Title page for etd-0226115-110948


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URN etd-0226115-110948
Author Zong-Han Wu
Author's Email Address No Public.
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Department Mechanical and Electro-Mechanical Engineering
Year 2014
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Intelligent Road Surface Detection Systems Based on
Terrain Classification and Quality Analysis
Date of Defense 2015-02-10
Page Count 81
Keyword
  • terrain classification
  • BPNN
  • feature extraction
  • pothole detection
  • multi-sensors
  • Abstract Nowadays, the drivers cannot dodge bumpy road because of unfamiliar with traffic and poor visibility and to cause the traffic accident, therefore the situation of the roadway and driving safety are the most interested topic.
      In this thesis, the main experimental equipment is golf car which equip the webcam, laser range finder, IMU and RTK-DGPS to construct an intelligent roadway detection system. In this system, we divide it into three functions, terrain classification, pothole detection and roadway quality analysis. In terms of terrain classification, the experimental equipment captures the front of image through the webcam, and this information as the inputs of Back Propagation Neural Network (BPNN) is the training of the terrain classification and the final classification mechanism. In terms of pothole detection and roadway quality analysis, the experimental equipment gauges the pothole and analyze the roadway quality through laser range finder, webcam and IMU. At the end, the system will gather the outcome of functions and then mark on the latitude and longitude of Google Map through RTK-DGPS on user interface to notify the drivers of nearby traffic.
      This thesis, intelligent roadway detection system, is the first system which integrates the terrain classification, pothole detection and roadway quality analysis. This system provides the information of the front of roadway for drivers to avoid the rough roadway and to decrease the chance of the traffic accident, and the more safety and comfortable driving environment.
    Advisory Committee
  • Sheng-Fu Liang - chair
  • Pei-Hsuan Tsai - co-chair
  • Jau-Woei Perng - advisor
  • Files
  • etd-0226115-110948.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2015-03-26

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