University of Belgrade
Faculty of Transport and Traffic Engineering
Vojvode Stepe 305, 11000 Belgrade, Serbia and Montenegro
http://www.sf.bg.ac.yu/
Emails: katarina@sf.bg.ac.yu ; dusan@sf.bg.ac.yu
Short Course 2006
Traffic Control and Transportation Planning:
Fuzzy, Neuro and Soft Computing Approach
13-15 June 2006, Belgrade, Serbia and Montenegro
Lecturers: Professors Dušan Teodorović and Katarina Vukadinović
Date: 13-15 June 2006
Location: Belgrade, Serbia and Montenegro
Fee:
950 €
Scope
The planning, design, and control of transportation systems (and especially
Intelligent Transportation Systems (ITS)) are complex subjects. A wide range of traffic
and transportation engineering parameters are characterized by uncertainty, subjectivity,
imprecision and ambiguity. Human operators, traffic controllers, dispatchers, drivers,
passengers, engineers, and planners use subjective knowledge, approximately known
values, and/or linguistic information on a daily basis when making decisions. Complex
traffic and transportation problems call for development of modern intelligent systems
that merge knowledge, techniques, and methodologies from various scientific areas.
These intelligent systems should be able to recognize different situations, and to
make appropriate decision without knowing the functional relationships between
individual variables. The new generation of intelligent traffic and transportation systems
should be able to generalize, adapt, and learn based on new knowledge and new
information.
Modern intelligent systems are based on computational tools that are capable to
compute with words (Fuzzy Logic), learn and adapt (Artificial Neural Networks), and
perform systemized random search and optimization (Genetic Algorithms). This
collection of computational tools has been known as Soft Computing.
The primary goal of this short course is to acquaint the participants with the basic
elements of Soft Computing, applications of Soft Computing techniques to date in traffic
and transportation engineering, and to indicate the directions for future research in this
area.
There are numerous traffic, transportation and logistic problems where Soft
Computing techniques could apply. These concepts are especially important for research
activities whose unified themes are uncertainty (randomness, stochasticity, fuziness, ...)
and time-dependence (dynamic, real-time). The state-of-the art Soft Computing
techniques used to model various traffic and transportation engineering problems (road
traffic control, ramp metering, signal control, route guidance, transportation planning,
route choice, traffic assignment, vehicle routing, scheduling, and dispatching) will be
presented and discussed. Because of its nature the course will be of interest to various
participants.
All transparency copies, and additional written material will be handed out.
Who Should Attend
The course should be attended by engineers, research and teaching assistants, graduate
students, traffic and transportation experts, planners, researchers, consultants, and
government employees, and all others who are interested in improving their knowledge,
and understanding soft computing models of complex traffic and transportation
phenomena.
Tentative Course Contents
1. INTRODUCTION
Course information
Other information
2. BASIC DEFINITIONS OF THE FUZZY SETS THEORY
The concept of fuzzy sets
(the equality of fuzzy sets; subsets of fuzzy sets; the intersection of fuzzy
sets; the union of fuzzy sets; fuzzy set height; support of fuzzy set; the
scalar cardinality of fuzzy set; complement of fuzzy sets; convex fuzzy
sets)
Fuzzy sets and probability theory
Linguistic variables and linguistic hedges
Fuzzy sets as points in hypercubes
Fuzzy relations
Max-min composition
Extension principle
Alpha cut
3. FUZZY ARITHMETIC
The concept of a fuzzy number
Adding, subtracting, multiplying and dividing fuzzy numbers
Triangular and trapezoidal fuzzy numbers
Methods for comparing fuzzy numbers
4. THE BASIC ELEMENTS OF FUZZY LOGIC SYSTEMS
Rules
Fuzzy inference engine
Fuzzification
Defuzzifier
Generating and tuning the fuzzy logic systems
Fuzzy logic type 2
5. A FUZZY MATHEMATICAL PROGRAMMING
The basic premises of Fuzzy Mathematical Programming
Fuzzy Linear Programming
6. ARTIFICIAL NEURAL NETWORKS
Basic concepts of Artificial Neural Networks
Neurons
Characteristics of Neural Networks
Classification of Neural Networks
A Multilayered Feedforward Neural Network
Training of a Neural Network
7. METAHEURISTIC ALGORITHMS
Combinatorial optimization problems and solution approaches
Tuning fuzzy logic systems as Combinatorial optimization problem
Genetic Algorithms
Simulated Annealing
Tabu Search
