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EN
A substantial part of the environmental issues relies on fossil fuels. This dependence is crucial in transport even though many incentives and interventions have been proposed to reduce pollutant emissions. Electric vehicles with zero emissions might represent a viable solution in urban areas. Many cities encouraged modal shift policies from cars to an e-bike or car-sharing/pooling with electric vehicle fleets. This paper reports the ongoing outputs from a pilot project, relying on a modal shift to the e-bike, promoted in the city of Messina (Southern Italy) by the Ministry of Ecological Transition. The objective is to assess, in the territorial context of Messina, the e-bike as a competitive transport mode in terms of social awareness of eco-friendly mobility solutions. The available dataset consists of about nine months of observations; data on total distance and trips have been gathered for each e-bike. It emerged how, in a typical working day, the average distance travelled is about 6.9 km, the usage rate for working days is about 81 %, and the carbon dioxide reduction is about 245 kg per person each year. During the project, information was also collected on the satisfaction with the e-bike and the quality of travel. It emerged that regular bicycle use has good repercussions on the interviewees' psycho-physical well-being, reducing the stress factor connected with urban mobility. Despite mechanical breakdowns and the lack of an infrastructure dedicated to active mobility representing a limitation, travel comfort and safety are two latent variables that are transver-sally valid within the population; about 15 % became familiar with the e-bike and made it their primary mode choice for everyday activities. In this sense, outputs represent a starting point for future policies and give back adjustments before introducing similar services to students from the university and second-grade schools.
EN
Traditional and innovative on-demand transport services, such as taxi, car sharing or dial-a-ride respectively, can provide a level of flexibility to the public transport with the aim to guarantee a better service and to reduce the exploitation costs. In this context, in order to point out the key-factors of on-demand services, this study focuses on traditional on-demand service (such as taxi one), and presents the results of a demand analysis and modelling, obtained processing taxi floating car data (FCD) available for the city of Rome. The GPS position of each taxi is logged every few seconds and it was possible to build a monthly database of historical GPS traces through around 27 thousands of GPS positions recorded per day (more than 750 thousands for the entire month). Further, the patterns of within-day and day-to-day service demand are investigated, considering the origin, the destination and other characteristics of the trips (e.g. travel time). The time-based requests for taxi service were obtained and used to analyse the trip distribution in space and on time. These analyses allow us to forecast trips generated/attracted by each zone within the cities according to land use characteristics and time slices. Therefore, a regression tree analysis was developed and different regressive model specifications with different set of attributes (e.g. number of subway stations, number of zonal employees, population) were tested in order to assess their contribution on describing such a service use.
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