Motion Estimation of Connected and Automated Vehicles under Communication Delay and Packet Loss of V2X Communications
Ziran Wang, Kyungtae Han, Prashant Han

TL;DR
This paper presents a consensus-based motion estimation method for connected and automated vehicles that maintains accurate position and speed estimates despite communication delays and packet loss in V2X systems, enhancing safety and coordination.
Contribution
It introduces a novel consensus-based motion estimation approach that effectively compensates for communication issues in V2X-enabled CAVs, improving their reliability in real-world scenarios.
Findings
Position estimation error is capped at 0.5 meters during packet loss.
Method maintains accuracy despite communication delay and packet loss.
Simulation results validate effectiveness in intersection scenarios.
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…
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