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osu1253598183.pdf (12.76 MB)
ETD Abstract Container
Abstract Header
Vehicle Detection and Classification from a LIDAR equipped probe vehicle
Author Info
Yang, Rong
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1253598183
Abstract Details
Year and Degree
2009, Master of Science, Ohio State University, Electrical and Computer Engineering.
Abstract
Vehicle detection and classification is important in traffic analysis and management. Various sensing techniques can be used in this field, while most preceding work relies on sensors mounted along the road way, this study develops a mobile platform using a LIDAR equipped probe vehicle to collect ambient traffic data while it drives. A vehicle detection method is developed to extract on-road vehicles from the background. The system employs two LIDAR sensors to measure the speed of the detected vehicles and then their length. A vehicle classification scheme is developed using length and height to sort the vehicles into six pre-defined categories. Ground truth data were generated from a developed GUI interface. Both the vehicle detection algorithm and the vehicle classification algorithm are evaluated by comparing the LIDAR measurement with the ground truth data, with good result.
Committee
Benjamin Coifman (Advisor)
Charles Toth (Committee Member)
Pages
70 p.
Subject Headings
Electrical Engineering
Keywords
vehicle detection
;
vehicle classification
;
image processing
;
LIDAR sensor
;
moving observer
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Citations
Yang, R. (2009).
Vehicle Detection and Classification from a LIDAR equipped probe vehicle
[Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1253598183
APA Style (7th edition)
Yang, Rong.
Vehicle Detection and Classification from a LIDAR equipped probe vehicle.
2009. Ohio State University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=osu1253598183.
MLA Style (8th edition)
Yang, Rong. "Vehicle Detection and Classification from a LIDAR equipped probe vehicle." Master's thesis, Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1253598183
Chicago Manual of Style (17th edition)
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Document number:
osu1253598183
Download Count:
4,823
Copyright Info
© 2009, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.