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Deterministic and low end-to-end latency communication is an urgent demand for many safety-critical applications such as autonomous vehicles and automated industries. The time-sensitive network (TSN) is introduced as Ethernet-based amendments in IEEE 802.1 TSN standards to support time-triggered (TT) traffic in these applications. In the presence of TT flows, TSN is designed to integrate Audio/Video Bridging (AVB) and Best Effort (BE) traffic types. Although AVB traffic has a lower priority than TT, it still requires low and deterministic latency performance, which may not be guaranteed under strict predefined TT scheduling constraints. For this reason, a window-overlapping scheduling algorithm is recently proposed in different works as analytical forms for TT latency under overlapping-windows based. But worst-case AVB latency evaluation under overlapped TT windows is also essential for critical optimizations and tradeoffs. In this paper, a worst-case end-to-end delay (<italic>WCD</italic>) for AVB traffic under overlapping-based TT windows (AVB-OBTTW) algorithm is proposed. Separate analytical models are derived using the network calculus (NC) approach for AVB-OBTTW with both non-preemption and preemption mechanisms. Using an actual vehicular use case, the proposed models are evaluated with back-to-back and porosity configurations under light and heavy loading scenarios. For specific AVB credit bounds, a clear <italic>WCD</italic> reduction has been achieved by increasing the overlapping ratio (<italic>OR</italic>), especially under back-to-back configuration. Preemption and non-preemption modes are compared under different loading conditions, resulting in lower <italic>WCD</italic>s using preemption mode than non-preemption, especially with porosity style. Compared to the latest related works, AVB-OBTTW reduces <italic>WCD</italic> bounds and increases unscheduled bandwidth, leading to the highest enhancements with the maximum allowable <italic>OR</italic>.

Worst-Case Latency Analysis for AVB Traffic Under Overlapping-Based Time-Triggered Windows in Time-Sensitive Networks