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Traffic Caution System for Pedestrian Safety

Authors: Hojin Jung; Seong Kyung Kwon; Haengju Lee; Sang Hyuk Son;

Traffic Caution System for Pedestrian Safety

Abstract

According to the 2013 annual report file by the Fatality Analysis Reporting System (FARS), 14 percent of all traffic fatalities and an estimated 3 percent of those injured in traffic crashes were pedestrians. Our approach is active safety system based on pedestrian detection. This paper proposes a traffic caution system for pedestrian safety whose objective is to give a warning using visual effect to both driver and pedestrian to solve a lack of driver's and pedestrian's road attentiveness. Our contributions are as follows: 1) pedestrian detection and vehicle speed estimation using low cost sensors, 2) spontaneous participation of a driver for risk awareness according to visual effects (e.g., if LEDs are turned on, the driver puts the phone down.), and 3) improvement of roadattentiveness of a pedestrian and a driver using visual effects (i.e., high attentiveness on the road if LEDs are red, and moderate attentiveness on the road if LEDs are yellow.).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Top 10%
Average
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