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Vehicle Detection and Classification from a LIDAR equipped probe vehicle

Abstract Details

2009, Master of Science, Ohio State University, Electrical and Computer Engineering.
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.
Benjamin Coifman (Advisor)
Charles Toth (Committee Member)
70 p.

Recommended Citations

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)