675 Instrumentation, signals, and control in transportation applications
Instructor: B. Coifman, Coifman.1@OSU.edu
Call number ECE 675: 10443-0 (if full, contact professor, we'll get you in)
Call number CE 675: 05166-6
Fall 2007, days/time TuTh 12:30-1:48, Bo 437
Undergraduate and Graduate, 3 credit hours
office hours Tu Th 1:48-2:48 in Hi 491b, briefly right after class in the classroom and by appointment
Come to first lecture before purchasing book
Preamble
Signals and disturbances are continually propagating through the traffic stream and we never notice them. Consider the animation to the left, it shows the evolution of the traffic state on a freeway, each circle is a different car. Notice that the vehicles move forward while the stop wave moves backwards. The image in the top right shows a frame that was used for the data extraction. In this class we will use engineering tools to come to understand what is going on and why.
Description
An interdisciplinary course bringing together electrical engineering tools and transportation applications. Students will gain valuable experience working in teams while learning traffic flow, surveillance and control.
This course will use hundreds of inductive sensors deployed along 14 miles of I-70/71 as well as instrumented vehicles (GPS position, radar distance sensors, etc.) to gain an understanding of what happens on the freeway. After quickly learning the basics of traffic flow theory, students will discover that signals and waves propagate through the traffic stream and learn how to work with this information. The course will also address instrumentation and data management.
Course projects can focus on such items as the propagation of waves in the traffic stream or the use of distance measuring equipment on probe vehicles.
Lectures will include a hands-on introduction to using Matlab effectively and manipulating data efficiently.
Success in the employment world depends on your ability to adapt and learn from every opportunity. This course will introduce you to new analytical tools that should prove beneficial in many situations. For example, no matter what your career path may be, you will have to mange large quantities of data. This course will help you learn the art of choosing the right data structures in a computer program that will greatly simplify the problem.
Finally, good performance in this class could lead to employment either as a GRA or an undergraduate researcher. the material covered is the cornerstone of a growing research program here at OSU.
Who should attend- EE
This course will be of interest to any electrical engineering student because it will apply electrical engineering skills that you have developed through out your education career. Furthermore, it will help you develop valuable analytical skills. While this course focuses on transportation applications, the problem solving techniques associated with moving people and goods can be transferred to the other areas of electrical engineering.
Who should attend- CE
Students with an interest in transportation systems or flows in general will be well served by this course. You will be introduced to traffic flow theory and be able to see it hands on. Again, it will apply engineering skills that you have developed through out your education career and it will help you develop valuable analytical skills.
Prerequisites
They boil down to some familiarity with computer programming and a willingness to learn. Consult the instructor for written permission (which should not be a problem) if you do not meet the official prerequisites.
Administrative stuff
syllabus.pdf
Reference stuff
Matlab student version
Matlab campus site license
Examples of various traffic control devices
Examples of loop detectors
Shock wave animations
Traffic Flow Theory Manuscript
Traffic Detector Handbook
On procrastination
To get to Transportation Research...
Committee on Academic Misconduct suggestionws
Homework
Traffic Flow Theory Manuscript (okay, so this is already listed under references)
Supplementary .m file for chapter 2 reading, lecture 1
Loop data, lecture 3
Solutions to HW #1, lecture 5 (remember, annotate fmsloadr2class.m, the hw1solnAlternateVersions are just FYI)
Data for HW #2, lecture 5
Data from HW #1, lecture 5
Still more alternate solutions to HW #1, lecture 5. A few students stumbled on to textread, which works well for the one hour of data, but would likely choke on 24 hrs. So I went back and came up with these two variations that borrow ideas from textread and run much quicker than the other posted solutions.
Revised HW #3 assignment, lecture 6
Solutions to HW #2, lecture 7
Data for HW #3, lecture 7
Solutions to HW #3, lecture 9
Solutions to HW #4, lecture 11
TRIS on line transportation publication search, lecture 13
Solutions to HW #5, lecture 13
Notes
Return to Benn Coifman's Electrical Engineering page
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