End-to-End Latency Measurement Methodology for Connected and Autonomous Vehicle Teleoperation

Abstract

Connected and Autonomous Vehicles (CAVs) continue to evolve rapidly, and system latency remains one of their most critical performance parameters, particularly when vehicles are operated remotely. Existing latency-assessment methodologies focus predominantly on Glass-to-Glass (G2G) latency, defined as the delay between an event occurring in the operational environment, its capture by a camera, and its subsequent display to the remote operator. However, G2G latency accounts for only one component of the total delay experienced by the driver. The complementary component, Motion-to-Motion (M2M) latency, represents the delay between the initiation of a control input by the remote driver and the corresponding physical actuation by the vehicle. Together, M2M and G2G constitute the overall End-to-End (E2E) latency. This paper introduces a measurement framework capable of quantifying M2M, G2G, and E2E latencies using gyroscopes, a phototransistor, and two GPS-synchronized Raspberry Pi 5 units. The system employs low-pass filtering and threshold-based detection to identify steering-wheel motion on both the remote operator and vehicle sides. An interrupt is generated when the phototransistor detects the activation of an LED positioned within the camera's Field Of View (FOV). Initial measurements obtained from our teleoperated prototype vehicle over commercial 4G and 5G networks indicate an average E2E latency of approximately 500 ms (measurement precision +/- 4 ms). The M2M latency contributes up to 60% of this value.