Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies

Kamtam, Sidharth Bhanu; Lu, Qian; Bouali, Faouzi; Haas, Olivier; Birrell, Stewart · 2024 · OpenAlex-citations

DOI: 10.3390/s24123957

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Summary

This systematic review addresses the critical challenge of network latency in the teleoperation of Connected and Autonomous Vehicles (CAVs). As CAVs advance toward higher levels of autonomy, teleoperation serves as a necessary fallback for handling edge cases and ensuring safety. However, the reliability of this remote control loop is heavily dependent on communication quality. The authors identify a gap in existing literature, noting that while previous surveys cover general teleoperation architectures or robotics, few comprehensively analyze latency-specific challenges and mitigation strategies within the CAV domain. The study aims to provide a detailed examination of latency trends, its impact on operator performance and vehicle control, and state-of-the-art compensation methods. The authors conducted a systematic review following PRISMA guidelines, searching multiple academic databases and industry reports for literature published within the last ten years. Approximately 230 papers were initially collected, with about 25% excluded based on relevance criteria. The remaining studies were categorized into topics such as networking, latency mitigation, and industry initiatives, distinguishing between CAV-specific research and broader teleoperation domains. The review synthesizes findings from simulations, theoretical analyses, and empirical studies to evaluate wireless technologies (including 4G, 5G, and WiFi), system architectures, and human factors. Key findings highlight that network latency significantly degrades teleoperation performance by disrupting the real-time transmission of sensory data (uplink) and control commands (downlink). The review establishes specific latency thresholds: constant latency under 170 ms is manageable, while delays between 300 ms and 500 ms become challenging for operators, particularly at slow speeds. Latencies exceeding 700 ms render timely interaction nearly impossible. Variable latency poses an even greater risk than constant delay, leading to operator frustration, increased mental workload, and vehicle instability such as over- or under-steering. The analysis further reveals that while 5G networks offer improved performance, ubiquitous coverage remains unrealistic, necessitating robust mitigation strategies. The paper categorizes these strategies into control latency approaches, perception latency compensation, and network optimization techniques. The significance of this work lies in its comprehensive mapping of the technical and human challenges associated with CAV teleoperation. By detailing the interdependency between network quality-of-service parameters and latency, the review provides actionable insights for engineers and researchers. It underscores the need for advanced mitigation methods, such as time-series prediction and control theory adaptations, to compensate for time-varying delays. Furthermore, the paper highlights ongoing standardization efforts and industry initiatives, offering a roadmap for developing safer, more efficient remote driving systems. This synthesis serves as a foundational resource for integrating teleoperation into the evolving landscape of autonomous transportation, emphasizing that addressing latency is crucial for achieving reliable operational design domains.

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Topics

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• teleoperation remote driving