Javier Gozalvez

This paper investigates the effectiveness of intent-sharing in enabling maneuver coordination for connected and automated vehicles, demonstrating substantial improvements in two scenarios.

This paper introduces FORESEE, a cooperative lane change model for connected and automated driving that utilizes V2X data to organize vehicles and improve traffic flow, enhancing average vehicle speed and energy efficiency.

This paper investigates the feasibility of using 5G networks for teleoperated driving (ToD) and identifies the impact of bandwidth and TDD frame structure on ToD performance.

This paper proposes a scheme to coordinate 5G and TSN schedulers for supporting deterministic communications with bounded latencies in industrial applications.

This paper proposes a new approach for designing Radio Access Network (RAN) slices in 5G and beyond networks using descriptors that consider both transmission rate and latency requirements to support deterministic aperiodic traffic in industrial critical applications.

This paper analyzes the impact of measurement errors and packet losses in V2X data on the effectiveness of cooperative perception in automated vehicles and identifies challenges related to the generation of ghost vehicles.