AH2170 Transport Data collection and Analysis 7.5 credits

Transport Data collection and Analysis

Please note

The information on this page is based on a course syllabus that is not yet valid.

Evaluation, design, planning and operation of transportation system requires rich data, and systematic and efficient data collection plans.

The need for data and techniques for data analysis must  be adapted to the problem and site in question. Different types of data require different reduction techniques as well as methods for accurate statistical data analysis.

The course will provide knowledge on data collection and analysis methods as well as selection and interpretation of appropriate statistical tests that are relevant to the solution of the studied problem.

  • Education cycle

    Second cycle
  • Main field of study

    Built Environment
  • Grading scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 19 for programme students

Autumn 19 for Study Abroad Programme (SAP)

  • Periods

    Autumn 19 P1 (7.5 credits)

  • Application code

    10026

  • Start date

    26/08/2019

  • End date

    25/10/2019

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places *

    Min. 1

    *) The Course date may be cancelled if number of admitted are less than minimum of places.

  • Application

    Apply for this course at antagning.se through this application link.
    Please note that you need to log in at antagning.se to finalize your application.

Autumn 18 for Study Abroad Programme (SAP)

  • Periods

    Autumn 18 P1 (7.5 credits)

  • Application code

    10047

  • Start date

    27/08/2018

  • End date

    26/10/2018

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places *

    Min. 1

    *) The Course date may be cancelled if number of admitted are less than minimum of places.

Autumn 18 for programme students

Autumn 18 for programme students

Intended learning outcomes

  • Identify appropriate methods for transportation, traffic and spatial data collection.
  • Understand transportation and geoinformation data needs
  • Understand the role sampling the data collection
  • Use descriptive statistics for the analysis and preparation of data
  • Perform outlier analysis
  • Perform statistical inference for hypothesis testing and interval estimations
  • Specify and estimate linear regression models and discrete choice models
  • Apply methods and interpret results using statistical software
  • Design and perform stated-preference study
  • Discuss and compare linear regression models and discrete choice models and their attributes

Course main content

  • Transportation and geoinformation data needs
  • Sampling and sample statistics.
  • Descriptive statistics and outliers
  • Hypothesis testing and confidence Intervals
  • Linear regression and applications (in transport and traffic)
  • Maximum estimation likelihood method and applications
  • Other data analysis and model building methods

The content of the course is presented and trained in tutorials. Applications are in traffic studies, transport planning, safety studies and spatial analysis. Further training in field surveys and data analysis, model building and interpretation is carried out in the form of comprehensive project work.

The project covers all the major steps that have to be undertaken including report preparation, discussion of the results. The students will also present their results for discussion.

Eligibility

Bachelor’s degree in engineering, science, economics, planning or a similar degree, with at least 60 cr (ECTS) in mathematics, physics, statistics and/or computer science, as defined in the admission requirements for the Master’s programme in Transport and Geoinformation Technology. Together with documented proficiency in English corresponding to English B.

Literature

Possible literature could include:

S. Washington, M. Karlaftis, F. Mannering, Statistical and Econometric Methods for Transportation Data Analysis (2003).

Class handouts and material on Bilda.

Other useful books:

  • M. Ben-Akiva, S. Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, 1987.
  • J. de D. Ortúzar and L.G. Willumsen, Modelling Transport (2002).
  • O’Flaherty (ed.), Transport Planning and Traffic Engineering, chapter 12-13, 1997.

Examination

  • PRO1 - Project Assignments, 3.5, grading scale: A, B, C, D, E, FX, F
  • TENA - Written Examination, 4.0, grading scale: A, B, C, D, E, FX, F

Requirements for final grade

A mandatory written examination equivalent to 4.0 cr with grading scale A-F and a mandatory project assignment equivalent to 3.5 cr with grading scale A-F. The course will have grading scale A-F, where the course grade will be determined by the grade on the written examination and the project work.

Offered by

ABE/Systems Analysis and Economics

Contact

Anders Karlström

Examiner

Anders Karlström <anders.karlstrom@abe.kth.se>

Version

Course syllabus valid from: Autumn 2019.
Examination information valid from: Autumn 2010.