COURSE UNIT TITLE

: QUEUING MODELS IN TRANSPORTATION SYSTEMS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CIE 5068 QUEUING MODELS IN TRANSPORTATION SYSTEMS ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR SERHAN TANYEL

Offered to

TRANSPORTATION ENGINEERING
TRANSPORTATION ENGINEERING
TRANSPORTATION ENGINEERING

Course Objective

Queue formation is one of the most important factors in transportation systems. To be able to predict the performance of a transportation system and to optimize the facility use are possible by modeling the queue formation in transportation facilities. By this course, it is aimed to provide information about the queuing models, and ability to describe various cases encountered in transportation systems.

Learning Outcomes of the Course Unit

1   To formulate the queue formations in transportation systems
2   To analyze the function of queue and delay terms in traffic engineering
3   To relate various queue models with the cases encountered in traffic engineering
4   To adapt the queue model outputs in the performance analysis of transportation systems
5   To apply, evaluate and present queue models on the samples of transportation system facilities

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to queuing models, objective, histiorical development, terms and notations, the problems and solution methods in queuing theory, homework assignment
2 Queuing theory applications, specific equations in queuing theory, utility analysis, fundamentals of queuing
3 Queuing theory applications (cont.), random variable functions, M/G/1 queue systems, temporal analysis of M/M/m queue systems
4 Random variable functions (cont.), numerical example: case 1 (one operator, infinite line), numerical example: case 2 (m operator, infinite line)
5 Random variable functions (cont.), numerical example: case 3 (one operator, finite line), numerical example: case 4 (m operator, finite line), extensions and variables
6 Queuing network, priority in queuing systems, preferable results for the queuing systems with difficult analysis procedure, spatial queues, road-driver systems, general models, double-unit models,
7 Homework presentations
8 Spatial queues (cont.), Hypercube queuing model, Hypercube approach procedure (infinite line capacity), correction factors, work load prediction, homework assignment
9 Queuing models in transportation systems, the use of queuing models in transportation systems
10 Queuing models in transportation systems (cont.), intersection systems
11 Queuing models in transportation systems (cont.), applications in public transit system
12 General applications, numerical examples
13 Home-work presentations
14 General evaluation

Recomended or Required Reading

Textbook(s): LARSON, R.; ODONI, A.R. (1999) Urban Operation Research , Massachusetts Institute of Technology.
Supplementary Book(s): INOSE, H.; HAMADA; T. (1975) Road Traffic Control , University of Tokyo Press, Japan.
Materials: Course presentations.

Planned Learning Activities and Teaching Methods

The visual presentetions and presentation slides.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE 1 MIDTERM EXAM 1
2 MTE 2 MIDTERM EXAM 2
3 ASG ASSIGNMENT
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE 1 * 0.15 +MTE 2 * 0.15 +ASG * 0.20 +FIN * 0.50
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE 1 * 0.15 +MTE 2 * 0.15 +ASG * 0.20 +RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

LO 1-4 will be evaluated by using mid-term and final exams.
LO 5 will be evaluated by using home-works and presentations.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr. Serhan TANYEL (serhan.tanyel@deu.edu.tr)

Office Hours

It will be announced when the course schedule of the faculty is determined.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 4 56
Preparation for midterm exam 2 10 20
Preparation for final exam 1 10 10
Preparing assignments 2 20 40
Preparing presentations 2 10 20
Final 1 2 2
Midterm 2 2 4
TOTAL WORKLOAD (hours) 194

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.153454
LO.24543
LO.355443
LO.43454554
LO.54343

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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