Towards safer texting while driving through stop time prediction

Driver distraction due to in-vehicle device use is an increasing concern and has led to national attention. We ask whether it is not more effective to channel the drivers' device and information system use into safer periods, rather than attempt a complete prohibition of mobile device use. This paper aims to start the discussion by examining the feasibility of automatically identifying safer periods for operating mobile devices. We propose a movement-based architecture design to identify relatively safe periods, estimate the duration and safety level of each period, and delay notifications until a safer period arrives. To further explore the feasibility of such a system architecture, we design and implement a prediction algorithm for one safe period, long traffic signal stops, that relies on crowd sourced position data. Simulations and experimental evaluation show that the system can achieve a low prediction error and its converge and prediction accuracy increase proportionally to the availability of the amount of crowd-sourced data.