Influence of Human Driver’s Distraction Behavior on Longitudinal Velocity Control of Autonomous Vehicle

It’s commonly difficult for autonomous vehicles (AVs) to detect human driver distraction behaviors, which would lead to probable late preparation for AVs to take brakes in time to avoid rear-end collisions. Hence, in this paper, we aimed to build a connection between AV control and human driver distraction detection, to aid AVs to predict potential risk and avoid distracted drivers like experienced human drivers. First, a practical system framework integrating driver distraction detection, vehicle-to-vehicle communication, and AV velocity control was proposed. Then, an implementation of driver distraction detection based on convolutional neural networks was put forward. Finally, a longitudinal velocity control method considering driver distraction behavior based on model predictive control was posed with persistent feasibility analysis. Simulation results validated the effectiveness of the work in this paper.