THESIS
2017
ix, 43 pages : illustrations ; 30 cm
Abstract
Motivated by safety challenges resulting from distracted pedestrians, we design and implement
VSpace, an acoustic-based system to alert pedestrians of any oncoming vehicles
with their smartphones by acoustic Doppler Effect profiling. VSpace can figure out the
vehicle spatial status including velocity, direction and minimum distance online based on
vehicle acoustic sensing. VSpace performs vehicle spatially-aware discovering in four major
steps: (1)Vehicle acoustic signal processing; (2)Vehicle classification; (3)Vehicle sound
Doppler profiling and (4)Vehicle spatial status reconstruction. All implementation of VSpace
is based on a COTS smartphone with a microphone. We evaluate VSpace with comprehensive
experiments of 20 different vehicles in 240 practical cases, in which VSpace...[
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Motivated by safety challenges resulting from distracted pedestrians, we design and implement
VSpace, an acoustic-based system to alert pedestrians of any oncoming vehicles
with their smartphones by acoustic Doppler Effect profiling. VSpace can figure out the
vehicle spatial status including velocity, direction and minimum distance online based on
vehicle acoustic sensing. VSpace performs vehicle spatially-aware discovering in four major
steps: (1)Vehicle acoustic signal processing; (2)Vehicle classification; (3)Vehicle sound
Doppler profiling and (4)Vehicle spatial status reconstruction. All implementation of VSpace
is based on a COTS smartphone with a microphone. We evaluate VSpace with comprehensive
experiments of 20 different vehicles in 240 practical cases, in which VSpace
achieves an overall accuracy of 91.67% in vehicle classification and satisfactory low relative
error in vehicle spatial status reconstruction, respectively.
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