CIVL2700 Transport Systems

How CIVL2700 is assessed

What CIVL2700 covers

CIVL2700 Transport Systems runs in two halves, and this twelve-chapter map follows the teaching schedule through both.

Chapters 1–6 cover the planning and demand half — accessibility, traffic assignment and tolling, logit choice, demand forecasting and deterministic queueing — while Chapters 7–12 cover the traffic-engineering half, from the flow–density–speed identity q = k·v and the fundamental diagram to intersection control, signal timing and public transport. Use it to see how each week's model builds toward the comprehensive final.

The University of Sydney frames CIVL2700 around a planning and demand half — accessibility, traffic assignment (User Equilibrium versus System Optimal and congestion tolling), logit mode choice, the four-step demand model, and departure-time and deterministic queueing — and a traffic-engineering half that asks how the road then performs, through stochastic queues, the flow–density–speed identity q = k·v, the fundamental diagram, intersection control, signal timing and public-transport operation.

Transport Systems is a method-and-units subject: the marks live in choosing the right model, substituting with correct SI units, doing one clean calculation and interpreting the result.

The University of Sydney runs CIVL2700 assessment through Canvas as four assignments and two supervised in-class tests across the semester, capped by a comprehensive final worth 40% of the unit that is a hurdle — you must score at least 40% on the final itself to pass.

That structure rewards steady work through STUVAC rather than a last-night cram, and the CIVL2700 result feeds the Weighted Average Mark (WAM) that later University of Sydney transport units build on.

Worked example · free

Triangular fundamental diagram: capacity, congestion wave and a congested state

Key terms

Flow (q)

The rate at which vehicles pass a fixed point, in veh/h (or veh/s). Point definition q = n/T; also q = 1/h̄, the reciprocal of the mean time headway.

Density (k)

The number of vehicles per unit length of road at an instant, in veh/km. Section definition k = n/L; also k = 1/s̄, the reciprocal of the mean spacing.

Space-mean speed (v_s)

The harmonic (travel-time / section) average speed, in km/h. The only speed for which q = k·v is exact: v_s = q/k.

Time-mean speed (v_t)

The arithmetic average of spot speeds measured at a point, in km/h. Always v_t ≥ v_s (the inspection paradox), because a detector over-samples fast vehicles.

q = k·v (fundamental identity)

Flow equals density times space-mean speed — dimensionally veh/km × km/h = veh/h. The backbone relation of the traffic-engineering half of the unit.

Traffic intensity (ρ)

The queueing utilisation ρ = λ/μ, the ratio of arrival rate to service rate. Stable single-server queues require ρ < 1.

Capacity (q_max)

The maximum sustainable flow on a road, reached at the critical density; on a triangular fundamental diagram q_max = v_f·k_c.

Critical density (k_c)

The density at which flow is maximised; below it traffic is free-flowing, above it congested.

Jam density (k_j)

The density at which traffic is bumper-to-bumper and flow falls to zero; the spacing there is the minimum s = 1/k_j.

Congestion-wave speed (w)

The backward speed at which a jam propagates upstream on the congested branch; w = q_max/(k_j − k_c), a positive magnitude with branch slope −w.

User Equilibrium (UE)

Wardrop's first principle: every used route between an origin–destination pair carries equal, minimal travel time, so no traveller can improve by switching.

System Optimal (SO)

Wardrop's second principle: flows that minimise total network travel time. SO total time is always ≤ UE; a congestion toll can shift UE flows to SO.

Saturation flow (s)

The maximum discharge rate of a signalised lane group during effective green, in veh/h; movement capacity is c = s·g/C.

Webster optimum cycle (C_opt)

The cycle length that minimises delay: C_opt = (1.5L + 5)/(1 − Y_c), where L is total lost time and Y_c the sum of critical flow ratios (< 1).

CIVL2700 FAQ

Questions students ask in each CIVL2700 chapter

What is the difference between accessibility and mobility in CIVL2700?

Mobility is the ease of moving — how far and fast you can travel, measured by speed or person-throughput. Accessibility is the ease of reaching the things you want (jobs, schools, shops), measured by how many opportunities lie within a travel-time budget. They can move in opposite directions: a motorway can raise mobility (high speed) while cutting local accessibility if it severs a community, and mixing land uses so destinations are close can raise accessibility without any extra travel. Distinguishing the two is a classic Week 1 short-answer item. Chapter 01 · Introduction to Transport Systems & Accessibility

Is System Optimal always faster for every individual driver than User Equilibrium?

No. SO minimises the total travel time across all vehicles, not each person's time. At the system optimum a few drivers could personally go faster by switching routes — which is exactly why SO is not self-sustaining and needs a toll to hold it in place. UE is the outcome self-interested drivers actually reach; it is never faster in total (TTT(UE) ≥ TTT(SO)), but individuals are, by definition, each on their own shortest route. Chapter 02 · Traffic Assignment: User Equilibrium, System Optimal & Tolling

Why can systematic utility be negative in a logit model?

Because utility is measured on an arbitrary scale where only differences between alternatives matter. Adding the same constant to every V cancels in the ratio P(i) = e^V_i / Σ e^V_j, so a negative V is perfectly valid. e^V is always positive, so the shares are still genuine probabilities between 0 and 1. If a share ever falls outside that range, the exponentials were summed wrong, not a sign chosen wrong. Chapter 03 · Discrete Choice Modelling (Logit)

What is the difference between the four-step and three-step travel demand models?

