Intelligent scheduling for in-car notifications

Jonathan Wright, Quentin Stafford-Fraser, Marwa Mahmoud, Peter Robinson
Proc. IEEE RTSI 2017
The process of driving a car involves a cognitive load that varies over time. Additional load comes from secondary factors not directly associated with the driving process, including navigation devices, entertainment systems and the car's own warnings. In this paper, we present a framework for intelligent scheduling of in-car notifications based on the driver's estimated cognitive load. As the single channel for communication, it reschedules the notifications using a priority queue, and relays them to the driver based on the urgency of the notification and the overall estimated cognitive load being experienced by the driver at any given moment. We evaluate our system using a dataset collected from a car's CAN bus during multiple on- road trials and show that our proposed approach reduces the number of simultaneous calls on the driver's attention during the driving task. We also demonstrate that our intelligent scheduling significantly reduces the maximum cognitive load experienced by the driver and the frequency with which high loads occur.

Demonstration of Jonathan’s simulator

Available here: PDF