The Internet of Things (IoT) constantly offers new opportunities and features to monitor and analyze driver behaviour through wide use of smartphones, effective data collection and Big Data analysis. In that framework, the aim of this paper is to investigate the impact of mobile phone use on driving behaviour and road safety through the investigation of driving analytics collected by smartphone sensors. For this purpose, a 100-driver naturalistic experiment was carried out and an innovative data collection scheme using a smartphone application was exploited in order to record the respective driving performance data. Statistical analyses were carried out using linear mixed binary logistic regression models in order to investigate the correlation of mobile phone use with trip characteristics, such as speed, duration, harsh events, etc. Exposure metrics found to be significantly associated with the probability of mobile phone use are total trip distance and driving on workdays and during rush hours. Additionally, the increase of the average speed is found to reduce the probability of mobile phone use while driving.
| ID | pj190 |
| Manuscript | |
| Tags | driver behaviour, driver distraction, naturalistic driving, statistical modelling, telematics |
