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

Road safety builds on traffic and driver–infrastructure interaction: nighttime visibility represents a key-aspect of this complex interaction. Therefore, providing an adequate road lighting system and improving drivers’ visibility in nighttime conditions is vital. In this sense, photoluminescent paints for pavements can improve road safety in terms of visibility. This study models photoluminescent phenomenon by referring to dense-graded friction courses (DGFC) and open-graded friction courses (OGFC), and evaluates the effects due to season. Measurements, based on the photometry technique, were carried out in the laboratory on cores. The photoluminescent phenomenon was investigated in terms of charge and discharge time linked to decay phenomena and modeled as a function of pavement type and paint treatments. Results show that photoluminescent performance depends on the luminance time and volumetric characteristics of bituminous mixtures. Results can benefit both researchers and practitioners and can allow optimizing painting treatments for different bituminous mixtures.