03-25201820182018http://library-opac.usj.edu.mo/cgi-bin/koha/opac-detail.pl?biblionumber=174070https://dspace.usj.edu.mo/handle/123456789/4646This thesis introduces, implements and evaluates an innovative concept for assessing driving behavior in public transportation through Mobile Crowd Sensing (MCS), under the field of Advanced Public Transportation System (APTS) - a sub-group of Intelligent Transportation Systems (ITS). Aggressive driving behavior is known to be a cause of avoidable accidents and to increase fuel consumption. In public transportations, it is also a case for costumers� dissatisfaction. Monitoring the quality of driving behavior is a key element to overcome this issue and to improve road safety and customer satisfaction. In this research project, a software application (app) for mobile devices was developed as an experimental tool / proof-of-concept, to monitor aggressive driving behavior in bus drivers, collecting data coming from mobile device�s accelerometer and passengers� qualitative evaluation. The experimental procedure took place in public transportation in Macau (bus only) and consisted of data collection of drivers� aggressive driving behavior using the developed application. The analysis of collected data suggests that MCS is a viable way to assess drivers� behavior in public transportation, thus contributing to the improvement of the service and increase of road safety. Although the methodology has been tailor-made for Macau public transportation, it is believed that the same concept can be applied to other cities, leading them towards the goal of becoming smarter cities. Keywords: driving behavior; mobile crowd sensing; crowdsourcing; smart city; advanced public transportation system; intelligent transportation system; road safety; mobile device accelerometerenUniversity of Saint JosephThesis and Dissertations PhD in Information System (D-IS)Doctoral Dissertation