Although driver distraction and in particular the use of mobile phones while driving has been extensively studied over the last decade, mainly due to the ever-increasing use of mobile phones for both speech and other applications (texting, gps, internet etc.) there are specific open issues that the proposed research proposal is called to address. The first concerns the absence of real driving data relevant to mobile phone use, given that the vast majority of existing research is conducted in the ‘safe’ environment of a driving simulator. The second relates to the inability to investigate the influence of mobile phone use on unobserved variables representing broader driving behaviour rather than on individual driving parameters.

In this context, the scope of the proposed research is to analyse the influence of mobile phone use as well as driver and road environment characteristics on driving behaviour and road safety. In order to achieve the above objective, a naturalistic driving experiment will be conducted using large-scale mass data (big data) collected through a mobile phone (smartphone) application. The experimental procedure, which will be carried out with the support of OSeven, which will provide the application and the unprocessed data, is the first of its kind in the world and is expected to be of much greater scientific value and effectiveness than standard experiments because it will analyse a huge amount of real driving data, which until now has not been possible to collect.

For this purpose, 100 drivers will install the OSeven app (available in both IOS and Android software) which records every second of driving specific parameters of driving behaviour, road type and mobile phone usage. The mass data collected will be appropriately processed by developing algorithms in a programming language. Then, a series of different families of statistical analyses will take place which aim to both analyze the influence of mobile phone use and other factors on driving behavior parameters but most importantly to quantify the impact on unobserved variables that best represent general driving behavior.

The benefits of the proposed research will be both scientific and socioeconomic. The scientific benefit relates to the innovations presented by the study in both the collection and processing of mass driving data in real-world conditions and the development and application of complex and innovative statistical methodology for multifaceted analysis of actual driving behavior. The socio-economic benefit concerns measures and information campaigns to address the problem of mobile phone use in driving.