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IOM for Transportation Systems (R-Module)

Exam number: 6786

Semester: from 1st semester

Duration of the module: One semester

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: Summer semester 2017

Prerequisites: Successful passing of "IOM for Transportation Systems"

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Jan Fabian Ehmke

Name of the professor: Prof. Dr. Jan Fabian Ehmke

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 15 h; self-study: 165 h

Contact hours (per week in semester): 1

Methods and duration of examination:

  • Concept Presentation (10% of grade)
  • Final Presentation (50% of grade)
  • Documentation (40% of grade)

Emphasis of the grade for the final grade: Please check regulations of the study programme

Aim of the module (expected learning outcomes and competencies to be acquired):
In this R-Module course, students are expected to apply approaches and methods from the lecture “IOM for Transportation Systems”. It will be mandatory for participants to have passed the previous lecture successfully. The course is limited to 16 participants. In case there are more applicants, the grade in the exam “IOM for Transportation Systems” is decisive. Application via Moodle is required.

Contents of the module:
The core topic of the R-Module will be the development and improvement of rack-based Bike Sharing Systems. In recent years, Bike Sharing Systems have evolved all over the planet, and they often have become an environmental-friendly alternative of urban mobility on the edge of personal and public transportation. Students will work in groups to analyze operational data from different, existing bike sharing systems, embed them in geographical information systems, and create examples for optimization problems and solutions discussed in the lecture. While we provide introductory material for data, approaches and solution methods, it is the participants’ task to create examples and get themselves involved with appropriate software.

Schedule

  • Kick-Off: Wednesday, June 7, 14-15:30, Room HG 217
  • Concept Presentation: Wednesday, June 28, 14-15:30, Room GD 311
  • Final Presentation and Submission of Documentation: Wednesday, July 19, 10-13, HG 217
  • If you cannot make it to one of these dates, the module is not for you.

Teaching and learning methods:
Presentation, discussion, data analysis, modeling and solving optimization problems.

Literature (compulsory reading, recommended literature):

Further information:
Registration in Moodle Viadrina required.