Queue Length Calculator

Estimate average queue length and waiting times using FHWA signal timing planning formulas, M/M/1 exponential service, or M/D/1 deterministic service models.

Use the Queue Length Calculator

Queue Parameters

Calculation Results

Enter parameters and click Calculate

Model Relationships & Governing Equations

FHWA Signal Timing Manual (Chapter 3) Planning Expressions:

c = s × (g / C)
X = v / c (degree of saturation)
Qavg = v × (C − g) / 3600  [veh/lane]
Q95 ≈ 2 × Qavg  (screening approximation)

Valid for undersaturated flow (X < 1.0) with Poisson/random arrivals. Back-of-queue and incremental delay require full HCM procedures.

Summary

This calculator provides planning-level queue estimates for both transportation and operations engineering. For traffic signals, it computes undersaturated average red-phase queue per lane using the FHWA Traffic Signal Timing Manual formula (Equation 3-5) and displays an approximate Q95 screening estimate. For analytical service points, it computes utilization (ρ), queue length (Lq), total in system (L), queue waiting time (Wq), and total time (W) under M/M/1 (exponential service) or M/D/1 (deterministic service) queuing models.

How it works

  1. Select the operational model: FHWA Traffic Signal (planning level), M/M/1 (exponential service), or M/D/1 (deterministic service).
  2. For traffic signals, enter hourly flow per lane, saturation flow rate, cycle length, and effective green time.
  3. For service queues, enter arrival rate (λ) and service rate (μ), selecting per-minute or per-hour time units.
  4. The calculator verifies stability limits (v/c < 1.0 or ρ < 1.0) and evaluates closed-form queue length and delay expressions.
  5. Results display average queue length, wait times, capacity utilization, and model-specific planning cautions.

Use cases

  • Perform planning-level screening of signalized intersection queue lengths per lane.
  • Estimate a 95th-percentile screening queue for initial signal timing reviews.
  • Model single-server customer lines with random service times (e.g., tech support, retail checkouts).
  • Model single-server queues with constant service duration (e.g., automated car wash, automated toll booths).
  • Compare wait times and line lengths between exponential and deterministic service distributions.

Frequently Asked Questions

Last updated: 2026-09-17 · Reviewed by Nham Vu