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DETERMINING INTERSECTION TURNING MOVEMENTS WITH DETECTION ERRORS.pdf (1.98 MB)
ETD Abstract Container
Abstract Header
Determining Intersection Turning Movements with Detection Errors
Author Info
Feng, Dehua
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707
Abstract Details
Year and Degree
2017, Master of Science, University of Akron, Civil Engineering.
Abstract
This study investigates and develops a turning movement data estimation model to determine all intersection turning movements by using a combination of matrix calculation and detector data. Two models are corresponding to two general intersection geometric backgrounds: three-leg and four-leg. According to the flow conservation law, the summation of all turning movements from a direction equals the total arrival or departure vehicles as linear equation format. These linear equations can transform into matrix format by using the coefficient matrix times the variable matrix that equals the constant matrix. After checking the number of solutions for the non-homogenous linear equation, the rank of the coefficient matrix is equal to the rank of the augmented matrix which this system called over-determined system. The system utilizes the matrix simplification techniques and pseudoinverse concept to isolate unknown variable matrix and solve by the least square method in the MATLAB. The calculated answers are 100% accuracy compared with ground truth. Moreover, with the error consideration of input data, the error matrix have joined the system. The error percentage e_i is assigned randomly to a 10% error interval. The overall results indicate that all results are within 10% and the worst-case scenario is roughly 7%. However, with historical data, the through movements have less error percent than the left and right turning movements. Through movement only have 2% error rather than 10%. Furthermore, when applying our model to the different intersection, if current input variables hold large percentage error, the alternative system can change and flip input and output variable to avoid large error. With the historical data points, the final solutions are within the 6% error range. Additionally, the results also approve that change of input volume level will not affect the result under the same error interval.
Committee
Ping Yi, Dr. (Advisor)
Kevin L. Kreider, Dr. (Committee Member)
Jun Ye, Dr. (Committee Member)
Pages
65 p.
Subject Headings
Civil Engineering
Keywords
Turning movement matrix, O-D method, Least square method, Over-determined linear system, pseudoinverse, Random error estimation
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Citations
Feng, D. (2017).
Determining Intersection Turning Movements with Detection Errors
[Master's thesis, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707
APA Style (7th edition)
Feng, Dehua.
Determining Intersection Turning Movements with Detection Errors.
2017. University of Akron, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707.
MLA Style (8th edition)
Feng, Dehua. "Determining Intersection Turning Movements with Detection Errors." Master's thesis, University of Akron, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707
Chicago Manual of Style (17th edition)
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Document number:
akron1512746695445707
Download Count:
1,206
Copyright Info
© 2017, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.