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Unit outline_

CIVL9700: Transport Systems

Semester 1, 2023 [Normal day] - Camperdown/Darlington, Sydney

This unit of study aims to provide an introduction to transport systems and is assumed knowledge for units on traffic engineering, transport planning, and city logistics. Topics include: the role of accessibility as the reason for transport; the history of transport technologies in Australia and globally; the characteristics of the principle modes of transport; factors behind the demand for mobility; qualitative choice modeling; agent-based modeling; predicting travel demands; the mechanics of queueing and traffic flow; intelligent transport systems; the microscopic and macroscopic fundamental diagrams; highway capacity and level of service; the design of transport junctions.

Unit details and rules

Academic unit Civil Engineering
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Basic statistics through regression analysis, differential and integral calculus, computer programming

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator David Levinson, david.levinson@sydney.edu.au
Lecturer(s) Jacob Elmasry, jacob.elmasry@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final Exam
Evaluate the learning outcomes for the whole semester
45% Formal exam period 3 hours
Outcomes assessed: LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11 LO12 LO13 LO14
Small continuous assessment In-Class Submissions
Weekly submissions testing content from that week's lecture.
10% Multiple weeks n/a
Outcomes assessed: LO11 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO13 LO12
Assignment Assignment 1
Solve Problems relating to the content from the first few weeks.
5% Week 06
Due date: 27 Mar 2023 at 23:59
n/a
Outcomes assessed: LO1 LO4 LO6 LO7
Small test In-Class Assessment
In-class test assessing the learning outcomes of weeks 1-7
20% Week 08
Due date: 18 Apr 2023 at 13:00
75 min
Outcomes assessed: LO5 LO13 LO7 LO6 LO4 LO9 LO8
Assignment Assignment 2
Solve Problems relating to the content from the middle of the semester.
5% Week 09
Due date: 24 Apr 2023 at 23:59
n/a
Outcomes assessed: LO4 LO5 LO6 LO7 LO8 LO13 LO1
Assignment group assignment Preliminary report of group project
A preliminary report to get feedback on Assignment 4
0% Week 10
Due date: 01 May 2023 at 23:59
n/a
Outcomes assessed: LO1 LO2 LO3 LO8 LO9 LO11 LO12 LO13 LO14
Assignment Assignment 3
Solve Problems relating to the content from the end of the semester.
5% Week 12
Due date: 15 May 2023 at 23:59
n/a
Outcomes assessed: LO1 LO4 LO5 LO6 LO8 LO9 LO10 LO11 LO13 LO14
Assignment group assignment Assignment 4
Final Group Assignment. SparkPlus may be used to assess contributions.
10% Week 13
Due date: 28 May 2023 at 23:59
n/a
Outcomes assessed: LO1 LO2 LO3 LO8 LO9 LO11 LO12 LO13 LO14
hurdle task = hurdle task ?
group assignment = group assignment ?

Assessment summary

There may be statistically and educationally defensible methods used when combining the marks from each component to ensure consistency of marking between markers, and alignment of final grades with unit outcomes and grade descriptors.

The University has authorised and mandated the use of text-based similarity detecting software Turnitin for all text-based written assignments. Detailed information for each assessment can be found on Canvas

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Assignments submitted electronically are due at 23:59 on the submission day. Assignment penalties for lateness is 5% per day. Assignments more than 10 days late or submitted once after the solutions are released on Canvas get 0.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Opening Session; Introduction to Transport Systems Lecture (4 hr) LO4 LO5 LO6
Tutorial - Discussion Tutorial (2 hr) LO1 LO2 LO4 LO5 LO6
Week 02 Transport Network Modelling (Traffic Assignment) Lecture (4 hr) LO4 LO6
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO4 LO6
Week 03 Choice Modelling Lecture (4 hr) LO4 LO6 LO9
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO6 LO7
Week 04 Travel Demand Forecasting Lecture (4 hr) LO6 LO7
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO7 LO14
Week 05 Queueing Theory; Fundamental of Traffic Engineering Lecture (4 hr) LO13
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO13 LO14
Week 06 Fundamental of Traffic Engineering; Traffic States Lecture (4 hr) LO8 LO9 LO13
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO12 LO13 LO14
Week 07 Traffic States and Measurements; Macroscopic Traffic Models Lecture (4 hr) LO6 LO9 LO13
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO13 LO14
Week 08 Highway Level of Service Lecture (4 hr) LO4 LO6 LO7 LO9 LO10 LO12 LO14
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO12 LO13 LO14
Week 09 Principles of Intersection Control Lecture (4 hr) LO4 LO5 LO6 LO8 LO9 LO11 LO13
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO8 LO11 LO13 LO14
Week 10 Traffic Signal Timing Design and Analysis Lecture (4 hr) LO5 LO6 LO8 LO9 LO13
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO8 LO11 LO14
Week 11 Public Transport Operation and Planning Lecture (4 hr) LO4 LO10 LO13 LO14
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO12 LO13 LO14
Week 12 Public Transport Operation and Planning Lecture (4 hr) LO4 LO5 LO9 LO10
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO10 LO14
Week 13 Emerging Transport Technologies; Closing Session Lecture (4 hr) LO5 LO9 LO12 LO14
Tutorial - Problem Solving Tutorial (2 hr) LO1 LO2 LO12 LO13 LO14

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Juan de Dios Ortúzar, Luis G. Willumsen, Modelling Transport (4th).
  • Fred L. Mannering, Scott S. Washburn, Principles of Highway Engineering and Traffic Analysis (5th).
  • Roger P. Roess, Elena S. Prassas, William R. McShane, Traffic Engineering (3rd).

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Seek basic information to answer general transport queries using standard knowledge resources, e.g library inquiries, web-based information
  • LO2. Evaluate reliability of external information extracts and synthesize relevant content
  • LO3. Function effectively as an individual in multidisciplinary and multicultural teams to deliver traffic related projects
  • LO4. Recognize that safety, efficiency, and sustainability are all crucial considerations for the design of transport systems
  • LO5. Explain the characteristics of the Australian transport infrastructure and identify the challenges it is facing
  • LO6. Distinguish the specific characteristics of each transport mode and identify the appropriate tool(s) for the needed analysis
  • LO7. Apply travel demand forecasting methods to predict motor vehicle, pedestrian, bicycle, and public transport flows given input land use, network geometry, and travel behaviour characteristics
  • LO8. Apply fundamental principles in the design of traffic controls
  • LO9. Demonstrate knowledge of the role that advanced technologies play and will play in the field of transport and traffic engineering
  • LO10. Recommend appropriate public transport service to serve new developments
  • LO11. Recommend appropriate measures for the design of a junction to serve all travelers and the community
  • LO12. Perform basic transport field data analysis
  • LO13. Apply traffic flow theory to the design and operation of transport infrastructure, e.g. ramp metering and traffic signal control
  • LO14. Undertake problem identification and formulation and develop solutions.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

The types, weights and content of the assessments are adjusted to reflect the online learning environment. Extra learning materials are added for tutorial classes.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.