Smart cities aim to improve the citizens' quality of life by leveraging information about urban scale processes extracted from heterogeneous data sources collected on citywide deployments. The Internet-of-Things (IoT) is, thus, the enabler of smart city technologies at urban scale. In this paper, we present PortoLivingLab, a multisource sensing infrastructure that leverages IoT technology to achieve city-scale sensing of four phenomena: weather, environment, public transport, and people flows. To sense these processes on a city scale, we deployed a vehicular network with over 600 vehicles and 19 static environmental sensors. We also developed an easily reconfigurable crowdsensing platform and carried out several crowdsensing campaigns with more than 600 participants. The data is collected in a common backend and stored using similar spatio-temporal data models to simplify sharing and joint analysis for the characterization of urban dynamics. We describe the architecture and composing elements of PortoLivingLab, highlighting the IoT technologies, and challenges faced. We present several proof-of-concept use cases (e.g., passenger flows from WiFi connections) that provide new insights into different components of an evolving and moving city. Finally, we lay out the future lines of work that will strive for finding hidden phenomena by leveraging data from the three complementary platforms.

Considering that the transport sector is responsible for an increasingly important share of current environmental problems, we look at Intelligent Transportation Systems (ITS) as a feasible means of helping in solving this issue. In particular, we evaluate the impact in terms of Carbon Dioxide (CO₂)emissions of Virtual Traffic Light (VTL), which is a recently proposed infrastructureless traffic control system solely based on Vehicle-to-Vehicle (V2V) communication. Our evaluation uses a real-city scenario in a complex simulation framework, involving microscopic traffic, wireless communication, and emission models. Compared with an approximation of the physical traffic light system deployed in the city, our results show a significant reduction on CO₂ emissions when using VTLs, reaching nearly 20% under high-density traffic.

Road transportation is one of the main sources of greenhouse gas emissions, which lead to global warming and climate change. Promoting the decarbonization of this sector through more efficient and greener mobility is a challenging task that can be achieved by intelligent transportation systems (ITS) enabled by vehicular communications. In this paper, we briefly present how mobility players and enablers (driver, vehicle, and road network) influence energy consumption and pollutant emissions. Furthermore, this survey paper details how different ITS, ranging from eco-routing to intelligent intersection management, can lead to sustainable mobility by promoting a more efficient vehicle usage and enhanced efficiency on road network utilization. Results shown that ITS has the potential to considerably reduce fuel consumption and pollutant emissions, namely, by smoothing the traffic flow, reducing the number of start–stops, and reducing the total travel distance. In addition, we present and analyze two main methods for evaluating green transportation systems: 1) field operational tests; and 2) simulation-based evaluations. We give special emphasis to simulation-based assessment of Green ITS measures by detailing the necessary models and their interactions. Finally, we propose a number of recommendations and future research directions in the area of Green ITS.

Modern societies rely on efficient transportation systems for sustainable mobility. In this paper, we perform a large-scale and empirical evaluation of a dynamic and distributed taxi-sharing system. The novel system takes advantage of nowadays widespread availability of communication and computation to convey a cost-efficient, door-to-door and flexible system, offering a quality of service similar to traditional taxis. The shared taxi service is assessed in a real-city scenario using a highly realistic simulation platform. Simulation results have shown the system's advantages for both passengers and taxi drivers, and that trade-offs need to be considered. Compared with the current taxi operation model, results show a increase of 48% on the average occupancy per traveled kilometer with a full deployment of the taxi-sharing system.

We perform an extensive study of cooperative awareness in vehicular networks based on periodic message exchange. We start by analyzing measurements collected on four test sites across Europe. To measure cooperative awareness, we use three metrics: 1) neighborhood awareness ratio, 2) ratio of neighbors above range, and 3) packet delivery rate. Using the collected data, we define a simple model for calculating neighborhood awareness given a packet delivery ratio for an environment. Finally, we perform realistic large-scale simulations to explore the achievable performance of cooperative awareness under realistic transmit power and transmit rate constraints. Our measurements and simulation results show the following: 1) Above a certain threshold, there is little benefit in increasing the cooperative message rate to improve awareness; higher transmit power and fewer message transmissions are a better approach, since message delivery is dominated by shadowing; 2) The efficacy of cooperative awareness varies greatly in different environments on both large scale (e.g., 90% awareness is achievable up to 200 m in urban compared to 500 m in highway) and small scale (e.g., vehicles in nearby streets can have significantly different awareness levels); 3) Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications have distinct awareness patterns; 4) Each location has distinct transmit power that achieves high awareness; 5) Achieving high awareness levels results in increased reception of potentially unwanted messages; therefore, a balance needs to be found between awareness and interference, depending on the specific context. We hope that our results will serve as a starting point for designing more effective periodic message exchange services for cooperative awareness.

Parking is a major problem of car transportation, with important implications in traffic congestion and urban landscape. Reducing the space needed to park cars has led to the development of fully automated and mechanical parking systems. These systems are, however, limitedly deployed because of their construction and maintenance costs. Leveraging on semi and fully-autonomous vehicular technology, as well as on the electric propulsion paradigm and in vehicular ad hoc networking, we propose a new parking concept where the mobility of parked vehicles is managed by a parking lot controller to create space for cars entering or exiting the parking lot, in a collaborative manner. We show that the space needed to park such vehicles can be reduced to half the space needed with conventional parking lot designs. We also show that the total travelled distance of vehicles in this new parking lot paradigm can be 30% less than in conventional parking lots. Our proposal can have important consequences in parking costs and in urban landscape.