According to Motorcycle Industrial Council (MIC), in USA the number of owned
motorcycle increased during last few years and most likely will keep increasing. However, the
number of the deadly crash accidents associated with motorcycles is on the rise. Although MIC
doesn't explain why the accident rate has increased, the unprotected motorcyclist gear can be one
of the reasons. The most recent National Highway Traffic Safety Administration (NHTSA)
annual report stated that its data analyses are based on their experiences and the best judgment is
not based on solid scientific experiment [3]. Thus, building a framework for the data acquisition
about the motorcyclist environment is a first step towards decreasing motorcyclist crashes.
There are a few naturalistic motorcycle studies reported in the literature. The naturalistic
motorcycle study also identifies the behaviors and environmental crash hazards. The primary
objective of this thesis work is to design a highly portable data logging embedded system for
naturalistic motorcycle study with capability of collecting many types of data such as images,
speed, acceleration, time, location, distance approximation, etc. This thesis work is the first
phase (of three phases) of a naturalistic motorcycle study project. The second phase is to
optimize system area, form factor, and power consumption. The third phase will be concerned
with aggressive low power design and energy harvesting. The proposed embedded system design
is based on an Arduino microcontroller. A whole suite of Arduino based prototype boards,
sensor boards, support software, and user forum is available. The system is high portable with
capability to store up to eight (8) hours of text/image data during a one month study period. We
have successfully designed and implemented the system and performed three trial runs. The data
acquired has been validated and found to be accurate.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-5866 |
| Date | 01 January 2013 |
| Creators | Elmehraz, Noureddine |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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