This paper presents a literature review about the application of blockchain-based systems in transportation. The main aim was to identify, through the implementation of a multi-step methodology: current research-trends, main gaps in the literature, and possible future challenges. First, a bibliometric analysis was carried out to obtain a broad overview of the topic of interest. Subsequently, the most influential contributions were analysed in depth, with reference to the following two areas: supply chain and logistics; road traffic management and smart cities. The most important result is that the blockchain technology is still in an early stage, but appears extremely promising, given its possible applications within multiple fields, such as food track and trace, regulatory compliance, smart vehicles’ security, and supply-demand matching. Much effort is still necessary for reaching the maturation stage because several models have been theorized in recent years, but very few have been implemented within real contexts. Moreover, the link blockchain-sustainability was explored, showing that this technology could be the trigger for limiting food waste, reducing exhaust gas emissions, favouring correct urban development, and, in general, improving quality of life.

Traffic safety and energy efficiency of vehicles are strictly related to driver’s behavior. The scientific literature has investigated on some specific dynamic parameters that, among the others, can be used as a measure of unsafe or aggressive driving style such as longitudinal and lateral acceleration of vehicle. Moreover, the use of modern mobile devices (smartphones and tablets), and their internal sensors (GPS receivers, three-axes accelerometers), allows road users to receive real time information and feedback that can be useful to increase awareness of drivers and promote safety. This paper focuses on the development of a prototype mobile application that can evaluate the grade of safety that drivers are keeping on the road by measuring of accelerations (longitudinal and lateral) and warning for users when it can be convenient to correct their driving style. The aggressiveness is evaluated by plotting vehicle’s acceleration on a g-g diagram specially studied and designed, where horizontal and lateral acceleration is displayed inside areas of “Good Driving Style”. Several experimental tests were carried out with different drivers and cars in order to estimate the system accuracy and the usability of the application. This work is part of the wider research project M2M, Mobile to Mobility: Information and communication technology systems for road traffic safety (PON National Operational Program for Research and Competitiveness 2007-2013) which is based on the use of mobile sensor computing systems for giving real-time information in order to reduce risks and to make the transportation system more safe and comfortable.

The monitoring of road surface anomalies, such as potholes, speed bumps etc., has a great importance in order to ensure safety and comfort for all road users, from pedestrian to drivers. The constant mapping of road real conditions also allows adequate infrastructure's maintenance and management operations, together with a consistent allocation of resources. For this reason, informing road users on infrastructure quality and getting information from the same users have become the new frontier of mobile devices applications for driving assistance and navigation (such as a specific social network for safety road). In the light of the above and thanks to the results obtained from previous studies, this paper focuses on the development of a useful automated sensing system for the monitoring of road surface quality.The system is based on the use of a simple application for smartphones that employs two main sensors piggybacked on mobile devices: a GPS receiver for vehicle's localization and a three axis accelerometer to collect acceleration data due to vehicles motion on road anomalies. The information collected during the trip is transferred in real time (1Hz frequency) to a central server where data are processed using automated algorithms for signal analysis. In particular, high-energy events are identified by monitoring and measuring the vertical acceleration impulse. A statistical analysis of experimental data has led to the detection of specific thresholds to which the impulse values are continuously compared. Several experimental tests were carried out for corroborating the approach and to validate the system accuracy. Results exhibited high performance of the system architecture. This study is part of the extensive research project M2M (Mobile to Mobility, PON co-financed by European Regional Development Fund, FESR), that is based on the use of mobile sensor computing systems forgiving real- time information to road users in order to make the transportation system more safe and comfortable

The monitoring of road surface conditions plays a key role in ensuring safety and comfort to the various road users, from pedestrians to drivers. Furthermore, having information on infrastructure quality allows road managers to guarantee an adequate maintenance. These data can be given and used at the same time by users, by means of mobile devices, widespread in Italy and in the World. The main aim of this paper is to realize a simple application, which can be installed on several devices (smartphone/tablet), that allows to use sensors piggybacked on them in order to monitor road surface quality. Experimental tests are carried out on urban roads of Calabria (Italy) to validate and test the mobile application. In particular, the accelerometer is used for detecting surface conditions, in terms of potholes and bumps. The Global Positioning System (GPS) is employed to know in real time the location of vehicles and of road surface anomalies. Five different devices were used, all placed in a test vehicle in three different placement conditions. For the validation process, only one device was used, completely bound in an utilitarian car. The algorithm developed to detect road bumps and potholes is based on the analysis of the acceleration signal in terms of high-energy events; three filters are applied on the original signal. Moreover, verification of the rate of false detections and undetected road anomalies is planned, using georeferenced photos that allow the correct localization on the map and the assessment of the correspondence between the elements, detected with the accelerometer, and real road conditions. The results obtained show that our application could be used as an useful automated sensing system for road quality

Safety performance is evaluated by using measures obtained experimentally from a videotaping of traffic operations at an urban roundabout situated in Cosenza, Italy. Five different expressions of safety performance from the perspective of “rear-end” vehicle interactions include maximum deceleration rate to avoid a crash (DRAC), time-to-collision (TTC), proportion of stopping distance (PSD), time integrated time-to-collision (TIT), and crash potential index (CPI). Differences in safety performance are discussed with respect to the type of measure, traffic conditions, and variations in roundabout geometry. The results of this analysis suggest that safety performance is highly sensitive to the way it is measured; different measures can highlight different locations or geometric features of the roundabout as posing potential safety problems. This study underscores the usefulness of safety performance measures for providing meaningful experimental indicators of potential safety problems at roundabouts and how ...

Urban areas, with their dense populations and complex infrastructures, are increasingly susceptible to various risks, including environmental challenges and infrastructural strain. This paper delves into the transformative potential of digital twins—virtual replicas of physical entities—for mitigating these risks. It specifically explores the role of digital twins in reducing disaster risks, such as those posed by earthquakes and floods, through a comprehensive bibliometric-based literature review. Digital twins could contribute to risk reduction by combining data analytics, simulation, and predictive modeling by creating virtual replicas of physical entities and integrating real-time data streams to better address and manage risks in urban environments. In detail, they can help city planners and decision-makers analyze complex urban systems, simulate potential scenarios, and predict potential outcomes. This proactive approach allows both the identification of vulnerabilities and better implementation of targeted mitigation strategies to enhance urban resilience and sustainability. More informed decisions can be made relying on simulations, and it can also be possible to optimize resource allocation and better respond to emerging challenges. This work reviews the key publications in this domain, with the aim of finding relevant papers that can be useful to urban planners and policy-makers. The paper concludes by discussing the broader implications of these findings and identifying challenges in the widespread adoption of digital twin technology, including data privacy concerns and the need for interdisciplinary collaboration. It also outlines prospective avenues for future research in this emerging field.