Postgraduate taught 

Urban Analytics MSc

Transport Planning Lab URBAN5102

  • Academic Session: 2023-24
  • School: School of Social and Political Sciences
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes

Short Description

The course will provide hands-on training in the use of software used for transport planning. 

Timetable

Course will be offered in 2 hourly blocks over 9 weeks.

Excluded Courses

None

Co-requisites

Transport Planning Methods (URBAN5103)

Assessment

Assessment:

The course assessment will include three equally weighted exercises. Each exercise will have 2-3 questions and students should submit their workings and a short write-up of each exercise. The 'workings' will be the R code, Excel file etc. that was used to do the analysis. For each exercise, students will be asked to answer a set of questions which will require them to present and discuss their results (approximately 750 words per exercise). 

Course Aims

This course will supplement the material covered in the Transport Planning Methods course with a series of in-lab hands-on specialised software training.

 

Specific course aims are to:

■ introduce cost-benefits analysis and statistical programming software (R); and

■ provide examples of real-world transport planning problems and state-of-art practitioner approaches to addressing frequently encountered transport analysis problems.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ identify, investigate and evaluate real-world transport planning problems and state-of-art practitioner approaches to addressing frequently encountered transport analysis problems;

■ process diverse types of transport planning data;

■ conduct a statistical analysis using real data on a transport-related topic and write a concise description of the main findings to communicate to a non-technical audience;

■ develop transport planning and impact analysis scenarios, present major assumptions and write a concise description of the main findings;

■ conduct a cost-benefit analysis and present understanding of the principles and concepts relating to life-cycle analysis, estimation of salvage values, discounting and other related concepts; and

■ apply statistical programming software (R) skills to solve transportation problems and conduct cost-benefit analyses.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.

 

Minimum requirement for award of credit for students on MSc City Planning is D3 or above.

 

University standard regulations apply to students on other qualifications.