Abstract
Contemporary urban transportation networks are facing challenges to address the growing needs of mobility, all the while improving their economic gains and environmental sustainability. Several studies demonstrate that competitive alternatives to individual private transport are able to address these challenges, such as public transportation services. Thus, the need for optimising their operational efficiency and offer user-centric service delivery arises, with a range of challenges related to the inherent complexity of urban transportation networks as well as the range of dynamic elements involved in such systems. An innovative approach to this problem leverages personal mobile devices in combination with collaborative exchange of information. In this study a system was developed to combine information provided by travellers with data from public transport operators. The result is a rich model of the transportation network that enables the distribution of information in a personalized way and in real-time: the Seamless Mobility solution. Large-scale and expensive infrastructures, such as existing ticketing systems, constitute a threat to such flexibility and traveller access to services. As a result, a distributed architecture was targeted with the goal of integrating personal mobile devices in the infrastructure, with benefits for travellers and transport operators. The proposed solution integrates a broad scope of challenges, including application of secure mobile payments methods, data aggregation from different components and distribution based on relevance techniques. With the implementation of this solution we expect to positively impact the way travellers and transport operators interact, and contribute towards mobility services that are more agile and adequate, taking into account that mobility patterns vary from person to person, seasonally, and even throughout a day. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
This paper proposes an ontology-based approach to visualizing urban mobility data. Our approach, which is in ongoing development, is centered in a visualization-oriented urban mobility ontology that is used to semantically characterize data and visualization techniques. We present a practical application to a public transportation network of the city of Porto, Portugal. We address how semantics can empower and facilitate tasks like automatic recommendation of visualization techniques, and definition of a data filter based on passengers' journey patterns.

Abstract
The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.

Abstract
Urban traffic emissions have been increasing in recent years. To reverse that trend, restrictive traffic measures can be implemented to complement national policies. We have proposed a methodology to assess the impact of three restrictive traffic measures in an urban arterial by using a microsimulation model of traffic and emissions integrated platform. The analysis is extended to some alternative roads and to the overall network area. Traffic restriction measures provided average reductions of 45%, 47%, 35%, and 47% for CO2, CO, NOx, and HC, respectively, due to traffic being diverted to other roads. Nevertheless, increases of 91%, 99%, 55%, and 121% in CO2, CO, NOx, and HC, respectively, can be expected on alternative roads.

Abstract
Eco-routing has been shown as a promising strategy to reduce emissions. However, during peak periods, with limited additional capacity, the eco-friendliness of various routes may change. We have explored this issue empirically by covering about 13,300 km, in three different areas, using GPS-equipped vehicles to record second-by-second vehicle dynamics. This study has confirmed the importance of the eco-routing concept given that the selection of eco-friendly routes can lead to significant emissions savings. Furthermore, these savings are expected to be practically unchanged during the peak period. However, some potential negative externalities may arise from purely dedicated eco-friendly navigation systems.

Abstract
In general, car manufacturers face trade-offs between safety, efficiency and environmental performance when choosing between mass, length, engine power, and fuel efficiency. Moreover, the information available to the consumers makes difficult to assess all these components at once, especially when aiming to compare vehicles across different categories and/or to compare vehicles in the same category but across different model years. The main objective of this research was to develop an integrated tool able to assess vehicle's performance simultaneously for safety and environmental domains, leading to the research output of a Safety, Fuel Efficiency and Green Emissions (SEG) indicator able to evaluate and rank vehicle's performance across those three domains. For this purpose, crash data was gathered in Porto (Portugal) for the period 2006-2010 (N = 1374). The crash database was analyzed and crash severity prediction models were developed using advanced logistic regression models. Following, the methodology for the SEG indicator was established combining the vehicle's safety and the environmental evaluation into an integrated analysis. The obtained results for the SEG indicator do not show any trade-off between vehicle's safety, fuel consumption and emissions. The best performance was achieved for newer gasoline passenger vehicles (<5year) with a smaller engine size (<1400 cm(3)). According to the SEG indicator, a vehicle with these characteristics can be recommended for a safety-conscious profile user, as well as for a user more interested in fuel economy and/or in green performance. On the other hand, for larger engine size vehicles (>2000 cm(3)) the combined score for safety user profile was in average more satisfactory than for vehicles in the smaller engine size group (<1400 cm(3)), which suggests that in general, larger vehicles may offer extra protection. The achieved results demonstrate that the developed SEG integrated methodology can be a helpful tool for consumers to evaluate their vehicle selection through different domains (safety, fuel efficiency and green emissions). Furthermore, SEG indicator allows the comparison of vehicles across different categories and vehicle model years. Hence, this research is intended to support the decision-making process for transportation policy, safety and sustainable mobility, providing insights not only to policy makers, but also for general public guidance.