16-Civ-B7 Transportation Planning and Engineering · December 2018
Question 2 of 7: Deterministic Queueing at a Single-Lane Bottleneck
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
Notes on this paper
Paper format. National Examination, December 2018 — 16-Civ-B7,
Transportation Planning & Engineering. Three hours. Closed book; one 8.5 in × 11 in
aid sheet hand-written on both sides is permitted, plus an approved Casio or Sharp
calculator. Seven questions, all of equal value (20 marks); any five constitute a
complete examination and only the first five that appear in the answer book are
marked. All seven are solved here, because the set is a study resource.
Ortúzar, J. de D. & Willumsen, L.G., Modelling Transport, 4th ed. —
Ch. 4 (trip generation), Ch. 5 (gravity/distribution), Ch. 7 (discrete choice and
the IIA property), Ch. 10–11 (equilibrium assignment).
Meyer, M.D. & Miller, E.J., Urban Transportation Planning: A Decision-Oriented
Approach, 2nd ed. — land use / transport interaction and travel-demand
management.
Transportation Research Board, Highway Capacity Manual, 6th ed. —
capacity adjustment factors and level-of-service criteria.
Transportation Association of Canada, Geometric Design Guide for Canadian Roads
— Canadian capacity and design practice.
Question 2: Deterministic Queueing at a Single-Lane Bottleneck (20 marks)
Find. The cumulative arrival and departure diagram to the instant the
queue clears; the maximum queue length and the maximum time any vehicle waits; and the
total and average delay accumulated over the whole congested period.
Cumulative arrival and departure curves for the one-lane bottleneck. The vertical gap between the curves is the queue length at that instant, the horizontal gap is the delay of the vehicle at that cumulative position, and the shaded area between them is the total delay.
Approach. Treat the bottleneck as a deterministic D/D/1 queue: build the
cumulative arrival curve A(t) and the cumulative departure curve D(t), then read the
queue as the vertical gap, the individual delay as the horizontal gap, and the total delay
as the enclosed area.
Part (a) — establish that a queue forms and when it ends.
Measure time t in hours after 9:00 a.m. During the first period the arrival rate
exceeds the capacity, so the bottleneck is oversaturated and a queue grows at
λ1 − μ = 1500 − 1250 = 250 veh/h. After 11:00 a.m. the
arrival rate falls below capacity, so the queue discharges at
μ − λ2 = 1250 − 750 = 500 veh/h. A queue therefore builds
for exactly two hours and then drains.
Write the two cumulative curves. The arrival curve is piecewise linear
and the departure curve runs at capacity for as long as a queue exists:
$$A(t)=\begin{cases}1500\,t, & 0 \le t \le 2\\ 3000+750\,(t-2), & t > 2\end{cases}$$
while the departure curve runs at capacity for as long as a
queue is present,
$$D(t)=1250\,t$$
Both are measured in vehicles, with t in hours after 9:00 a.m.
Locate the instant the queue clears. The queue vanishes where the two
cumulative curves meet, A(t) = D(t):
$$3000+750\,(t-2)=1250\,t \;\Longrightarrow\; 1500=500\,t \;\Longrightarrow\;
\boxed{t_c = 3.0\ \text{h, i.e. 12:00 noon}}$$
The root lies in the interval t > 2 over which the second branch of A(t) is
valid, so it is admissible — a check worth making, because equating the curves on the
wrong branch is the standard error on this question.
Part (b) — maximum queue length. The vertical gap
Q(t) = A(t) − D(t) grows at 250 veh/h until 11:00 and shrinks thereafter, so it peaks
exactly at the break point t = 2 h:
$$Q_{max}=A(2)-D(2)=3000-2500=\boxed{500\ \text{vehicles}}$$
Note that the peak is at the rate crossover, not at the end of the analysis
period.
Maximum waiting time. Under first-in-first-out the delay of an
individual vehicle is the horizontal gap between the curves at that vehicle's cumulative
position. The worst-off vehicle is the last one to arrive during the build-up, number
n = A(2) = 3,000, which arrives at t = 2.0 h and is served when the
departure curve reaches 3,000 vehicles:
$$t_{depart}=\frac{3000}{1250}=2.40\ \text{h}
\;\Longrightarrow\;
w_{max}=2.40-2.00=0.40\ \text{h}=\boxed{24\ \text{minutes}}$$
Every earlier vehicle waits less because it joined a shorter queue, and every later one
waits less because the queue is by then draining, so 24 min is the maximum.
Part (c)(1) — total vehicle delay. The total delay is the area
between the two cumulative curves. That area is a triangle on each side of the peak, with a
common height equal to the maximum queue:
$$D_{total}=\tfrac12\,(2.0)(500)+\tfrac12\,(1.0)(500)=500+250=\boxed{750\ \text{veh}\cdot\text{h}}$$
Equivalently, one may integrate A(t) − D(t) from 0 to 3 h; the numerical integral
returns the same 750 veh·h, which is a useful independent check.
Part (c)(2) — average delay per vehicle. The delay is shared
among every vehicle that arrives during the congested period. That count is
1500(2.0) + 750(1.0) = 3,750 vehicles, which agrees with the departures
μtc = 1250(3.0) = 3,750 — the curves must close at the clearance
instant, so this is a free arithmetic check.
$$\bar d=\frac{D_{total}}{N}=\frac{750}{3750}=0.20\ \text{h}=\boxed{12\ \text{minutes per vehicle}}$$
For interpretation: a mean delay of 12 min (720 s) is more than eight times the 80 s/veh
control-delay threshold that defines level of service F at a signalised intersection, so
this bottleneck is severely oversaturated for three hours and the 24-minute worst-case wait
is what drivers will actually report. Note also the two spare capacities are unequal —
the lane is 250 veh/h short during the peak but has 500 veh/h of surplus afterwards —
which is why the recovery takes only half as long as the build-up.