This study uses indicators to evaluate the progress made by Italian cities in the smart mobility sector, in order to understand how these cities have approached the new guidelines imposed by the European Union, and how they have implemented the European changes. Specifically, this study analyses the evolution of public transportation systems, using a sample of twenty-two Italian cities for three successive time periods (2005, 2010, and 2015). The outcomes identified are then linked to funding provided for the implementation of projects related to smart mobility in the cities studied, in order to verify possible correlations between the growth of these services and European and national financial investments. The data analysis shows remarkable progress in the field of sustainable mobility, especially between 2010 and 2015 as well as how this progress is linked to significant financial support that favours the realization of projects related to smart mobility.

Pedestrian infrastructures feature the spaces where every user accesses all the mobility forms: in fact, every movement begins and finishes with a walking section. For this reason, it is very important to pay more attention towards what is said “last mile”, that must be designed and constructed to be easily used from the major part of users, with a special attention to more disadvantage citizens. Among all pedestrian characteristics, the least considered is speed, and when it is considered, the reference is the mean speed, that is the speed of the most likely common user. There are numerous and simultaneous factors that influence pedestrian behavior. The age factor mainly determines the psycho-physical characteristics and therefore the behavior. In the present study, it has been observed the behavior on sidewalks with reference to age. The study is based on a survey carried out in the downtown of Oristano, with a total pedestrian flow of 14,182 users. The purpose is, first, to understand how pedestrian speed varies with age, and subsequently to assess if a statistical model exists to describe the pedestrian behavior by age. After a general analysis of pedestrian behavior, the paper focused on users walking not alone but within a flow. The research considers pedestrian speed in real conditions and not isolated pedestrian speed because a pedestrian, inevitably, interacts with other pedestrians and this provides a particular condition. For this reason, the main analysis is based on a subdataset formed by the 2794 individual pedestrians. The analysis shows that there is not a linear relationship between speed and age, but it is better to consider a polynomial model between the mean individual pedestrian speed, mean walking speed and age class. Results show that speed of individual pedestrians decreases as age increases; younger pedestrians walk faster than others, with a difference of 19.2% respect to older ones. This decrease can be represented by a statistical model. The model also shows that there is not a linear relationship between speed and age, but it is better to consider a polynomial model between the mean individual pedestrian speed, mean walking speed and age class. It is necessary to underline this aspect because many efforts have been made all over the world to promote sustainable mobility. Walking is one of the most important aspect of sustainability, so we will aspect an increase of the number of new walking citizens. But it is necessary to consider how population is growing, with a growing number of senior citizens. It is for these users that we will have to plan in the future. In conclusion, the paper studied the mean individual pedestrian speed and its relationship with age and mean walking speed, finding statistical models able to interpret pedestrian behavior; the choice of the mean individual pedestrian speed as dependent variable is the novelty of the study because analyzes a real condition. In fact, the most common case is that of a pedestrian walking within a flow, and not alone. This is an element distinguishing this study from many others. For this reason, this study can help to improve research in this area and could be useful to understand how to plan and to design pedestrian infrastructures. It would also be important to apply this method to other cities with similar characteristics to verify the real transferability of the model and, consequently, of the results.