Ant Colony Optimization
8. MODELING ROUTE-CHOICE AND TRAFFIC ASSIGNMENT PROBLEMS
BY FUZZY LOGIC
User equilibrium and system optimum
Braess paradox
Stochastic traffic assignment
Travel time perceptions
Solving route choice problems in urban networks using fuzzy logic
Modeling route choice with advanced traveler information by fuzzy logic
Fuzzy-Neural approaches to route selection for dynamic route guidance
9. TRAFFIC FLOW MODELING BY FUZZY LOGIC
GM based car-following models
Fuzzy inference car-following models
Fuzzy sets and systems for a lane-changing model
10. RAMP METERING BY SOFT COMPUTING TECHNIQUES
Ramp metering strategies
Genetic-Fuzzy approach for ramp metering
A Neuro-Fuzzy algorithm for coordinated traffic responsive ramp metering
11. SOFT COMPUTING TECHNIQUES IN INCIDENT DETECTION
Fuzzy logic/Neural Network based incident detection
Fuzzy clustering based approach to automatic incident detection
12. SOFT COMPUTING METHODS IN TRAFFIC CONTROL
Traffic control strategies classification
Fuzzy Logic/Neural Network models of signalized pedestrian crossing
Fuzzy Logic/Neural Network models of signalized intersections
Intelligent isolated intersection
Distributed and cooperative fuzzy controllers for traffic intersections group
13. SOFT COMPUTING METHODS IN TRANSPORTATION DEMAND
ANALYSIS
Forecasting with Neural Network models
Neural Network for estimation of an Origin-Destination matrix
Neural Network for estimating a real-time Origin-Destination matrix from traffic
counts
Trip distribution modeling using fuzzy logic and a genetic algorithm
Neural Network approach to transportation network improvement problem
14. SOFT COMPUTING METHODS IN VEHICLE, ROUTING, SCHEDULING,
AND DISPATCHING
Vehicle routing and scheduling problems characterized by travel and/or service
time uncertainty
Vehicle routing and scheduling problems characterized by node demand
uncertainty
About the Lecturers
Professor Dušan Teodorović has had a full-time University career since 1974 at
the University of Belgrade, Serbia and Virginia Polytechnic Institute and State
University, USA. Dr. Teodorovic’s main contribution is pioneering scholarly research in
the area of soft computing techniques (fuzzy systems, neural networks and genetic
algorithms) in Traffic and Transportation Engineering. Professor Dušan Teodorović’s
research interests are Operations Research and Artificial Intelligence applications in
traffic and transportation engineering. He has taught various undergraduate, graduate, and
doctoral courses in the areas of transportation engineering and Operations Research. He
is co-author of the book: “Traffic Control and Transport Planning: A Fuzzy Sets and
Neural Networks Approach”, Kluwer Academic Publishers, Boston, (1998), and the
author of numerous technical papers. He was Guest Editor of the Special Issues of the
journals Transportation Planning and Technology (1993), and Fuzzy Sets and Systems
(2000) devoted to the Fuzzy Sets Theory applications in traffic and transportation. He is
an Editorial Board member in a few scientific journals. Professor Teodorović in an
Elected Member of the Academy of Engineering Sciences of Serbia and Montenegro.
Associate professor Katarina Vukadinović’s research and teaching topics are
Operations Research and Artificial Intelligence applications in transportation planning, as
well as transportation system performance analysis and evaluation. She is a co-author of
the book: “Traffic Control and Transport Planning: A Fuzzy Sets and Neural Networks
Approach”, Kluwer Academic Publishers, Boston, (1998), and the author of a few
technical and journal papers.
Fee and Registration
Registration is limited to 40 participants on a first-come-first-serve basis. The fee is
950€. This fee includes:
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Handout material (transparency copies, reading material)
Refreshments
Daily lunch
One course dinner
Method of Payment
Payment may be effectuated via:
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check (indication: “Short Course Professor Dušan Teodorović”)
Location
The course will take place at the Faculty of Transport and Traffic Engineering, University
of Belgrade (located 5 Km from the Belgrade city center), Serbia and Montenegro.
Accommodation
Comfortable rooms in various Belgrade’s hotels will be available at special prices for the
participants. Participants will have to arrange their reservations themselves. Detailed
information on travel options, the Belgrade city attractions, and hotel information and
prices will be provided upon receipt of the registration.
To register, please send an email message to katarina@sf.bg.ac.yu
or dusan@sf.bg.ac.yu