Fuzzy-based collision avoidance system for autonoumous driving in complicated scenarios /
The overall safety of human beings and the avoidance of imminent accidents on roads was the primary motivation for this research. Accidents on roads have caused many incidents resulting to death, which refers to human mistakes after avoiding natural disasters that could occur on roads. We also can c...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
Kuala Lumpur :
Kulliyyah of Engineering, International Islamic University Malaysia,
2018
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| Subjects: | |
| Online Access: | http://studentrepo.iium.edu.my/handle/123456789/4833 |
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| Summary: | The overall safety of human beings and the avoidance of imminent accidents on roads was the primary motivation for this research. Accidents on roads have caused many incidents resulting to death, which refers to human mistakes after avoiding natural disasters that could occur on roads. We also can classify human mistakes into mental mistakes, which includes driving under the influence of alcohol, psychological problems or mental retardation. The second classification comprises the mistakes that could occur from the humans when they are in a healthy state of mentality. These accidents occur when the driver is not fully focused on the road, or there are obstacles in blind areas which are difficult to detect, due to fog or any other natural causes. The first step to assist the driver is to create a fully automatic system to avoid collisions, which is called a collision avoidance system (CAS). In this study, we present a fuzzy-based control approach for smart and safe obstacle avoidance in complicated traffic scenario, where there are static and dynamic obstacles (e.g. broken-down vehicles, wrong parking road-side vehicles, or moving vehicles, etc.). The fuzzy system takes an optimal decision to control the car throttle, braking, and steering to avoid collision using the available information on the road map (i.e. the distance to obstacles, the current traffic in the neighbouring lanes, the velocity of the front and rear car, etc.). Simulation results from three different scenarios involving a combination of dynamic and static or broken-down vehicles demonstrate that the fuzzy controlled car can effectively avoid obstacles or collisions in complicated traffic situations. |
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| Physical Description: | xvi, 77 leaves : colour illustrations ; 30cm. |
| Bibliography: | Includes bibliographical references (leaves 67-77). |