Driving Through the Network: Performance and Workload Under Latency and Video Impairment

TL;DR

This study investigates how network latency and video quality affect teleoperation performance and workload in automated vehicles using a driving simulator with various network conditions.

Contribution

It provides empirical data on the independent and combined effects of latency and bitrate on operator workload and performance, highlighting physiological measures for overload detection.

Findings

Latency and bitrate increase operator load and affect performance.

Physiological measures show sub-additive interactions between latency and bitrate.

300 ms latency with 2000 kbit/s bitrate is velocity-equivalent to optimal conditions.

Abstract

Teleoperation promises to extend the operational envelope of automated vehicles, yet it critically depends on network latency and video quality. We report a fixed-base driving-simulator study (N=25) with a 2x2 manipulation of added latency (100/300 ms) and bitrate (500/2000 kbit/s), plus a best-case baseline (0 ms added, 9000 kbit/s). We measured effective glass-to-glass (G2G) latency per condition (baseline approx. 413 ms; effective totals approx. 500-700 ms) and verified stable framerate and encoder settings. Multimodal measures covered performance (speed, steering reversals, crashes), oculomotor behavior (blink rate, fixation duration), physiology (RR interval, heart rate, skin conductance), and subjective workload. Latency and bitrate each increased operator load and modestly affected performance. Physiological measures (heart rate, RR interval) exhibited sub-additive interactions, whereas performance and oculomotor interactions were small or non-significant. Equivalence tests showed that 300 ms with 2000 kbit/s was velocity-equivalent to best-case (SESOI +/- 2 km/h), while 300 ms with 500 kbit/s was not. We argue that latency and video quality should be treated as largely independent design levers, and that physiology-aware adaptation can anticipate overload before safety is compromised.