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Unit outline_

CIVL5701: Transport Networks

Semester 2, 2021 [Normal day] - Remote

This unit of study aims to provide an introduction to the intersections of theory and applications in Transport Networks, Geography, and Land Use. It describes how to characterize networks, (topology, hierarchy, morphology), and how that affects the use of those networks. The course is a mix between a lecture and a student-led seminar, with students responsible for researching and presenting on a number of the topics, as well as developing a course text in a wikibook format. Students will learn the basics of networks and how transportation systems function on them.

Unit details and rules

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

CIVL2700 OR CIVL9700

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator David Levinson, david.levinson@sydney.edu.au
Type Description Weight Due Length
Assignment Assignment 1: Accessibility Analysis
X
5% Week 02
Due date: 31 Aug 2020 at 23:59
1 Week
Outcomes assessed: LO4
Assignment Assignment 2: CLUSTER
5% Week 04 n/a
Outcomes assessed: LO2
Assignment Assignment 3: SONG
5% Week 06 n/a
Outcomes assessed: LO2 LO3
Assignment Assignment 4: ADOBE
5% Week 09 n/a
Outcomes assessed: LO3 LO4
Presentation group assignment Develop Transport Network Plan
Design a network
40% Week 12
Closing date: 02 Nov 2020
Work on over course of semester.
Outcomes assessed: LO1
Assignment Take-home exam
D Take-home (short release). Extended essay. No MCQ
20% Week 13
Due date: 16 Nov 2020 at 15:00

Closing date: 16 Nov 2020
2 hours expected duration.
Outcomes assessed: LO2 LO4 LO3
Assignment Weekly Quizzes
Online Quiz Reinforcing Lectures
20% Weekly Online Quiz each week ~ 20 min
Outcomes assessed: LO2 LO3 LO4
group assignment = group assignment ?

Assessment summary

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.

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 Accessibility Lecture (3 hr) LO4
Week 02 Characterising networks Lecture (3 hr) LO1
Week 03 Historical network growth (London, Twin Cities, New York, Beijing) Lecture (3 hr) LO2
Week 04 Historical network growth (cont'd) Lecture (3 hr) LO2
Week 05 Evolving transport networks Lecture (3 hr) LO3
Week 06 Vulnerability, resilience, robustness and reliability Lecture (3 hr) LO1
Week 07 Scaling and Size Lecture (3 hr) LO3
Week 08 Network Economics. Spatial interaction: matching home and work (ABODE model) Lecture (3 hr) LO3
Week 09 Spatial econometrics Practical (3 hr) LO3
Week 10 Network Morphology, Space Syntax, and Public Transport Networks Lecture (3 hr) LO3
Week 11 Term Paper Presentations and Conclusions Presentation (3 hr) LO1 LO2 LO3 LO4

Attendance and class requirements

Weekly in-person (online) attendance is expected as per University requirements. There will be in-class activities critical to learning.

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

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

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. develop a transport network plan for a potential development site, share with class
  • LO2. use a network evolution model: understand the iterative growth of networks; understand place formation as a response to the growth of networks; understand the impact of first mover advantages
  • LO3. draw implications of alternative policies on transportation network growth; demonstrate transportation planning model (modeling process); practice the methods of system analysis
  • LO4. analyse the accessibility of a metropolitan region: create a mobility (isochrone) map for one place in a metropolitan area by multiple modes; create an isochrone for one mode for several different areas in the region, compare these locations spatially, and discuss the effect of network structure and location on mobility; create an accessibility map for multiple modes for a consistent time of day for one year; comment on the differences in the accessibility by mode.

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.

Weekly quizzes and more problems/examples have been added since the last time the unit was offered.

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.