Both are trip-based. The four-step model keeps trip distribution (which destination zone) and modal split (which mode) as two separate stages, giving generation → distribution → modal split → assignment. CIVL2700's three-step model estimates distribution and modal split together as one joint mode/destination choice, giving generation → mode/destination choice → route choice. The modern alternative to both is the activity-based model, which simulates a person's whole daily activity schedule instead of independent trips. Chapter 04 · Travel Demand Forecasting

Where on the cumulative-curve diagram is the maximum queue, and why not at the end?

The queue is the vertical gap A(t) − D(t), and it is largest at the kink where the arrival rate drops back to capacity (λ = μ). Before that instant the gap is still widening because arrivals outrun the server; after it the server is catching up, so the gap shrinks. At clearance the two curves meet and the gap is zero, and at t = 0 the queue has not yet formed — so evaluate the maximum at the kink, not at either end. Chapter 05 · Deterministic (D/D/1) Queueing & Departure-Time Choice

When do I use M/D/1 instead of M/M/1?

Use M/D/1 when service takes a fixed, constant time per vehicle (an automated gate or a fixed-cycle booth); use M/M/1 when service times are variable (exponential). At the same rho, M/D/1 gives exactly half the queue term, so choosing M/M/1 for constant service over-predicts the queue. Chapter 06 · Stochastic Queueing (M/M/1, M/D/1, M/M/1/N)

Why does q = k·v only work with the space-mean speed?

The identity is really flow = density × (distance covered per unit time by the vehicles on the road). That average distance-per-time is the space-mean (harmonic, section) speed. The time-mean speed averages spot speeds at a point, where fast vehicles are over-sampled, so it is biased upward and would over-estimate the flow. Substituting v_s = q/k is exact; substituting v_t is not. Chapter 07 · Traffic-Stream Variables: Flow, Density, Speed

Why must q = k·v use the space-mean speed and not the detector's spot speeds?

A loop or radar at a fixed point over-samples fast vehicles (they pass more often), so the arithmetic average of spot speeds — the time-mean speed — is biased high and is always ≥ the space-mean speed. Only the space-mean (harmonic / travel-time-based) speed makes q = k·v exact, which is why exam questions that hand you spot speeds expect a conversion before you multiply by density. Chapter 08 · Fundamental Diagram, MFD & Traffic Measurement

Why does a roundabout have fewer conflict points than a signalised 4-leg cross?

A single-lane 4-leg cross has 32 vehicle conflict points — 16 crossing, 8 merging and 8 diverging. A roundabout forces every entry to be a merge and every exit a diverge, so it carries no crossing conflicts and only 8 points in total (the T-junction and roundabout figures are standard textbook values — confirm on Canvas). Because crossing conflicts cause the highest-severity right-angle and head-on crashes, removing them is why roundabouts are the safety win; the geometry also lowers relative speeds. Chapter 09 · Principles of Intersection Control

Why are the yellow and all-red rounded UP to 0.5 s and never down?

Because they are safety clearances: the yellow gives a driver time to stop or commit, and the all-red flushes committed vehicles before the conflicting green. Rounding down would shorten that protection and could create a dilemma zone, so both y and AR are rounded up to the nearest 0.5 s - and each is rounded before you add them for the intergreen I = y + AR. Chapter 10 · Signal Timing I: Phasing, Clearance & Lane Groups

When do I use Webster's optimum cycle and when do I use the minimum cycle?

Use Webster's C_opt = (1.5L + 5)/(1 − Y_c) when the question asks you to minimise delay — it sits at the bottom of the delay-versus-cycle U. Use the minimum cycle C_min = L·X_c/(X_c − Σ(v/s)_ci) when you are given a target degree of saturation (a v/c ceiling such as 0.90) and want the shortest cycle that still holds it. Usually C_opt is the longer of the two, and both round up to the nearest 5 s. Watch the denominators: Y_c must be below 1 for C_opt, and the target X_c must exceed Σ(v/s)_ci for C_min to stay positive. Chapter 11 · Signal Timing II: Webster Cycle & Green-Time Allocation

Is the Week-12 public-transport material examinable in CIVL2700?

Yes. Public transport operation and planning is part of the University of Sydney CIVL2700 syllabus and is fair game in the comprehensive final exam (worth 40% of the unit, a supervised 2.5-hour paper covering the whole semester). The dwell-time and transit-economics calculations are short and formula-light, making them an efficient place to earn marks. Confirm the exam scope, date and the open/closed-book rule on Canvas. Chapter 12 · Public Transport Operation & Planning

How to study for the exam

Treat CIVL2700 as a set of recurring calculation types rather than a reading unit, and rehearse them weekly on Canvas material rather than cramming through STUVAC. Each week, do one worked problem of that week's model end to end — write the model name, substitute with SI units, carry one clean calculation, then interpret the answer and cross-check it a second way (for example spacing from 1/k against v·h̄).

Because In-class Test 1 covers Weeks 1–4 and Test 2 covers Weeks 5–8, those weeks get examined twice, so keep old test topics warm rather than filing them away.

For the comprehensive 40% final, prioritise breadth: the hurdle rewards attempting every topic, so make sure you can start a question in traffic flow, queueing, the fundamental diagram, signal timing and demand forecasting, and only then deepen the ones you find hardest.

When a step won't click, ask Sia to explain that single step a different way and to set you a fresh practice question in the same style — it teaches the method and checks your reasoning, and it never substitutes for your own graded work.

Your AI Engineering tutor for CIVL2700

Stuck on a hard CIVL2700 question? Sia is AskSia’s AI Engineering tutor — ask any CIVL2700 Transport Systems question and get a clear, step-by-step explanation grounded in how the course is actually taught and assessed. Read this whole study guide free, then take your hardest questions to Sia.