Motion Estimation of Connected and Automated Vehicles under Communication Delay and Packet Loss of V2X Communications

Abstract

The emergence of the connected and automated vehicle (CAV) technology enables numerous advanced applications in our transportation system, benefiting our daily travels in terms of safety, mobility, and sustainability. However, vehicular communication technologies such as Dedicated Short-Range Communications (DSRC) or Cellular-Based Vehicle-to-Everything (C-V2X) communications unavoidably introduce issues like communication delay and packet loss, which will downgrade the performances of any CAV applications. In this study, we propose a consensus-based motion estimation methodology to estimate the vehicle motion when the vehicular communication environment is not ideal. This methodology is developed based on the consensus-based feedforward/feedback motion control algorithm, estimating the position and speed of a CAV in the presence of communication delay and packet loss. The simulation study is conducted in a traffic scenario of unsignalized intersections, where CAVs coordinate with each other through V2X communications and cross intersections without any full stop. Game engine-based human-in-the-loop simulation results shows the proposed motion estimation methodology can cap the position estimation error to 0.5 m during periodic packet loss and time-variant communication delay.