Course Title: Intelligent Transport Systems

Part A: Course Overview

Course Title: Intelligent Transport Systems

Credit Points: 12.00

Terms

Course Code	Campus	Career	School	Learning Mode	Teaching Period(s)
AUTO1929	City Campus	Undergraduate	115H Aerospace, Mechanical & Manufacturing Engineering	Face-to-Face	Sem 1 2016
AUTO1929	City Campus	Undergraduate	172H School of Engineering	Face-to-Face	Sem 1 2017, Sem 1 2018, Sem 1 2019, Sem 1 2020, Sem 2 2021, Sem 2 2022, Sem 2 2023

Course Coordinator: Dr Nirajan Shiwakoti

Course Coordinator Phone: +61 3 9925 6193

Course Coordinator Email: nirajan.shiwakoti@rmit.edu.au

Pre-requisite Courses and Assumed Knowledge and Capabilities

Pre-requisites: AUTO1928 Sustainable Transport Systems or equivalent. 

Course Description

This course introduces you to the field of Intelligent Transport Systems (ITS) with an emphasis on how advanced technology is playing a growing role in the management of traffic and transportation systems. Several functional areas within ITS such as Advanced Traveller Information Systems (ATIS), Advanced Traffic Management Systems (ATMS) and Advanced Vehicle Control Systems (AVCS) are examined along with contemporary research methods. The fundamentals of human factors and ITS implementation issues are discussed. As the field of ITS is developing rapidly, this course is intended to provide you with a solid foundation to enable further postgraduate studies or work in the designated field of ITS.

Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level.

This applies to students who commence enrolment in a bachelor honours program from 1 January 2016 onwards. See the WAM information web page for more information.(http://www1.rmit.edu.au/browse;ID=eyj5c0mo77631)
 

Objectives/Learning Outcomes/Capability Development

This course contributes to the development of the following Program Learning Outcomes:

1 Knowledge and Skill Base
1.2. Conceptual understanding of the mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline.
1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
1.4. Discernment of knowledge development and research directions within the engineering discipline.

2 Engineering Application Ability
2.1. Application of established engineering methods to complex engineering problem solving.
2.2. Fluent application of engineering techniques, tools and resources.

3 Professional and Personal Attributes
3.1. Ethical conduct and professional accountability
3.2. Effective oral and written communication in professional and lay domains.
3.4. Professional use and management of information.
 

Upon successful completion of this course you should be able to:

1. Apply the fundamentals of traffic flow theory in the management and operations of road traffic;
   2. Characterise the range of technologies involved in the delivery of traveller information systems;
   3. Assess the options available for the management of non-motorized and motorized traffic;
   4. Investigate and analyse the current applications and trends in the context of AVCS;
   5. Critical review of literature on the contemporary issues in the application of advanced technology in transport.

Overview of Learning Activities

The learning activities included in this course are:
• pre-recorded lecture videos: will guide students through important principles and concepts and assist in appropriate problem solving techniques;
• tutorial sessions: will help students to connect theory to practice, and reinforce the principles and concepts learnt in the lectures; and

Overview of Learning Resources

Course-related resources will be provided on Canvas. These will include course notes or presentations, and other learning materials generated by the course lecturer(s), references, and approved links to useful material on external web-sites.

Overview of Assessment

X This course has no hurdle requirements.
☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Learning & Teaching).

Assessment item 1:  Problem Solving (Individual)
Weighting of final grade: 35%  
Related course learning outcomes: 1, 2, 3, 4
Description:  You will work on solving various theoretical and numerical problems related to topics covered in this course.

Assessment item 2:  Report (Group)
Weighting of final grade:  30% 
Related course learning outcomes: 5
Description:  You will critically analyse on ITS application case study and submit a report.

Assessment item 3:  Presentation (Group)
Weighting of final grade: 15% 
Related course learning outcomes: 5
Description:  You will present and defend the main findings from your report on ITS application case study.

Assessment item 4:  Report (Group)
Weighting of final grade: 20% 
Related course learning outcomes:  1, 2, 3, 5
Description: You will be asked to plan, undertake, and report on an observational survey.