Abstract
A semi-integrated system for driver assistance and pedestrian safety is presented. This system is composed of a single camera which focuses on the driver for picking up visual cues and a stereo rig that focus on the road ahead for the detection of road obstructions and pedestrians. While the car is in motion, the driver's viewing direction is obtained and analyzed along with information of road condition and any moving vehicle ahead in order to determine if the current driving condition is safe. In addition, when the vehicle is moving slowly, the system can also detect the existence of a pedestrian ahead and warns the driver if the pedestrian moves in front of the car. This system contains algorithm-based safety analysis as well as fuzzy rules-based analysis for interaction between variables. Our experimental results show that the condition for driver safety can be accurately classified in 94.5% of the tested driving conditions, and the pedestrians can be identified in 93.18% of the tested cases. These were compared to the results of similar systems and shown to be superior.
| Original language | English |
|---|---|
| Pages (from-to) | 4413-4427 |
| Number of pages | 15 |
| Journal | Applied Soft Computing Journal |
| Volume | 13 |
| Issue number | 11 |
| DOIs | |
| State | Published - 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being -
SDG 11 Sustainable Cities and Communities
Keywords
- Adaboost
- Driving safety
- Fuzzy
- Histogram of oriented gradient
- Stereo vision
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